Author details

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Full Name

Renqiang Min

Affiliation

ORCID

Career Start Year

2009

Papers

17

H Index

10

Expertise

CM4AI Collaborator

PMID	Paper Title	Journal Title	Published Year
36571499	Attentive Variational Information Bottleneck for TCR-peptide interaction prediction.		2023
36341448	On TCR binding predictors failing to generalize to unseen peptides.	Frontiers in Immunology	2022
35187404	A Deep Generative Model for Molecule Optimization via One Fragment Modification.	Nat Mach Intell	2021
34079815	Ranking-Based Convolutional Neural Network Models for Peptide-MHC Class I Binding Prediction.	Frontiers in Molecular Biosciences	2021
34252960	DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays.	Bioinformatics	2021
28668660	Accelerating deep neural network training with inconsistent stochastic gradient descent.	Neural Networks	2017
26206306	High-order neural networks and kernel methods for peptide-MHC binding prediction.	Bioinformatics	2015
24297536	An integrated approach to blood-based cancer diagnosis and biomarker discovery.	Pac Symp Biocomput	2014
22009677	PhenoM: a database of morphological phenotypes caused by mutation of essential genes in Saccharomyces cerevisiae.	Nucleic Acids Res	2012
22955978	Understanding transcriptional regulation by integrative analysis of transcription factor binding data.	Genome Res	2012
22955619	Architecture of the human regulatory network derived from ENCODE data.	Nature	2012
22039215	TIP: a probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles.	Bioinformatics	2011
21441928	Systematic exploration of essential yeast gene function with temperature-sensitive mutants.	Nat Biotechnol	2011
20489180	Exploiting the determinants of stochastic gene expression in Saccharomyces cerevisiae for genome-wide prediction of expression noise.	Proc Natl Acad Sci U S A	2010
20865155	Gene expression variability within and between human populations and implications toward disease susceptibility.	PLoS Comput Biol	2010
20014473	A probabilistic framework to improve microrna target prediction by incorporating proteomics data.	J Bioinform Comput Biol	2009
19254184	Learned random-walk kernels and empirical-map kernels for protein sequence classification.	J Comput Biol	2009

1 - 17 of 17

University of Toronto

Co-authored papers 6

Yale University

Co-authored papers 5

Ke Jin

West China Hospital, Sichuan University

Co-authored papers 3

Franco J Vizeacoumar

College of Medicine, University of Saskatchewan

Co-authored papers 3

Baylor College of Medicine

Co-authored papers 3

University of Toronto

Co-authored papers 2

Co-authored papers 2

Stanford University

Co-authored papers 2

Alessandro Datti

University of Perugia

Co-authored papers 2

University of Toronto

Co-authored papers 2

Co-authored papers 2

Frederick S Vizeacoumar

College of Medicine, University of Saskatchewan

Co-authored papers 2

Brenda J Andrews

University of Toronto

Co-authored papers 2

Roger P Alexander

Co-authored papers 2

Co-authored papers 2

Co-authored papers 2

University of Toronto, College Street

Co-authored papers 1

Dorrelyn Patacsil

Co-authored papers 1

Stanford University

Co-authored papers 1

Manoj Hariharan

Co-authored papers 1

National Cancer Institute

Co-authored papers 1

Anne-Claude Gingras

Lunenfeld-Tanenbaum Research Institute

Co-authored papers 1

RIKEN Center for Integrative Medical Sciences

Co-authored papers 1

Andrew D Stephens

Co-authored papers 1

The University of Texas Health Science Center at Houston

Co-authored papers 1

Co-authored papers 1

Ghia Euskirchen

Co-authored papers 1

Serafim Batzoglou

Co-authored papers 1

Michael Costanzo

Co-authored papers 1

Co-authored papers 1

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