2024-02-21 FEB
DNA language models; gemini and/or openAI APIs?
Journal Club
Proc Natl Acad Sci U S A. 2023 Oct 31; 120(44): e2311219120. PMID: 37883436 [pdf]
DNA language models are powerful predictors of genome-wide variant effects
Gonzalo Benegas, a Sanjit Singh Batra, b and Yun S. Song b , c , d , 1
aGraduate Group in Computational Biology, University of California, Berkeley, CA 94720
bComputer Science Division, University of California, Berkeley, CA 94720
cDepartment of Statistics, University of California, Berkeley, CA 94720
dCenter for Computational Biology, University of California, Berkeley, CA 94720
Summary (Gemini)
Building language models for DNA is an emerging field with promising potential. These models, similar to how they work with natural language, can learn the patterns and relationships within DNA sequences and use this knowledge to perform various tasks, such as:
Building language models for DNA is an emerging field with promising potential. These models, similar to how they work with natural language, can learn the patterns and relationships within DNA sequences and use this knowledge to perform various tasks, such as:
Predicting the function and effects of genetic variations
Identifying regulatory elements in DNA
Generating novel DNA sequences with desired properties
Several challenges exist in building DNA language models, including the vast amount of data required for training and the unique characteristics of DNA sequences compared to natural language. However, ongoing research is addressing these challenges, and the development of DNA language models is a rapidly evolving field.
Notes
Jeya's conversation with Gemini: https://gemini.google.com/share/55079d730ee6
Hugging faces GPN models
https://github.com/songlab-cal/gpn/tree/main/analysis/human
https://github.com/songlab-cal/gpn/tree/main/analysis/arabidopsis
Hachaton
Project updates
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Gemini and/or openAI APIs?
https://platform.openai.com/docs/quickstart?context=node <-- serverless agents
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epiVerse governance - that of an agent-based operating system.
Serverless Web Agents, mediated by token.
Managing token is the critical question - https://ai.google.dev/pricing
Either way generative AI OS is proposed as web agents
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