Deep learning decodes the principles of differential gene expression.

Nature Machine Intelligence
Shinya TasakiYanling Wang

Abstract

Identifying the molecular mechanisms that control differential gene expression (DE) is a major goal of basic and disease biology. We develop a systems biology model to predict DE, and mine the biological basis of the factors that influence predicted gene expression, in order to understand how it may be generated. This model, called DEcode, utilizes deep learning to predict DE based on genome-wide binding sites on RNAs and promoters. Ranking predictive factors from the DEcode indicates that clinically relevant expression changes between thousands of individuals can be predicted mainly through the joint action of post-transcriptional RNA-binding factors. We also show the broad potential applications of DEcode to generate biological insights, by predicting DE between tissues, differential transcript-usage, and drivers of aging throughout the human lifespan, of gene coexpression relationships on a genome-wide scale, and of frequently DE genes across diverse conditions. Researchers can freely utilize DEcode to identify influential molecular mechanisms for any human expression data - www.differentialexpression.org.

Associated Software

References

Dec 11, 1999·Nucleic Acids Research·M Kanehisa, S Goto
May 30, 2003·Hepatology : Official Journal of the American Association for the Study of Liver Diseases·Alistair J WattStephen A Duncan
May 16, 2007·Proceedings of the National Academy of Sciences of the United States of America·Kwang-Il GohAlbert-László Barabási
Mar 18, 2008·FEBS Letters·Tina GlisovicGideon Dreyfuss
Mar 19, 2011·BMC Bioinformatics·Xavier RobinMarkus Müller
Feb 13, 2013·Nature Reviews. Genetics·Zachary D Smith, Alexander Meissner
Mar 19, 2013·Cell·Tong Ihn Lee, Richard A Young
May 6, 2014·Trends in Endocrinology and Metabolism : TEM·Martina I LefterovaSusanne Mandrup
Nov 5, 2014·Nature Reviews. Genetics·Stefanie GerstbergerThomas Tuschl
Jan 22, 2015·Nucleic Acids Research·Matthew E RitchieGordon K Smyth
Mar 10, 2015·International Journal of Hematology·Maria Rosaria ImperatoConstanze Bonifer
May 8, 2015·Nature Reviews. Genetics·Maxwell W Libbrecht, William Stafford Noble
May 9, 2015·Science·Marta MeléRoderic Guigó
Jul 28, 2015·Nature Biotechnology·Babak AlipanahiBrendan J Frey
Aug 11, 2015·Nature Genetics·Eric R GamazonHae Kyung Im
Aug 13, 2015·ELife·Vikram AgarwalDavid P Bartel
Jan 16, 2016·Cell Systems·Arthur LiberzonPablo Tamayo
May 5, 2016·Nucleic Acids Research·Maxim V KuleshovAvi Ma'ayan
Aug 19, 2016·Nature·Monkol LekUNKNOWN Exome Aggregation Consortium
Dec 8, 2016·Nucleic Acids Research·Ivan YevshinFedor Kolpakov
Jun 18, 2017·Cell·Ian A RoundtreeChuan He
Jul 29, 2017·Cell·Aviad TsherniakWilliam C Hahn
Nov 2, 2017·Nucleic Acids Research·Cynthia L SmithUNKNOWN Mouse Genome Database Group
Nov 6, 2017·Cellular and Molecular Life Sciences : CMLS·Eduardo Soares, Huiqing Zhou
Feb 10, 2018·Cell·Samuel A LambertMatthew T Weirauch
May 26, 2018·Nucleic Acids Research·Daniel J B ClarkeAvi Ma'ayan
Sep 22, 2018·Nucleic Acids Research·Yumin ZhuPengyuan Wang
Jan 22, 2019·Cell·Kishore JaganathanKyle Kai-How Farh
Mar 9, 2019·Proceedings of the National Academy of Sciences of the United States of America·Megan CrowJesse Gillis
May 16, 2019·Nature Reviews. Genetics·Stefan Schoenfelder, Peter Fraser

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Methods Mentioned

BETA
feature extraction

Software Mentioned

Gene Discovery Informatics Toolkit
hyperopt
TargetScan
DEcode
R ggplot2
DeepExplainer
DeepLIFT
XGBoost
Nvidia
DepMap

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