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The 2020 schedule is still incomplete Program Highlights »
Learning Meaningful Representations of Life (LMRL.org)
Elizabeth Wood · Debora Marks · Thouis Jones · Adji Bousso Dieng · Alan Aspuru-Guzik · Anshul Kundaje · Barbara Engelhardt · Chang Liu · Edward Boyden · Kresten Lindorff-Larsen · Mor Nitzan · Smita Krishnaswamy · Wouter Boomsma · Yixin Wang · David Van Valen · Orr Ashenberg

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There now exists a unique opportunity to unlock the secrets of biological systems at all scales. Mapping structural molecular detail to organismal phenotype and function; predicting emergent effects of human genetic variation; designing novel interventions including prevention, diagnostics, therapeutics, and the development of new synthetic biotechnologies for causal investigations are just some of the challenges that hinge on appropriate formal structures to make them accessible to the broadest possible community of computer scientists, statisticians, and their tools.

This workshop is designed to bring together trainees and experts in machine learning with those in the very forefront of biological research today for this purpose. Our full-day workshop will advance the joint project of the CS and biology communities with the goal of "Learning Meaningful Representations of Life" (LMRL), emphasizing interpretable representation learning of structure and principle. As last year, the workshop will be oriented around five layers of biological abstraction: genome, molecule, cell, synthetic system, and phenotype. This year will have a special talk in each layer dedicated to COVID responses, successful or not, at that level of biological scale from some of the world's foremost experts and first-line responders.