Foundation model for comprehensive transcriptional regulation analysis  

作　　者：Zhaowei Yu Yong Zhang 

机构地区：[1]State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center,Institute for Regenerative Medicine,Department of Neurosurgery,Shanghai East Hospital,Shanghai Key Laboratory of Signaling and Disease Research,Frontier Science Center for Stem Cell Research,School of Life Sciences and Technology,Tongji University,China

出　　处：《National Science Review》2024年第11期7-10,共4页国家科学评论（英文版）

基　　金：supported by the National Nat ural Science Foundation of China(32325012,32030022,32488101,32400522);the National Key Research and Development Program of China(2021YFA1302500);the Science and Technology Commission of Shanghai Municipality(23JS1401200);the Postdoctoral Innovation Talents Support Program(BX20230265);the China Postdoctoral Science Foundation(2022M722423).

摘　　要：Transcription regulation is a complex biological process that researchers have long sought to decode.With recent ad-vancements in artificial intelligence(AI),foundation models,particularly those based on transformer architectures,are emerging as promising tools to address this challenge.These models are first pre-trained to capture intricate patterns within input genomic data,such as DNA sequences and epigenomic or transcrip-tion factor binding information,mainly through self-supervised learning.This foundational training allows them to then be fine-tuned for specific biological contexts,predicting and interpreting how genomic features influence transcription regulation.This perspective reviews the development and applications of founda-tion models in transcription regulation,with a focus on their training methods,architectures。

关 键 词：FOUNDATION INTERPRETING COMPREHENSIVE 

分 类 号：TN911.7[电子电信—通信与信息系统] R318[电子电信—信息与通信工程]