Shamim A Mollah, PhD

Assistant Professor
Department of Genetics
Institute for Informatics  [CV]
4444 Forest Park Ave
Room 6307, Campus Box 8102 [Map]
Phone: 314-273-8438

About me

Ph.D. Bioinformatics and Systems Biology, UC San Diego
M.A. Biomedical Informatics, Columbia University
B.S. Computer Science, Indiana University
B.A. Mathematics, Indiana University

Shamim Mollah is an Assistant Professor of Genetics and Institute for Informatics at Washington University School of Medicine in St. Louis. Shamim received her Ph.D. in Bioinformatics and Systems Biology from University of California San Diego. Her research was focused on applying network analysis-based models on multi-omics data using dynamic modeling, graph-theory, and machine-learning techniques to characterize drug responses in cancer cells.  She studied the responses of individual/combination drug/s on tumor cells and their effects on key proteins involved in cell signaling pathways. Shamim received her Master’s degree in Biomedical Informatics from Columbia University, where her research was focused on computational linguistics studying morphology of medical language using natural language processing. She received her undergraduate degrees in Computer Science (B.S.) and Mathematics (B.A.) from Indiana University where her research was focused on reinforcement learning (AI) and dynamic modeling (operation research). Previously, Shamim served as the bioinformatics scientist at the Rockefeller University, where she managed bioinformatics data analysis core for the Center of Clinical and Translational Science (CCTS). During her tenure at the Rockefeller University, her proposed bioinformatics research proposals led to the 2008 Obama challenge grant award and its renewal in 2011.

Min, Shi, PhD 

Postdoctoral Research Associate, Email:

Min Shi earned his Ph.D. in Computer Science from Florida Atlantic University, USA, where his research interests include machine learning, deep learning and network analysis. In the Mollah lab, his research focus is to develop computational models and machine learning methods to interpret tumor microenvironment through integration of large scale multi-omics data. He has also been working on a project which aims to study the respiratory immune characteristics associated with Covid-19 severity. From this project, he has gained experiences in addressing and analysing the high-dimensional single-cell RNA sequencing data.

Rintsen, Sherpa

Bioinformatics Research Assistant, Email:

Rintsen is a graduate of Washington University in St. Louis, where he received his Bachelor of Arts in Genomics and Computational Biology. His undergraduate research focused on variant discovery in experimentally evolved social amoebae, taking a bioinformatic approach to understanding the genetics behind certain behavioral and morphological phenotypes. As a part of the Mollah Lab, he hopes to utilize machine learning and systems biology approach to understand how post translational modification (PTMs) of histones influence gene regulation. He is currently studying the gene regulatory mechanisms and chromatin landscape of breast tumor microenvironment using high throughput RNASeq and ATACSeq data.

Charles, Lu

Bioinformatics Research Assistant, Email:

Charles is a recent graduate of Washington University in St. Louis, where he received his Bachelor of Science in Computer Science & Mathematics and Biochemistry. His undergraduate research focused on HOX gene expression regulation in AML. He was a MARC U-STAR Program scholar. As a part of the Mollah Lab, he hopes to utilize machine learning and systems biology approaches to connect epigenetic regulators to cancers and other complex diseases. He is currently developing hyper-relational knowledge graphs using natural language processing on biomedical textual data and spatial genomics data.

Heming, Zhang

PhD Rotation Student, Email:
Biomedical Data Science, specializing in Bioinformatics

Heming is a first year Ph.D. student at Washington University in St. Louis School of Medicine. He received his Master of Science in Computer Science from Washington University in St. Louis where he used computational and deep learning models, especially GNN (graph neural networks), to analyze cell signaling interactions and predict drug combinations’ effects. In Mollah lab, he will carry on his project to develop and test various transformational/ML methods for mass spectrometry data in breast cancer.

Reetika, Ghag

MS Student, Email: 
Biomedical Data Science, specializing in Translational Bioinformatics

Reetika is a masters student at Washington University in St. Louis School of Medicine. She earned her Bachelor of Engineering in Computer Engineering from Pune Institute of Computer Technology, India. In the Mollah lab, her research focus is to develop computational models and machine learning methods to integrate and analyze high-dimensional single-cell sequencing data.

 Stefanie, Kriel

Undergraduate Student, Email:
Biology, with a minor in Computational Biology

Stefanie is a sophomore at Washington University in St. Louis. In the Mollah Lab, Stefanie hopes to learn more about the intersection between machine learning, biological questions and in general, gain experience in professional research. She is currently working on determining enrichment of various phospho/proteins in signaling pathways in breast tumor microenvironment. 


Maya, Natesan

Undergraduate Student, Email:
Computer Science, with a minor in Bioinformatics

Maya is a junior at Washington University in St. Louis. Through her previous research experience, she has performed mutational signature analyses on annotated cancer variants and assessed variant oncogenicity utilizing bioinformatics tools. She is a NIH sponsored NCI summer intern. In the Mollah Lab, Maya hopes to utilize machine learning to decipher biological insights underlying chromatin remodeling in cancer. She is currently working on developing a predictive model for identifying chromatin remodeler proteins in cancer.

Laura, Valderrabano

Summer Intern, BIDS Program, Email:
Undergraduate Student, BIology, minor in Computational Biology

Laura is a Senior at Cornell University. In the Mollah Lab, Laura hopes to utilize machine learning, statistics, and proteomics data to automate signaling pathway of phoshpoproteins to determine cell fate in breast tumor microenvironment.

Looking for graduate students from CSB, MGG, HSG, BIDS, Cancer Biology, and Biochemistry to join!


Past Lab Members

Heyang, Ji

Graduate Student, Email:

Research: Hierarchical approach to cancer subtyping

Nathan, Wamsley

Graduate Student (rotation student), Email:
Computational and Systems Biology

Aparna, Anand

Graduate Student (rotation student), Email:

Molecular Genetics and Genomics

Paul, Morrison

Summer Intern, BIDS Program, Computer Science
Research: Generating 3D Network Models

Liubou, Klindziuk (Yuuna)

Summer Intern, BIDS Program, Mathematics, Email: Email:

Research: Deciphering tumor microenvironment in breast cancer using latent space model
Current: Computational biologist at Broad Institute

Lab Activities


4th of July cookout, 2020

Journal club