Bin Chen, PhD

Associate Professor
Pediatrics & Human Development, Pharmacology & Toxicology

Bio

Bin was recruited to MSU through the Global Impact Initiative. Prior to this position, Bin was a faculty member (instructor, assistant professor) at UCSF for three years. Bin trained as a chemist in college, worked as a software engineer before graduate school, trained as a chem/bioinformatician in graduate school, worked as a computational scientist at Novartis, Pfizer and Merck. He received his PhD in informatics at Indiana University, Bloomington and pursued his postdoctoral training in Dr. Atul Butte's lab at Stanford University. Bin co-founded DahShu, a non-profit organization to promote research and education in data sciences. As a PI, he has received >$4.5 million research funding. He has also contributed to a number of big grants (e.g., P01 and U24) as a co-investigator.

Colleges

• College of Human Medicine

Programs

• Integrated Pharmacological Sciences Training Program
• Doctor of Philosophy in Pharmacology and Toxicology

Works

• STANCE: a unified statistical model to detect cell-type-specific spatially variable genes in spatial transcriptomics. (2024-09-24)
• Imputing abundance of over 2,500 surface proteins from single-cell transcriptomes with context-agnostic zero-shot deep ensembles. Cell Systems (2024)
• Imputing abundance of over 2500 surface proteins from single-cell transcriptomes with context-agnostic zero-shot deep ensembles. (2024-07-31)
• TransCell: In Silico Characterization of Genomic Landscape and Cellular Responses by Deep Transfer Learning. Genomics, Proteomics & Bioinformatics (2024-07-03)
• Computational discovery of co-expressed antigens as dual targeting candidates for cancer therapy through bulk, single-cell, and spatial transcriptomics. Bioinformatics Advances (2024-01-05)
• OCTAD: an open workspace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features. Nature Protocols (2021-02-23)
• Harnessing big ‘omics’ data and AI for drug discovery in hepatocellular carcinoma. Nature Reviews Gastroenterology & Hepatology (2020-04-15)
• Publisher Correction: Harnessing big ‘omics’ data and AI for drug discovery in hepatocellular carcinoma. Nature Reviews Gastroenterology & Hepatology (2020-03-11)
• Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types. Nature Communications (2019-08-08)
• Evaluating cell lines as models for metastatic breast cancer through integrative analysis of genomic data. Nature Communications (2019-05-15)

Employment

• Assistant Professor, Michigan State University (2018-04-01)
• Instructor/Assistant Professor, University of California, San Francisco (2015-04-01—2018-03-31)