experiments systems biology

10 Awesome Biology Experiments Ideas For High School Aspirants

Science is no fun without practical experiments. Unlike middle school, where you limit your study and inquiry of science to the theoretical realm, high school has a different scene. Experiments are a major part of studying science in high school, and biology all the more so. Biology is fascinating. It makes us wonder at the complex system which makes the human body function efficiently; it has all the answers to the questions of death, sickness, and life. But we must admit that only the theoretical explanation of these complex concepts never suffices to give us a satisfactory understanding. That is where practical experiments come to the rescue. 

Therefore, this post will cover 10 fascinating biology experiments that high school students can do independently, even at home. 

Cool Experiments To Do In Your Bio Lab

While many are intrigued by art competitions , others are moved toward robotic classes. However, in a bunch of students, there are a few who love biology experiments. Hence, here are a few experiments that can be tried out by high schoolers if biology is the subject that piques their interest:

1. Extract DNA

Everyone knows DNA is the agent behind our hereditary traits. Residing in the cell’s nucleus, it guides major aspects of our physiognomy. Usually, the DNA is not visible to the naked eye, you need a powerful microscope to view it, but with this experiment, you can have a fine look at the DNA with this DNA extracting experiment. 

Basically, you will be forcefully breaking down some cell walls of the extracted cells by dipping it into your extraction solution. Adding 35ml of dish soap and 5gm of salt in 240 ml of water will give you the extraction solution. Dip and mix some mashed banana slices into the extract, leading the DNA to head out into the solution. Then we will use some alcohol to force the DNA to join up into large chains that we can actually see. You will get a fluffy white substance, the DNA that is visible to the naked eye, made possible by this extraction experiment. 

2. Dissect A Flower

Everyone has theoretically seen and known the different parts of a flower. Some exceptional students might even have that picture inscribed in their memory. Very well if you have that, but the hands-on experience of viewing those parts with your own eyes can definitely beat any other theoretical picture-viewing experience. 

So, first thing first, go out and choose a bloom. Observe the flower and point out the petals, stamen, and pistil. Use a razor to remove the stamen and observe the Filament and Anther under magnifying glasses. Wipe out some pollen grains and have a detailed look at it under the microscope while you are at them. Next up, remove the pistil and observe your flower’s ovary, stigma, and style with a magnifying glass. This is the simplest yet a fascinating experiment on the list. 

3. Raise A Butterfly

Again, we have the theoretical knowledge of the life cycle of a butterfly. Yet it takes us by surprise and wonder when we see the process through our own eyes. So, get ready to be fascinated by a butterfly’s journey from an ugly worm to a colourful butterfly. 

The process is easy. You get a caterpillar, observe it daily, and note the changes. The changes will be as precise as your books have always told you. First off, a butterfly lays an egg and a caterpillar hatches from the egg. The caterpillar eats and grows, shedding its skin several times to accommodate its growing belly. Once the caterpillar reaches the right size, it sheds its skin for the last time, revealing the chrysalis, which quickly hardens. Inside the chrysalis, the caterpillar goes through metamorphosis and changes into a butterfly. At the right time, the butterfly breaks out. It hangs onto the chrysalis for a bit, just until its wings dry out and harden. Then, it flies off in search of nectar. 

So, in the end, you will be sitting back and enjoying the release of the butterfly you raised with your own very hands.   

4. Frog Dissection

Dissecting a frog is one of those lab activities that fascinate and chill you simultaneously. But before you start with the dissection, make sure you take note of all the outer organs like the skin, legs, head, digits, and urinary outlet (cloaca) of the specimen. 

You will need a good scalpel, pins, and a dissection tray to cut the frog. After these things are in place, you are all set to perform the three significant incisions on the specimen. Start by cutting from the jaw to down between the legs, then make two horizontal incisions, one above the neck and the other towards the bottom of its legs. At this point, you will start seeing some organs residing in the abdominal cavity. Repeat the same incision on the frog’s abdomen to open the abdominal cavity. Observe the heart, and identify the major organs like the liver, stomach, intestines, and oviducts. 

This experiment will definitely leave you amazed at the complex system of nerves, muscles, and bloods that functions interdependently to sustain a living being. However, this experiment should be done in front of teachers and professors in the lab.

5. Diversity Among Plant Samples

Another simple biology experiment involves going into your natural environment, such as a local park, to observe diversity among plant samples. To make the experiment more detailed, students can rub collected samples on filter paper to observe which plants present which colors. 

Teens can work to find out why certain plants present certain colors. They can also dissect the flowers of the plants and paste the dissected parts of the flowers in their observation notebooks to make a note of the differences between the flowers of the different species of plants. 

6. Yeast Experiment

Another simple and easy experiment on the list for high schoolers is the yeaThis experiment is easy because it only involves taking out four different food samples on different plates and a long-time observation of the mold that grows on each sample. 

Studying mold is an excellent way to learn more about ecology and biology. This experiment compares how fast mold grows on different types of foods kept in many American homes. Some of the foods are generally kept in refrigerators to extend shelf life, while others are commonly stored at room temperature. This experiment shows that certain foods grow mold faster than others, which is one reason why these foods are often kept in the refrigerator. 

Going a step further, the students can also do research inspired by this experiment and find answers to questions such as: what makes a mold grow? And how does one prevent their growth?

7. Look at cell division under the microscope

Cheap digital microscopes with high magnification power that can be directly connected to your laptop or smartphone are easily available in the market nowadays. You can make use of such microscopes to observe every little thing you find at home or outdoors.  

A great experiment to do at home with a microscope is to look at how cells divide in different organisms. One of the easiest is baker’s yeast. With a magnification of at least 400x, you can start discerning the shapes of individual yeast cells in water. You will notice that some of them have little buds on them, which is the way they grow and divide. 

Taking it one step further, you can also take the tip of the onion’s root and observe them to study the different stages of mitosis as well. 

8. Ferment your own food

Bacteria and yeast are practically geniuses in the art of fermentation. Humans have been taking their help for the longest time to make food items such as bread and alcohol. And it is quite easy to ferment your own food at home. 

In most cases, you need a starter culture of the bacteria or fungi that make the food you will be fermenting. You can get it from someone already doing fermentation at home or buy it online. Many options range from kombucha, kefir, or mead to yogurt, cheese, kimchi, and sauerkraut. Each fermented food has different requirements, so ensure you have everything you need before starting. After you have everything in place, you are ready to experiment with this fermented food and its varied tastes. 

9. Examining Fingerprints

The tips of each finger of your hand have a combination of lines and features in distinctive patterns that we call fingerprints. Fingerprints are one of the fascinating features of the human body. We have been told that each of us is unique in our light, and our fingerprints prove it to be so. You can analyze your own uniqueness by analyzing your very own fingerprints in this project. All you need is paper, magnifying glass, and stamp ink.

First, you need to press a finger against the ink pad and then against a piece of paper. Then, use the magnifying glass to examine the fingerprints and look for arches, whorls, and loops. You can record your finding on your paper. And then take a friend’s fingerprints to analyze the differences. 

10. Create A Fall Leaf (Or Signs Of Spring) Journal

Biology is all about studying life and learning more about our natural surroundings. A Fall Leaf journal or a Signs of Spring journal will help your students learn about the trees and bushes that are in your area. This experiment is easy, needs minimal effort, and is fun and exciting as well. 

Things To Remember

Science experiments are interesting by nature, but this aspect of their nature shouldn’t keep us from maintaining our share of vigilant caution. Science experiments could sometimes wreak havoc if we do not take enough caution while doing these experiments. Therefore, in order to prevent yourself from ruining your own experiments, you have to follow some safety instructions while doing these experiments. 

Wear covered shoes and long pants while performing any experiment, and keep your hair up so it can’t fall into your experiment or a flame. Don’t carelessly sniff or taste any chemicals; don’t just experiment with everything you get your hands on. Make sure you have your full attention in the experiments, and handle everything with care, especially sharp objects like knives or objects that could produce a flame. And at the end of your experiment, you should also know how to dispose of the waste properly. 

In the end of it, what matters the most is that we genuinely imbibe the lessons that we learn from our experiments. These biology experiments will get you further into the fascinating world of biology. If you want to further your knowledge, you may also visit science labs, perform science experiments in the lab, attend workshops and seminars, and meet people and learn from their experiences. 

Keep learning, keep experimenting, and keep enjoying the process of learning. 

Sananda Bhattacharya, Chief Editor of TheHighSchooler, is dedicated to enhancing operations and growth. With degrees in Literature and Asian Studies from Presidency University, Kolkata, she leverages her educational and innovative background to shape TheHighSchooler into a pivotal resource hub. Providing valuable insights, practical activities, and guidance on school life, graduation, scholarships, and more, Sananda’s leadership enriches the journey of high school students.

Explore a plethora of invaluable resources and insights tailored for high schoolers at TheHighSchooler, under the guidance of Sananda Bhattacharya’s expertise. You can follow her on Linkedin

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Top 30 Biology Experiments for High-School

The field of biology offers a wide range of fascinating experiments that can deepen our understanding of the living world around us. From studying the behavior of cells to investigating the intricacies of ecosystems, biologists use a variety of methods to uncover the secrets of life.

We’ve compiled a captivating list of 30 biology experiments that are both educational and fun and also suitable for a wide range of ages.

These hands-on educational activities will not only deepen your appreciation for the intricacies of life but also fuel your curiosity and passion for scientific exploration.

So, roll up your sleeves, gather your lab equipment, and prepare to embark on an exciting adventure through the fascinating world of biology-based science experiments!

1. Grow a Butterfly

Students can gain knowledge about the various phases of development, from the egg to the larva to the pupa to the adult butterfly, by studying and taking care of a butterfly during its whole life cycle. This offers students a special chance to learn about the insect life cycle and the metamorphosis process.

Learn more: Elemental Science

2. Dissecting a Flower

Dissecting a flower can aid students in honing their analytical and observational skills. This may also aid in their comprehension of how a flower’s various components interact to facilitate reproduction, which is the flower’s main objective.

Learn More: How to Dissect a Flower

3. Extracting a DNA

The extraction of DNA is an excellent experiment for high school students to gain a better understanding of the principles of molecular biology and genetics. This experiment  helps students to understand the importance of DNA in research and its applications in various fields, such as medicine, biotechnology, and forensics.

Learn more: Extracting DNA

4. Looking at Fingerprints

Exploring fingerprints can be a fun and intriguing experiment. This experiment encourages students to develop their problem-solving skills and attention to detail, as they must carefully analyze and compare the various fingerprint patterns.

Fingerprint analysis is a fascinating and engaging experiment that can spark an interest in forensic science and provide students with a hands-on learning experience.

Learn more: Directions to Examine a Fingerprint

5. Cultivate Bacteria on Home Made Agar

This experiment provides a hands-on learning experience for students to understand the principles of microbiology and the techniques used in bacterial culture.

This experiment can also help students to understand the importance of bacteria in our daily lives, their role in human health, and their applications in various fields, such as biotechnology and environmental science.  

Learn more: Grow bacteria on Homemade Agar Plates

6. Make a Bioluminescent Lamp

This experiment provides an excellent opportunity for high school students to learn about bioluminescence and the principles of genetic engineering.

Creating a bioluminescent lamp is a fun and engaging way to explore the intersection of biology, chemistry, and physics, making it a perfect experiment for students interested in science and technology.

Learn more: Make Glowing Water

7. Make Plants Move with Light

This experiment can help students understand the role of light in plant growth and photosynthesis and the importance of light as an environmental factor for plant survival. 

Learn more: Experiments with Phototropism

8. Test the Five-Second Rule

The “5-second rule” experiment is a simple and fun way to investigate the validity of the popular belief that it is safe to eat food that has been dropped on the ground for less than 5 seconds.

The experiment is an engaging and informative way to explore the science behind a common belief and promote critical thinking and scientific inquiry among students.

Learn more: Five Second Rule

9. Examine How Antibiotics Affect Bacteria

This experiment is an excellent opportunity for high school students to develop their laboratory skills, such as aseptic technique and bacterial culture, and understand the principles of antibiotic resistance and its implications for human health.

Examining how antibiotics affect bacteria is a fascinating and educational experiment that promotes scientific inquiry and critical thinking among students.

Learn more: Learn About Bacteria

10. Look for Cell Mitosis in an Onion

This experiment is an excellent opportunity for high school students to develop their microscopy skills and understand the biological basis of growth and development in plants. This experiment is a fun and informative way to explore the world of cells and their role in the growth and development of living organisms.

Learn more: Onion Root Mitosis

11. Test the Effects of Disinfectants

Testing the effects of disinfectants is an important process in determining their efficacy in killing or reducing the number of microorganisms on a surface or object. Disinfectants can be hazardous if not used correctly, and testing their effects can help students understand how to use them safely.

Students can learn about proper handling techniques and how to interpret safety labels and warning signs.

Learn more: Antiseptic and Disinfectants

12. Microwave Seed Gardening

Microwave seed gardening is a quick and efficient method of germinating seeds, microwave seed gardening can be a useful method for starting seeds, but it should be used with care and in conjunction with other germination methods to ensure the best possible results. 

Learn more: Microwave plant

13. Water Bottle Bacteria Swab

This experiment can be a fun and informative way to learn about the importance of keeping water bottles clean and free from harmful bacteria. It can also be used to compare the cleanliness of different types of water bottles, such as metal, plastic, or glass.

Learn more: Swabbing Water Bottles

14. Frog Dissection

Frog dissection can be a valuable tool for teaching anatomy and physiology to high school students, as it provides a comprehensive examination of the internal organs and systems of the frog.

Dissection can be a valuable and engaging experiment for high school students interested in biology and life science.

Learn more: Frog Dissection

15. Witness the Carbon Cycle in Action

By witnessing the carbon cycle in action, learners can gain a better understanding of the interconnectedness of different parts of the Earth’s system and the impact that human activities can have on these processes.

Learn more: Carbon Cycle Lab

16. Investigate the Efficacy of Types of Fertilizer

Investigating the efficacy of different types of fertilizer can be an interesting and informative way to learn about plant growth and nutrition. Investigating the efficacy of different types of fertilizer is a practical and engaging way to learn about plant nutrition and the role of fertilizers in agriculture.

Learn more: Best Fertilizer

17. Explore the Impact of Genetic Modification on Seeds

Exploring the impact of genetic modification on seeds is a fascinating and relevant topic that can spark meaningful discussions and encourage learners to think critically about the role of science and technology in society.

Learn more: Genetically Modified (GM) Crops

18. Yeast Experiment

Another easy to perform experiment for high school students is the yeast. This experiment is simple since all that is required is the removal of four different food samples onto separate plates and a thorough examination of the mold that develops on each sample over time.

Learn more: Grow Yeast Experiment

19. Taste Perception 

The human tongue has specialized taste receptors that respond to five primary tastes: sweet, salty, sour, bitter, and umami (savory). Taste perception plays an important role in determining food preferences and dietary habits, as well as influencing the overall eating experience.

Learn more: Taste perception

20. Pea Plant Genetics

A classic pea plant genetics experiment involves cross breeding pea plants with different traits, such as flower color, seed shape, or pod shape.

This experiment can be conducted in a controlled environment, such as a greenhouse, by manually transferring pollen from one plant to another.

Learn more: Gregor Mendel Pea Experiment

21. Comparing Animal and Plant Cells

Comparing animal and plant cells is an important exercise in biology education. Both animal and plant cells are eukaryotic cells, meaning they contain a nucleus and other membrane-bound organelles.

This exercise can help students understand the structure and function of cells, as well as appreciate the diversity of life on Earth.

Learn more: Comparing Plant Cell and Animal Cell

22.  Testing Bacteria 

Bacteria are easily accessible and can be grown in a laboratory or even at home with simple equipment and materials. This makes it a practical and cost-effective experiment for schools with limited resources.

Learn more: How to grow Bacteria and more

23. The Effect of Light on Growth

Light is a fundamental environmental factor that plays a crucial role in the growth and development of plants. By conducting this experiment, students can gain a deeper understanding of how light affects plant growth and why it is important.

Learn more: The effect of light in Plant Growth

24. Planaria Regeneration

Planaria regeneration allows students to design their own experiments, as they can choose which body parts to remove and study the effects of different variables, such as temperature, pH, or chemical treatments on the regeneration process.

Planaria are easy to obtain and maintain in a laboratory or classroom setting. They are also affordable, making it an ideal experiment for schools with limited resources.

Learn more: Planaria Experiment

25. Making a Seed Board

Making a seed board can be a fun and engaging activity for students, as they can see the progress of their plants over time and share their results with others. It can also foster a sense of responsibility and ownership in caring for their plants.

26. Design an Owl Pellet

Dissecting an owl pellet provides a hands-on learning experience for students, allowing them to practice skills in scientific observation, data collection, and analysis. Students can also learn about the anatomy of the prey species found in the owl pellet.

27. Grow an Herbal Cutting

Growing an herb cutting provides a hands-on learning experience for students, allowing them to practice skills in plant care, experimental design, and data collection. Students can learn about the different stages of plant growth and the factors that affect it.

28. Eat a Cell Model

Creating an edible cell model connects to various disciplines, such as biology, anatomy, and nutrition. Students can learn about the different organelles that make up a cell and their functions, as well as the nutritional value of the food materials used in the model

29. Make a Habitat Diorama

Making a habitat diorama provides a hands-on learning experience for students, allowing them to practice skills in research, creative design, and presentation. Students can learn about different ecosystems and the organisms that inhabit them.

30. Create a Fall Leaf (or Signs of Spring) Journal

Creating a fall leaf (or signs of spring) journal provides a hands-on learning experience for students, allowing them to practice skills in observation, data collection, and analysis. Students can learn about the changes that occur in nature during the fall or spring season.

Similar Posts:

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Open Access

Peer-reviewed

Research Article

Maximizing the Information Content of Experiments in Systems Biology

Contributed equally to this work with: Juliane Liepe, Sarah Filippi

Affiliation Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London, United Kingdom

Affiliation Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland

* E-mail: [email protected]

Affiliations Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London, United Kingdom, Institute of Chemical Biology, Imperial College London, London, United Kingdom

• Juliane Liepe, 
• Sarah Filippi, 
• Michał Komorowski, 
• Michael P. H. Stumpf

• Published: January 31, 2013
• https://doi.org/10.1371/journal.pcbi.1002888
• Reader Comments

Our understanding of most biological systems is in its infancy. Learning their structure and intricacies is fraught with challenges, and often side-stepped in favour of studying the function of different gene products in isolation from their physiological context. Constructing and inferring global mathematical models from experimental data is, however, central to systems biology. Different experimental setups provide different insights into such systems. Here we show how we can combine concepts from Bayesian inference and information theory in order to identify experiments that maximize the information content of the resulting data. This approach allows us to incorporate preliminary information; it is global and not constrained to some local neighbourhood in parameter space and it readily yields information on parameter robustness and confidence. Here we develop the theoretical framework and apply it to a range of exemplary problems that highlight how we can improve experimental investigations into the structure and dynamics of biological systems and their behavior.

Author Summary

For most biological signalling and regulatory systems we still lack reliable mechanistic models. And where such models exist, e.g. in the form of differential equations, we typically have only rough estimates for the parameters that characterize the biochemical reactions. In order to improve our knowledge of such systems we require better estimates for these parameters and here we show how judicious choice of experiments, based on a combination of simulations and information theoretical analysis, can help us. Our approach builds on the available, frequently rudimentary information, and identifies which experimental set-up provides most additional information about all the parameters, or individual parameters. We will also consider the related but subtly different problem of which experiments need to be performed in order to decrease the uncertainty about the behaviour of the system under altered conditions. We develop the theoretical framework in the necessary detail before illustrating its use and applying it to the repressilator model, the regulation of Hes1 and signal transduction in the Akt pathway.

Citation: Liepe J, Filippi S, Komorowski M, Stumpf MPH (2013) Maximizing the Information Content of Experiments in Systems Biology. PLoS Comput Biol 9(1): e1002888. https://doi.org/10.1371/journal.pcbi.1002888

Editor: Andrey Rzhetsky, University of Chicago, United States of America

Received: July 27, 2012; Accepted: November 30, 2012; Published: January 31, 2013

Copyright: © 2013 Liepe et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors greatfully acknowledge funding from the Wellcome Trust (through a PhD studentship to JL; www.wellcome.ac.uk ), MRC (through a Biocomputing Research Fellowship to SF; www.mrc.ac.uk ) and BBSRC (to MK and MPHS; BB/G020434/1, www.bbsrc.ac.uk ). MPHS is a Royal Society Wolfson Research Merit Award Holder ( www.royalsociety.org ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Mathematical models of biomolecular systems are by design and necessity abstractions of a much more complicated reality [1] , [2] . In mathematics, and the theoretical sciences more generally, such abstraction is seen primarily as a virtue which allows us to capture the essential features or defining mechanisms underlying the workings of natural systems and processes. But while qualitative agreement between even very simple models and very complex systems is easily achieved, formally assessing whether a given model is indeed good (or even just useful) is notoriously difficult. These difficulties are exacerbated in no small measure for many of the most important and topical research areas in biology [3] – [5] . The regulatory, metabolic and signalling processes involved in cell-fate and other biological decision-making processes are often only indirectly observable; moreover, when studied in isolation their behavior can often be markedly altered compared to the experimentally more challenging in vivo contexts [6] . The so-called “inverse problem” — to learn, construct or infer mathematical or mechanistic models from experimental data — is often considered (see e.g. Brenner [7] ) as one of the major problems facing systems biologists.

Inferential tools have been developed that, given some observed biological data and a suitable mathematical candidate model, provide us with parameters that best describe the system's dynamics. Unfortunately obtaining reliable parameter estimates for dynamical systems is plagued with difficulties [16] , [17] . Usually sparse and notoriously noisy data are fitted using models with large number of parameters [18] . As a result, over-parameterized models tend to fit to the noisy data but may loose confidence in predictive behavior. Conventional fitting approaches to such data routinely fail to capture this complexity by underestimating the uncertainty in the estimated parameters, which substantially increases the uncertainty in prediction of model behavior.

Performing different experiments is costly, however, in terms of both money and time, and not all experiments are equally informative. Ideally we would like to perform only those experiments which yield substantial and relevant information. We regard any information that decreases our uncertainty about model parameters or model predictions as relevant . As we will show below, what is substantial information is then easily and naturally resolved. We will show, for example, that experimental interventions differ in the amount of information they provide e.g. about model parameters. Equally some experiments provide insights that are more useful for making predictions about system behavior than others. It may seem surprising that we consider parameter inference and prediction of output separately, but this merely reflects the fact that not all parameters contribute equally to system output: varying some parameters will have huge impact on the output, while varying other parameters will lead to negligible changes in the output. By making the reduction in uncertainty of predicted model behavior the target of experimental design we explicitly acknowledge this.

Experimental design in systems biology is different from classical experimental design studies. The latter theory was first developed at a time when the number of alternative hypotheses was smaller than the amount of available data and replicates [19] . Systems biology, on the other hand is hypotheses rich and data rarely suffice to decide clearly in favour of one model unambiguously. Moreover for dynamical systems, as a host of recent studies have demonstrated, generally less than half of the parameters are tightly confined by experimental data [16] , [17] . Together these two challenges have given rise to a number of approaches aimed at improving our ability to develop mechanistic models of such systems. Here we meld concepts from Bayesian inference and information theory to guide experimental investigations into biological systems to arrive at better parameter estimates and better model predictions.

Several authors have used the information theoretical framework, in particular the expected gain in Shannon information to assess the information content of an experiment [20] – [24] . Although the methodology of Bayesian experimental design is well established, its applicability has been computationally limited to small models involving only several free parameters. Recently their use for systems biology becomes possible as a result of increased computational resources. Vanlier et. al proposed an approach that uses the Bayesian predictive distribution to asses the predictive power of experiments [25] . Huan and Marzouk used a framework, which is similar to ours, in that it maximizes mutual information via Monte Carlo approximation to find optimal experiments [26] ; but they only focus on parameter inference and ignore prediction. Furthermore they only apply their method to systems with small number of parameters. Here we demonstrate how such an approach can be utilized to analyse multi-parameter models described by ordinary differential equations (ODEs) regarding both, parameter inference and prediction of system behavior. The latter is especially useful when one aims to predict the outcome of an experiment which is too laborious or impossible to perform. Our approach improves on previous methods [25] – [32] in a number of ways: first we are able to incorporate but do not require preliminary experimental data; second, it is a global approach that is not limited to some neighbourhood in parameter space unlike approaches solely based on e.g. the Fisher information [29] , [33] ; third, we obtain comprehensive statistical predictions (including confidence, sensitivity and robustness assessments if desired); and we are very flexible in the type of information that we seek to optimize.

Below we first develop the theoretical concepts before demonstrating the use (and usefulness) of the Bayesian experimental design approach in the context of a number of biological systems that exemplify the set of problems encountered in practice. In order to demonstrate the practical applicability of our approach we investigate two simple models (repressilator and Hes1 systems), as well as a complex signalling pathway (AKT) with experimentally measured dynamics.

Information content of experimental data

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• TIFF original image

https://doi.org/10.1371/journal.pcbi.1002888.g001

Below we use three examples of different complexity to show how this combination of rigorous Bayesian and information theoretical frameworks allows us to design/choose optimal experimental setups for parameter/model inference and prediction, respectively.

Experiment selection for parameter inference

To investigate the potential of our experimental design method for parameter estimation we first apply it to the repressilator model, a popular toy model for gene regulatory systems [40] . It consists of three genes connected in a feedback loop, where each gene transcribes the repressor protein for the next gene in the loop (see Figure 2 A and B ).

https://doi.org/10.1371/journal.pcbi.1002888.g002

https://doi.org/10.1371/journal.pcbi.1002888.g003

https://doi.org/10.1371/journal.pcbi.1002888.g004

Experiment selection for prediction

We next focus on a scenario where we aim to predict the behaviour of a biological system [44] under conditions for which it is not possible to obtain direct measurements. We consider as an example the phosphorylation of Akt and ribosomal binding protein S6 in response to a epidermal growth factor (EGF) signal. Figure 5 A shows the pathway of interest: the EGF growth factor binding to the activated receptor EGFR leads to phosphorylation of EGFR and a signal cascade which results in the phosphorylation of Akt (pAkt) which in turn can activate downstream signalling cascades and leads to the phosphorylation of S6 (pS6); a corresponding mathematical model is shown in Figure S7 [45] .

https://doi.org/10.1371/journal.pcbi.1002888.g005

https://doi.org/10.1371/journal.pcbi.1002888.g006

We have found that maximizing the mutual information between our target information — here either model parameter values or predictions of system behaviour — and the (simulated) output of potentially available experiments offers a means of arriving at optimally informative experiments. The experiments that are chosen from a set of candidates are always those that add most to existing knowledge: they are, in fact, the experiments that most challenge our current understanding of a system.

This framework has a number of advantages: First, we can simulate cheaply any experimental set-up that can in principle be implemented; second, using simulations allows us to propagate the model dynamics and to quantify rigorously the amount of (relevant) information that is generated by any given experimental design; third, our information measure gives us a means of meaningfully comparing different designs; finally, our approach can be used to design experiments sequentially — our preferred route as this will enable us to update iteratively our knowledge of a system along the way — or in parallel, i.e. selecting more than one experiment. Previous approaches had taken a more local approach [25] , [29] , [30] , [47] that relied on initial parameter guesses and often data; our approach also readily incorporates different stimulus patterns [48] .

Here we have focussed on designing experiments that increase our ability to estimate model parameters and to predict model behaviour. The latter depends on model parameters in a very subtle way: not all parameters affect system output equally and under all conditions. Target conditions could, for example, include clinical settings which are generally not experimentally amenable (at least in early stage research); here the current approach offers a rationale for designing [49] therapeutic interventions into complex systems based on investigations of suitable model systems. In this study we provide an approach to chose the optimal experiment out of a finite and discrete set of possible experiments. Experimental design with a continuous set of experiments requires a different approach, as for example shown in [50] .

With an optimal design we can overcome the problems of sloppy parameters [16] (which are, of course, dependent on the experimental intervention chosen [17] ) and can narrow down the posterior probability intervals of parameters. We would like to reiterate, however, the importance of considering joint distributions rather than merely the marginal probabilities of (or the confidence regions associated with) individual parameters: parameters of dynamical systems tend to show high levels of correlation (i.e. we can vary them simultaneously in a way that does not affect the output of the system — at least in some areas of parameter space) and their posterior probability distributions often deviate from normality (which also motivated the use of information theoretical measures which can deal with non-linearities and non-Gaussian probability distributions).

The approach we presented here yields the potential for model discrimination or checking the target of our analysis [48] , [51] , and, for example, choose experimental designs that maximize our ability to distinguish between competing alternative hypotheses or models. All of this is straightforwardly reconciled in the Bayesian framework, which also naturally lends itself to such iterative procedures where “today's posterior” is “tomorrow's prior” and models are understood increasingly better as new, more informative data are systematically being generated.

Information theoretic design criteria

Reducing uncertainty in model parameters

Reducing uncertainty in an experimental outcome

Estimation of the mutual information

Technical details.

Approximate Bayesian Computation (ABC)

Estimation of the entropy

Experimental data

The experimental data sets used to investigate the Akt model were collected and published by the lab of S. Kuroda. The data are normalised Western blot measurements as described in [45] .

Supporting Information

https://doi.org/10.1371/journal.pcbi.1002888.s001

https://doi.org/10.1371/journal.pcbi.1002888.s002

https://doi.org/10.1371/journal.pcbi.1002888.s003

https://doi.org/10.1371/journal.pcbi.1002888.s004

https://doi.org/10.1371/journal.pcbi.1002888.s005

https://doi.org/10.1371/journal.pcbi.1002888.s006

https://doi.org/10.1371/journal.pcbi.1002888.s007

https://doi.org/10.1371/journal.pcbi.1002888.s008

https://doi.org/10.1371/journal.pcbi.1002888.s009

Figure S10.

https://doi.org/10.1371/journal.pcbi.1002888.s010

Figure S11.

https://doi.org/10.1371/journal.pcbi.1002888.s011

Author Contributions

Conceived and designed the experiments: JL SF MK MPHS. Performed the experiments: JL SF. Analyzed the data: JL SF. Contributed reagents/materials/analysis tools: JL SF MK. Wrote the paper: JL SF MK MPHS.

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A Biologist’s Guide to Design of Experiments

Biology is a notoriously difficult research area, especially for replicating results. To paraphrase from a film that has inspired thousands of people to get into this field: life finds a way (of behaving unexpectedly). Because everything is so interconnected in biology, the one-factor-at-a-time (OFAT) approach is usually taken to investigate biological systems. But what if there were a better way to gain insights into the holistic nature of biology and explore the interconnectedness of various factors while maintaining scientific accuracy?

Well, there is. It’s called Design of Experiments (DOE).

The term ‘Design of Experiments’ can be a confusing one. Of course a scientist is going to design their experiment. In fact, what we are referring to when we say Design of Experiments (or DOE) is   a branch of applied statistics that can be applied to experimental design.   This systematic method allows scientists to simultaneously investigate the impact of different factors on an experimental process, while also taking the interactions between factors into consideration. 

There are plenty of benefits to performing DOE. Compared to other experimental approaches, DOE saves time and resources when performing experiments, whilst providing deeper insight into complex systems. 

If DOE is the key to unlocking biological complexity, why is it not used all the time?

Before we dive into that, let’s first look at the more traditional experimental approaches that scientists use to study complex systems. 

OFAT vs DOE

In order to fully comprehend the power of DOE, it’s helpful to have an understanding of more commonly used approaches, such as investigating a single factor at a time. 

One-factor-at-a-time (OFAT) methods are incredibly common in biological research.  One component (factor) is picked at a time and its values (levels) are varied, keeping all other known components constant. In this way, the impact of the selected component can be tested at each variation.

However, experimental optimization using OFAT methods limits the breadth of the possible design space and, by neglecting certain factors or their interactions, often identifies an incorrect optimal state of the system. By testing biological factors in isolation, scientists can be left blind to the interactions between other factors. 

Changing one factor at a time (OFAT, left) means effects are easy to distinguish but there is less information on how factors interact, a critical feature of complex systems. Using statistical techniques to design experiments that explore combinations of factor settings allows their effects to be understood in combination (DOE, right). Optimal results which would otherwise be missed can then be discovered.

In contrast to OFAT experimentation, the systematic structure of experimental conditions in DOE allows researchers to vary and test multiple factors in one go. By simultaneously investigating the effect of many factors on a process of interest, researchers are provided with a more complete understanding of the biological system they are studying.

DOE requires fewer resources for the amount of information obtained , saving on time and materials. By measuring multiple factors at once, you are reducing the number of biological and technical replicates required for a statistically accurate measurement compared to measuring those factors individually. 

Additionally, because some factors have a direct or indirect relationship with others, measuring the effect of these factors simultaneously can give better insights into a biological process. These relationships or “interactions” often underpin complex and non-intuitive trends in the data which, in turn, hold key insight into the underlying biological complexity of a system or process. 

Interactions between experimental factors are everywhere in bioprocessing but, with traditional experimentation, they are hard to investigate, and often go ignored or unrecognized. In fermentation, for example, pH readout is affected by the temperature of the medium and will shift as temperature changes, even before the medium is inoculated. By using a DOE approach researchers can pin down crucial interacting factors and gain crucial understanding and insight into how they can be exploited or controlled to improve system performance. When working in highly complicated systems and processes, such as in the production of biological therapeutics, DOE is the best approach to optimizing a process.

Even with all its benefits, many biologists still don’t perform DOE. This is for a number of reasons. DOE can be daunting to execute when the interactions of large numbers of factors need to be measured.  Many biologists are still unfamiliar with DOE if they didn’t study it or haven’t used it before, and it may be hard to know where to start.

Getting started with DOE 

As with anything, there can be a learning curve to setting up and starting to perform DOE. 

DOE can be difficult to plan and analyze; however experimental execution of a DOE can be particularly challenging, especially for those less comfortable with automation. DOE can be performed manually for two or three factors simultaneously, but as the number of factors increases or if you have liquid handling robots to carry out more complex experiments, the planning and attention to detail required to execute complex DOE designs becomes a significant burden,  you will need to use specialized software such as JMP to help design and model your experiments, and build a statistically accurate picture of your process. Whatever software package you use, there is plenty of support and information to help you design and analyze your experiment. 

One benefit of the COVID pandemic is that companies have put a lot of demos and resources online. You can see DOE in action with   liquid handling and automation here , and how software tools can   help design and carry out DOE experiments . Another great resource that we highly recommend for people starting out with DOE is the book DOE Simplified: Practical Tools for Effective Experimentation by Mark J. Anderson and Patrick J. Whitcomb.

Let us help you get started with DOE. Join our DOE masterclass webinar for biologists.

DOE and Machine Learning 

Machine Learning (ML), whereby computational algorithms interpret complex data, is a methodological approach to solving optimization problems when there is a lot of data available.   DOE can help ML approaches become more effective by finding the optimal algorithmic parameter settings, while ML can support DOE by better detecting the effects of factors and their interactions. Biological experimentation can be expensive, but through the use of DOE, coupled with ML, it may be possible to build Machine Learning capabilities using smaller (and less costly) data sets. This is especially useful as experiments scale up and the amount of data generated is difficult to collect and process manually.

Liquid handling technologies allow us to   consider more complex DOE experiments than ever before as they transcend the human limitations of carrying out physical work. This results in much more data captured by the software, as well as metadata that contextualizes the main data points of the factors under examination. By leveraging the power of ML in data analysis, the effect of the metadata can be considered in addition to the main data points in how outputs are affected by a process.

Transforming the biological research landscape with DOE

DOE is a powerful statistical and experimental design tool that allows biological researchers to make their processes more defined and predictable. The methodology is well suited to automating liquid handling and an array of software tools exist to help translate DOE designs into viable experiments. The data bottleneck can be addressed manually for small-scale DOE designs, but new software tools like ML can tease out new insights from the data allowing for more predictable and accurate research in the traditionally unpredictable field of biology. 

DOE is already a cornerstone of industry standards   supporting Quality by Design principles and the adoption of Computer-Aided Biology tools in this space is well underway. DOE and supporting CAB technologies are poised to transform the biological research landscape, uncovering new insights from data and ensuring biological research is more robust and precise than ever.

Learn more about DOE from our in-house experts by clicking here .

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Systems biology for beginners

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6 Easy Biology Science Experiments for Kids

Let’s dive into studying life and living organisms with a new set of biology experiments for kids! These are all easy and simple to do at home or in your classroom, and all of them are liquid or water-based, so you’ll likely have everything you need on hand to bring these science projects to life. We’ll be exploring osmosis, chromatography, homogenization, transpiration, capillary action, and evaporation.

Related: Check out our other science experiments for kids posts on physics and chemistry !

Gummy Bear Osmosis

“Solute” is a general term that refers to a molecule dissolved in a solution. In a salt water solution, for example, the salt molecules are the solutes. The more salt we put in the solution, the more we increase the concentration of solutes.

Water moves from an area with a lower concentration of solutes to an area with a higher solute concentration. This movement of water molecules is called “osmosis.” In order to examine the process of osmosis and observe how it works, we can look at what happens to gummy bears when they are left to soak in different solutions overnight.

Gummy Bear Osmosis Printable Instructions

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-------------------------------------------------------, what you’ll need:.

• Two container such as bowls, cups, or jars
• Measuring cup
• Gummy bears
• Add ½ cup of water to each of the two empty containers. Add 1 teaspoon of salt to one of the containers and stir well.
• Drop a gummy bear into each container and leave it 8 hours or overnight.
• Observe what happened to each gummy bear. Compare the gummy bears to each other, and also to a gummy bear that was not left to soak overnight.

What’s happening?

The concentration of solutes inside the gummy bear is higher than the concentration of solutes in plain water. As a result, in our experiment, the water flowed into the gummy bear causing it to swell, and that’s why the gummy bear grew overnight.

The same is true for the gummy bear placed in the salt water solution. However, the difference in solute concentration wasn’t as great, so less water flowed into the gummy bear. In other words, it took less water to balance out the solute concentration inside and outside the gummy bear. Thus, the gummy bear in the salt water solution grew less than the bear in the plain water solution.

You can experiment with different solute concentrations to see how it affects the outcome. What happens when you add twice as much salt to the overnight water bath? Is there any amount of salt that can be added to keep the gummy bear the same size?

Exploring Chromatography

Chromatography is a technique used to separate out the components of a mixture. The technique utilizes two phases – a mobile phase and a stationary phase. There are several types of chromatography, but in this experiment, we will be looking at paper chromatography.

In paper chromatography, the stationary phase is filter paper. The mobile phase is the liquid solvent that moves over the filter paper. For this experiment, we will use marker ink to examine how chromatography works.

Exploring Chromatography Printable Instructions

• Three clear containers such as drinking glasses or mason jars
• Coffee filters
• Rubbing alcohol
• Vegetable oil
• Water-soluble marker, any color
• Sharpie marker, any color
• Mark one container with an “A,” a second container with a “W,” and a third container with an “O.” Fill the bottom of the “A” container with rubbing alcohol, the “W” container with water, and the “O” container with vegetable oil. Make sure the liquid in each container comes up no more than ½ an inch from the bottom.
• Take three coffee filters out and measure out 1 inch from the bottom. Mark this spot by drawing a line with the pencil. Make one dot on this line using the water-soluble marker. Do the same with the Sharpie marker.
• Place one coffee filter in each container so that the bottom of the coffee filter is submerged in the solvent but the solvent DOES NOT touch the dots of marker ink. The solvent will travel up the coffee filter and past the dots. Watch what happens to the dots as the solvent moves over them.

Like dissolves like, so substances will interact with solvents that are similar to it. Water-soluble marker ink is polar, so it will interact with polar mobile phases such as water and alcohol. When a non-polar solvent such as vegetable oil moves over it, it will not interact, and therefore will not move.

Sharpie marker ink is “permanent” in the sense that it can’t be washed off with water. It isn’t water-soluble. When the rubbing alcohol moves over it, however, we see that the Sharpie ink interacts with it. This is because Sharpie ink contains alcohols in it. Following the principle of “like dissolves like,” it interacts with the rubbing alcohol.

Using Tie-Dyed Milk to Observe Homogenization

Molecules in a solution tend to aggregate with other molecules that are similarly charged. Fat molecules, for instance, will cluster together with other fat molecules. Milk is made up of different types of molecules, including fat, water, and protein. In order to keep these molecules from completely separating to form layers, milk undergoes a process called homogenization.

Even after undergoing homogenization, however, fat molecules floating free in solution will come together when milk is left sitting undisturbed. To visualize this process, and what happens when those molecules are dispersed, we can use food coloring and dish soap.

Using Tie-Dyed Milk to Observe Homogenization Printable Instructions

• Full fat milk
• 1 small bowl
• Cotton swabs
• Pour some milk into a small bowl. You don’t need a lot of milk for this, just enough to fill the bottom of your bowl. Allow the milk to settle so the surface of the milk is still before moving on to Step 2.
• Add a drop of food coloring to the surface of the milk.
• Dip a cotton swab in dish soap and touch the swab to the surface of the milk, directly adjacent to the drop of food coloring. What happens to the food coloring?

Have you ever tried to mix oil and water? The fat molecules in oil, just like the ones in milk, are “hydrophobic,” meaning they don’t like to be near charged molecules such as water, and will do whatever they can to keep away from them. To achieve this, they clump together. Because the fat molecules are less dense than water, the fat globules float up and form a layer above the water. In our experiment, we added food coloring to this layer of fat globules.

Dish soap is a detergent. Detergent molecules have a hydrophobic end and a hydrophilic end. Because of this, they are able to form a bridge between the fat molecules and the water molecules, causing the fat globules to break up and disperse. What we’re seeing when we add the dish soap is this dispersal of the fat clusters, carrying the food coloring with it and resulting in a beautiful tie-dyed pattern. The result is more dramatic if you add several drops of food coloring and include a variety of colors.

Making water travel through capillary action

Paper towels are designed to pick up spills quickly, absorbing lots of liquid with only a few sheets. But what is it about paper towels that makes them so absorbent? The answer is, in part, capillary action.

In this experiment, we’ll observe how capillary action works to make paper towels efficient. Using nothing but paper towels and the principles governing capillary action, we’ll make water travel from one container and into another.

Making Water Travel through Capillary Action Printable Instructions

• 3 containers (cups or jars)
• Paper towels
• Food coloring
• Line up the three containers. Fill the two containers on either end about ¾ full of water. Add several drops of food coloring to each of the jars. Whatever color you use is up to you, but the effect works best if the two colors combine to make a third color. (For instance – yellow and blue make green.)
• Fold a paper towel in 4 lengthwise. Place one end of the folded paper towel in one of the containers filled with colored water (make sure the end is immersed in the water) and let the other end hang into the empty container. Repeat using a second paper towel and the remaining filled container.
• Let the containers sit for four hours. Check them after 1 hour, 2 hours, and 4 hours. What do you see?

Paper towels are highly porous. These pores function like tiny tubes, or capillaries, to draw up water. Two properties allow this to happen. The first is adhesion. Water molecules are attracted to the walls of the capillaries and “stick” to them. This is enhanced in our experiment because paper towels are made of cellulose molecules that are highly attractive to water. The second property is cohesion. The water molecules like to stick to each other. Together, these two properties allow the water to “travel” along the paper towel against gravity, moving out of one container and dropping into the other.

Efficient paper towels are more porous than less efficient brands, giving them a higher degree of absorbency. Taking this into account, how do you think the progress observed at each time point would differ if you used low quality paper towels instead of highly absorbent ones? How would you expect the color in the middle jar to change if you use a less absorbent paper towel to make the blue water travel, and a more absorbent paper towel to make the yellow water travel?

Observing Xylem in Celery

All plants need water to survive. In order to move water up from the soil and into their shoots and leaves, plants have developed a system of water transport. This system is called “xylem.” We can observe the movement of water through xylem transport by placing stalks of celery in colored water. The colored water moves through the stalk and up into the leaves, making the path of the water through this system visible.

Observing Xylem in Celery Printable Instructions

• A container such as a jar or vase
• Add 1 cup of water to the empty container. Add 2 drops of food coloring to the water (or however many it takes to achieve the color desired) and stir well to mix.
• Choose a celery stalk that has leaves attached to the top. Cut about 1 inch off the bottom of the stalk.
• Place the stalk upright in the container, making sure the bottom of the stalk is immersed in the water.
• Leave the celery out over night. Observe what happens. Take the celery out of the water and cut it open to get a better look at the path the water took.

Plants use a system called xylem to pull water up from the ground and transport it up through the shoot into their leaves. This process is passive, meaning it doesn’t require any energy in order to occur. That’s why the celery was able to pull water up overnight. The celery pulled colored water through its stalk via the xylem transport system. The colored water traveled all the way into the leaves, staining them.

The xylem transport system can be seen more clearly when the celery is cut. The colored water stains the xylem cells, making them visible.

One phenomenon that drives the flow of water through a plant is transpiration. Transpiration is the name given to the process by which water evaporates from the leaves of a plant. What do you think would happen if we repeated the experiment using a celery stalk whose leaves had been cut off? Try it and see!

How to Make it Rain Indoors

One of the properties of water is that it can exist in different phases. It can exist as a liquid, which is the form we’re most familiar with, and it can also exist as a solid (ice), or gas (water vapor). In this experiment, we’ll take water through two of its phases – liquid and gas. We’ll observe how temperature causes water to move from one phase into another. This will allow us to get a better idea of what happens to water in nature, and the role temperature plays in the water cycle.

How to Make it Rain Indoors Printable Instructions

• Large container such as a jar
• A ceramic plate
• Heat approximately eight cups of water to just steaming. This can be done on the stovetop or the microwave, but a stovetop will give you more control over the heating process.
• Pour the water into the jar until it is completely full and allow the jar to sit for five minutes. This will heat the jar for the experiment. After five minutes, discard the water.
• Add enough heated water to fill the jar up approximately halfway. Cover the jar opening with the plate, making sure no steam can escape. Let the jar sit for 3 minutes. Observe what happens to the water in the jar. Note any changes you see.
• After 3 minutes have passed, place enough ice on top of the dinner plate to cover its surface. Watch what happens to the jar.

The water cycle is responsible for producing rain. Liquid water evaporates, sending water vapor into the atmosphere. When the water vapor reaches the cooler air in the upper atmosphere, it condenses back into water droplets, forming clouds. If too much water condenses, or if the temperature becomes colder, the condensed water will fall back down to earth in the form of rain.

In this experiment, we replicated these conditions to produce “rain.” First, we let the heated water form water vapor inside the jar. The water vapor filled the space between the water surface and the plate. We then added ice to our plate, initiating a quick temperature drop. The lower temperature caused the water vapor to condense. This was visible as water droplets that beaded and ran down the sides of the jar. This is how rain happens. We made it rain inside our jar!

You might also like this lesson plan: Learning About Glowing Animals – Bioluminescence or Biofluorescence?

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• What Is Systems Biology

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What is Systems Biology

Systems biology is based on the understanding that the whole is greater than the sum of the parts.

Systems biology has been responsible for some of the most important developments in the science of human health and environmental sustainability. It is a holistic approach to deciphering the complexity of biological systems that starts from the understanding that the networks that form the whole of living organisms are more than the sum of their parts. It is collaborative , integrating many scientific disciplines – biology, computer science, engineering, bioinformatics, physics and others – to predict how these systems change over time and under varying conditions, and to develop solutions to the world’s most pressing health and environmental issues.

This ability to design predictive, multiscale models enables our scientists to discover new biomarkers for disease, stratify patients based on unique genetic profiles, and target drugs and other treatments. Systems biology, ultimately, creates the potential for entirely new kinds of exploration, and drives constant innovation in biology-based technology and computation.

Because systems biology requires constant attention to a very complex, very human social experiment, ISB fosters the kind of financial, social and psychological environment in which the world’s best scientists, technologists, engineers and mathematicians can collaborate and do their best work.

Dr. Nitin Baliga, ISB SVP and Director, explains what is systems biology. Watch on YouTube .

SYSTEMS BIOLOGY 101:

Isb’s innovation engine.

A fundamental tenet of systems biology is that solving challenging biological problems always requires the development of new technologies in order to explore new dimensions of data space. New data types require novel analytical tools. This virtuous cycle of biology driving technology driving computation can exist only in a cross-disciplinary environment where biologists, chemists, computer scientists, engineers, mathematicians, physicists, physicians and others can come together in teams to tackle grand challenges. This is ISB. And this describes what we call the “innovation engine” (depicted below) that drives our ability to develop intellectual property, which we share through open-access platforms or by spinning out companies.

Cross-disciplinary Teams

In describing systems biology and the distinguishing characteristics of ISB’s approach, we always emphasize how our lab groups are intentionally and necessarily cross-disciplinary. One of our labs, for example, includes molecular biologists, microbiologists, geneticists, engineers, oceanographers, and even an astrophysicist. The complexity of biology in this age of “big data” requires diverse teams in order to tackle such vast amounts of data and to make sense of it all. New technologies that crunch data faster and more efficiently also permit researchers to re-analyze existing datasets, a process which often reveals undiscovered information. Complementary skills empower any of our groups of researchers to better understand biological or environmental challenges from different perspectives and to arrive at shareable insights more quickly. Our interdisciplinary teams have contributed notable advances to everything from ocean acidification to neurodegenerative diseases and tuberculosis to multiple cancers.

Network of Networks

Multiscale Modeling

Whether we explicitly recognize it or not, multiscale phenomena are part of our daily lives. We organize our time in days, months and years, as a result of the multiscale dynamics of the solar system. Our society is organized in a hierarchical structure, from towns to states, countries and continents. The human body is a complex machine, with many little parts that work by themselves or with other parts to perform specific functions. Organelles inside each cell in our bodies interact with one another to maintain a healthy functioning cell that moves, differentiates and dies. These subcellular organelles and their processes govern each cell’s signalling mechanism to interact with its neighboring cells, and form multi-cellular systems called tissues (e.g. epithelial tissue, muscular tissue). Two or more types of tissues work together to form an organ that performs a specific task (e.g. mouth, stomach, liver). Two or more organs work together to form organ systems, such as the digestive system and the nervous system, that perform more complex tasks. All these organ systems interact with each other to enable a healthy functioning organism. Traditional approaches to modeling real world systems focus on a single scale that imparts a limited understanding of the system. The pace at which biotechnology has grown has enabled us to collect large volumes of data capturing behavior at multiple scales of a biological system. Genetic as well as environmental alterations to the DNA, expression levels of RNAs, expression of genes and synthesis of proteins – all this is measurable now within a matter of days at a rapidly declining cost. So, it is really up to scientists and data analysts to make use of this variety of data types and build integrative models that enable a comprehensive understanding of the system under study. Multiscale models do just that. By integrating models at different scales and allowing flow of information between them, multiscale models describe a system in its entirety, and as such, are intrinsic to the principles of systems biology.

Single Cell Analysis

It is well known that there is no “average” patient. Therefore, in clinical trials encompassing large groups of patients, one needs to consider the characteristics of each patient, including each person’s individual genetic propensity to respond to a drug in a particular way. The statistical analysis of population averages suppresses valuable individual-specific information. The consideration of population heterogeneity due to inevitable patient-to-patient variability is called “stratification” and is at the heart of personalized medicine. Such stratification will allow a proper impedance match against appropriate and effective drugs. Each cell in a cell population of apparently identical cells is a distinct individual. There is no “average” cell even within a population of cells of the very same cell type. Just as one can look at individual patients in a population and identify subtypes of diseases, one can identify “quantized” or “discrete” cell-subtypes in a cell population. The quantized subtypes perform different functions and form a network – much like a social network in human populations. So understanding how an organ works will require understanding the coordinated integration of the functioning of all the quantized cell types. Because of such cellular heterogeneity, even the most potent target-selective drug will kill only a fraction of tumor cells – explaining the inexorable drug resistance in malignant tumors. This new insight on cellular heterogeneity calls for the measurement of all molecular profiles in individual cells. Tissues must be seen not as an amorphous mass but analyzed as dynamical populations of cells and at single-cell resolution.

Understanding Proteomics

If DNA is the blueprint for life, then proteins are the bricks. The genes in DNA are translated into proteins, strings of amino acids that fold into three-dimensional structures. The type and order of the amino acids in a protein will change its shape and determine its special function. Proteins are the molecules that make life happen: they are the powerplants that turn food into energy, the machines that make cells move, and even the computers that read DNA and make more proteins. The information to build every protein in an organism is contained in the DNA, but not every protein is produced at once or in the same amount. Think of a cell in your liver and a cell in your retina – both cells contain identical DNA, but very different subsets of proteins are being produced in order to give each cell its special function. Proteomics is the discipline of identifying and quantifying the proteins present in an organism. At ISB, we use state-of-the-art scientific instruments and cutting edge computational techniques to detect thousands of proteins at once, giving us a systems-level view of the molecular machinery of life.

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Science Experiments for Learning about the Human Body

March 17, 2021 By Emma Vanstone 29 Comments

This collection of science experiments for learning about the human body is perfect for encouraging kids to learn about their bodies! I’ve split the ideas into three age groups: preschool, primary age ( 5-11 ) and secondary ( 12+) but these are very loose recommendations. Hopefully you’ll find something that sounds fun to try!

I’ve also got lots of fun STEM challenges and science printable instructions you might like too!

Human Body Science Ideas for Preschoolers

If you have a big piece of paper or cardboard, get the children to draw around themselves , they can then measure arms and legs, label body parts and even draw in organs.

Learn about bones with this fun doctor role play activity using modroc as a cast on dolls.

Listen to your heart beat by making your own Stethoscope .

Make a model of a human brain using playdough.

Learn about keeping your hands with this hand hygiene activity .

Discover the relationship between arm span and height .

Human Body Science for Primary School

Did you know that taste is linked to smell ?

Use eggs to learn about tooth decay . Soak them in vinegar, coffee and coke to see what happens to the shell.

Investigate heart rate . This can be done by recording your pulse rate at rest then doing some exercise and measuring it again.

Did you know you can test your reaction time using just a ruler?

Have some fun finding out how strong your bones are.

These printable organs from Adventure in a Box are just brilliant!

See a close up of your fingerprint using a balloon!

Find out why you get dizzy with this great guest post from Red Ted Art

Learn about your lungs with this fake lung experiment .

Human Body Science for Secondary School

Make a model of a pumping heart using a jar.

Make a model of an animal cell . An edible version is especially fun!

Another easy edible experiment is my candy DNA model !

Follow the journey of food through the digestive system with this easy activity using tights!

These edible neurons from My Mundane and Miraculous Life are just brilliant too!

Find out how you can ‘see sound’ with these easy sound activities.

Try some of these brilliant blood experiments for learning about the heart, circulatory system and red and white blood cells.

Link to a scientist

Marie Curie ‘s research into radiation led to the discovery of radium which is now used to treat some cancers.

Marie M. Daly did groundbreaking research in the relationship between high blood pressure, cholesterol and clogged arteries.

Can you think of any more human body science experiments for us?

You might also like my NEW book! Gross Science is now available to buy and is full of icky, slimy and gross science experiments for kids including lots about the human body!

Last Updated on October 2, 2022 by Emma Vanstone

Safety Notice

Science Sparks ( Wild Sparks Enterprises Ltd ) are not liable for the actions of activity of any person who uses the information in this resource or in any of the suggested further resources. Science Sparks assume no liability with regard to injuries or damage to property that may occur as a result of using the information and carrying out the practical activities contained in this resource or in any of the suggested further resources.

These activities are designed to be carried out by children working with a parent, guardian or other appropriate adult. The adult involved is fully responsible for ensuring that the activities are carried out safely.

Reader Interactions

November 27, 2013 at 10:34 am

I would gice this to my Son

November 27, 2013 at 2:42 pm

my daughter

November 27, 2013 at 7:09 pm

I would give it to my son!

November 27, 2013 at 8:06 pm

my friends son

November 27, 2013 at 8:56 pm

I would give this to my daughter.

November 27, 2013 at 9:06 pm

November 27, 2013 at 9:29 pm

my granddaughter

November 28, 2013 at 6:13 pm

my grandson

December 01, 2013 at 4:42 pm

Id love to give it to my grand daughter

December 01, 2013 at 8:29 pm

my boys would share it! (hopefully)

December 04, 2013 at 8:09 am

December 04, 2013 at 1:11 pm

December 04, 2013 at 8:19 pm

my niece Yasmin 🙂

December 04, 2013 at 10:40 pm

I would give it to Lilly she has just started school and it will really help her to learn to read etc.

December 05, 2013 at 1:14 pm

My little boy

December 05, 2013 at 2:00 pm

December 05, 2013 at 7:53 pm

My dd would love this 🙂

December 05, 2013 at 7:54 pm

My nephew 🙂

December 05, 2013 at 8:53 pm

I would give this to my little one, he would love it.

December 05, 2013 at 10:23 pm

My son and daughter. X

December 05, 2013 at 10:25 pm

My Little girl she would love it x

December 05, 2013 at 11:07 pm

December 06, 2013 at 12:17 am

my brothers son- hes 5 x

December 06, 2013 at 10:02 am

I would give it to my step-granddaughter

December 06, 2013 at 4:11 pm

December 06, 2013 at 4:28 pm

would have to go between my two younger boys, Isaak and Archie!! With the hope that they didnt fight to much, lol least it built for children and quite robust!

December 06, 2013 at 4:46 pm

I would give it to my youngest 3 girls to share & have fun with!

December 06, 2013 at 8:01 pm

My son would love this

December 06, 2013 at 9:29 pm

My daughter x

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