Author

Martin Renqiang Min

ORCID 0000-0002-8563-6133Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Approach:graph neural network· 1 Assay:imaging· 1

Frequent Co-Authors

Jonathan WarrelliD· 2 shared Mark GersteiniD· 2 shared Andrea Meiser· 1 shared Anja MöschiD· 1 shared Ayako Demachi‐OkamuraiD· 1 shared Daiki MoriiD· 1 shared Daisuke MuraokaiD· 1 shared Donghoon LeeiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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2 shared papersImmunology

Jonathan WarrellORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Generative AI Guided Design of High-Affinity T cell Receptors

Martin Renqiang Min, Tianxiao Li, Kazuhide Onoguchi, Daiki Mori, Ayako Demachi‐Okamura, Jonathan Warrell, Pierre Machart, Anja Mösch, Andrea Meiser, Ivy Grace Pait, Daisuke Muraoka, Hirokazu Matsushita, Giulia Paiardi, Matheus Ferraz, Kaïdre Bendjama

This paper introduces TCRPPO2, an AI-driven framework for optimizing TCR affinity, showing improved activity in engineered TCRs against tumor antigens.

bioRxiv · Feb 18, 2026 · PreprintImmunology

Predicting Spatially Resolved Gene Expression via Tissue Morphology using Adaptive Spatial GNNs

Tianci Song, Eric Cosatto, Gaoyuan Wang, Rui Kuang, Mark Gerstein, Martin Renqiang Min, Jonathan Warrell

This paper predicts spatial gene expression from histological images using adaptive spatial GNNs, improving performance on breast cancer data.

Bioinformatics · Jun 19, 2024Peer-reviewedBioinformatics

DECODE: A Deep-learning Framework for Condensing Enhancers and Refining Boundaries with Large-scale Functional Assays

Zhanlin Chen, Jing Zhang, Jason J. Liu, Yi Qi Dai, Donghoon Lee, Martin Renqiang Min, Min Xu, Mark Gerstein

DECODE improves enhancer prediction and boundary detection using deep learning and functional assays, achieving higher accuracy and reduced annotation size.

Bioinformatics · Apr 26, 2021Peer-reviewedBioinformatics