Exploring The Possibilities Of AI & Machine Learning In The Field Of Biology

A.B. Learned Professor of Living State Physics, Dr. Robert Riek, is the University’s Distinguished Professor of Biomedical Engineering, Molecular Physiology and Biophysics, and Physics.

The University of Tennessee Health Science Center’s College of Graduate Health Sciences has appointed Dr. Michael McCallister as the Founding Director of the Vanderbilt Institute for Integrative Biosystems Research and Education and an Adjunct Professor of its Department of Graduate Education.

Biology’s legendary complexity has traditionally required scientists to zoom in on a single focus for investigation – for instance, an individual protein or cell. This method of isolated inquiry has been the standard research approach.

Systems biology, taking a broader approach to incorporating biological levels of complexity, which can extend over various spatial and temporal scales, is confronted with the challenge of discerning the proper set of biological variables and connections that may be managed via current research practices utilizing innovative multi-omic computation models.

Due to the complexity of systems biology models in increasing both breadth and depth, validating and expanding them comes with several challenges: generating numerous testable hypotheses, designing fitting experiments, interpreting data accurately to prove each hypothesis, and repeating steps as necessary.

As evidenced by a geometric or exponential increase, the complexity of both models and experiments might lead to a proportional decrease in the speed of scientific progress unless some means can be found to boost scientific exploration radically.

AI, ML, robot scientists, and self-driving laboratories are set to make huge strides in terms of individuals addressing complex biological issues. The various technologies could revolutionize the way that it is done.

The possibilities of AI and machine learning in biology are vast, and integrating these technologies into biological research can accelerate discoveries and improve human health. As technology evolves, seeing how it can further enhance our understanding of the biological world will be exciting.

Source: Events Calendar

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