12 May 2022

Machine learning is key to answer important biological questions

Machine learning

With a new hologenomic approach generating big data, we are now able to reassess some of life's biggest questions looking at the host and its millions of microbes as one. Machine learning and computer experts are, however, key to analysing and detangling these thousands of signals in order to answer important biological questions anew.

“Are you interested in how biology, maths and computer science can work together to solve the world's biggest problems?” This is what Project Manager Shelley Edmunds set out to explain in a new video aimed at students. The FindingPheno project bridges these disciplines, using machine learning to analyse biological data sets called omics to understand the complex biological systems that are going on inside all living organisms at a molecular level. The FindingPheno project hopes to inspire the next generation of computer experts to use their abilities to help solve some of the world’s most pressing challenges: climate change, biodiversity loss and health.

“Computer science isn’t just about machines and technology these days, it can be applied to all kinds of interesting problems. And biology isn’t just about living things, it also includes working more and more with computer analysis and data. Once the students understand some basic concepts within computer science such as bioinformatics, omics and machine learning, they can work together to come up with new and meaningful findings and answer important biological questions. So instead of studying only one type of science, the students should consider studying a bit of both biology and computer science”, answers Shelley, when asked about the main message that she wants the students to take away from the video.

Computer experts in demand

“One of the challenges that we face in research today is a lack of computer scientists trained to work with big data, especially ones who also understand biology. This problem will only get bigger as data size and complexity continues to grow thanks to new high throughput technologies such as next-generation sequencing, the rapid increase in computational power, and ongoing accumulation of open access datasets. So we need more students to choose this path to fill the demand”, Shelley concludes. 

In the FindingPheno project, computer experts get to combine machine learning with biology, which makes all the difference in answering life’s big questions, as can be seen in the explainer video below. If you want to learn more about how the FindingPheno project uses machine learning in biology you can visit this webpage.

In a new explainer video the FindingPheno project explains how machine learning and computer science is used to measure thousands of biological signals called omics data and how a computational framework can be used to untangle this web of signals in order to answer important biological questions.