Author

Connor Chain

Princeton UniversityORCID 0000-0002-0606-3710Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Barbara Elizabeth EngelhardtiD· 1 shared Chi-Yun WuiD· 1 shared Han Kim· 1 shared I. IraniiD· 1 shared Joseph P. SheehaniD· 1 shared Soodabeh GhaffariiD· 1 shared Syrine BelakariaiD· 1 shared Zemer GitaiiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperBioinformatics

Barbara Elizabeth EngelhardtORCID

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintJun 11, 2026

Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets

Connor Chain, Soodabeh Ghaffari, Syrine Belakaria…·Zemer Gitai

This paper develops a machine learning pipeline to discover novel antibacterial compounds with distinct mechanisms of action, finding that training data bias limits the discovery of mechanistically novel antibiotics.

DOI 10.64898/2026.06.08.730938

bacteria (other)machine learning (classical)

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