Unlocking gene regulation with sequence-to-function models

doi:10.1038/s41592-024-02331-5

2024-08-09

PRE

Alexander Sasse

Maria Chikina *

Sara Mostafavi *

DOI：10.1038/s41592-024-02331-5

原文链接

原文求助

摘要

En 中文

By exploiting recent advances in modern artificial intelligence and large-scale functional genomic datasets, sequence-to-function models learn the relationship between genomic DNA and its multilayer gene regulatory functions. These models are poised to uncover mechanistic relationships across layers of cellular biology, which will transform our understanding of cis gene regulation and open new avenues for discovering disease mechanisms.

Keyword:

GENOME

期刊

Nature Methods

IF:

32.1

论文数:

7.2K

被引数:

12.7W

机构

University of Washington

学者数:

8.0W

论文数: 7.0W

被引数: 12.5W

引用论文

Personal transcriptome variation is poorly explained by current genomic deep learning models 目前的基因组深度学习模型很难解释个人转录组变异

NATURE GENETICS

IF31.8

2023-11-30

OAAI

Huang, Connie; Shuai, Richard W.; Baokar, Parth; Chung, Ryan; Rastogi, Ruchir; Kathail, Pooja; Ioannidis, Nilah M.

An Energy-Efficient Path Availability Routing Algorithm For Mobile Ad Hoc Sensor Networks

2006 IEEE International Conference on Communications

IF0

2006-01-01

PREAI

Ming Yu; Aniket Malvankar; Simon Foo

Sequence-based modeling of three-dimensional genome architecture from kilobase to chromosome scale

NATURE GENETICS

IF31.8

2022-05-12

OAAI

Zhou, Jian

Designing for the deluge

Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing

IF0

2014-02-15

PREAI

Camille Cobb; Ted McCarthy; Annuska Perkins; Ankitha Bharadwaj; Jared Comis; Brian Do; Kate Starbird

Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings 用于从DNA序列预测个人基因表达的深度神经网络的基准测试突出了缺点

NATURE GENETICS

IF31.8

2023-11-30

OAAI

Sasse, Alexander; Ng, Bernard; Spiro, Anna E.; Tasaki, Shinya; Bennett, David A.; Gaiteri, Christopher; De Jager, Philip L.; Chikina, Maria; Mostafavi, Sara

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk 基于深度学习序列的变异对表达和疾病风险影响的从头算预测

NATURE GENETICS

IF31.8

2018-07-16

346

OAAI

Zhou, Jian; Theesfeld, Chandra L.; Yao, Kevin; Chen, Kathleen M.; Wong, Aaron K.; Troyanskaya, Olga G.

Ranking Sentences for Extractive Summarization with Reinforcement Learning

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

IF0

2018-01-01

OAAI