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Session Introduction: Biological molecular function: methods and benchmarks for finding function in biological dark
Jason E McDermott1, Yana Bromberg2, Hannah Carter3
1Computational Biology Group, Pacific Northwest National Laboratory Richland, Washington 99352, USA2Department of Molecular Microbiology and Immunology, Oregon Health & Science University Portland, Oregon 97239, USA, Jason.McDemott@pnnl.gov.
Computational biology faces challenges in determining molecular function. New AI/ML methods, including geometric protein modeling and reinforcement learning for sequence design, offer innovative solutions for biological "dark matter".
Area of Science:
- Computational Biology
- Artificial Intelligence in Biology
- Machine Learning for Genomics
Background:
- Accurate determination of biological molecular function is a significant challenge in computational biology.
- Vast areas of biological 'dark matter' exist in microbiomes, viruses, and unexplored sequence space.
- Traditional sequence similarity-based functional annotation methods have limitations.
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