Research Interests


Our lab focuses on developing computational methods to discover heterogeneous transcriptional regulatory mechanisms from single-cell sequencing data. Our efforts are split between inferring cell-type-specific regulatory signals and constructing reliable gene regulatory networks via the integration of single-cell multi-omics. We are also going into the development of novel computational algorithms for spatial transcriptomic data analysis in immuno-oncology and neuroscience.

We are developing enabling tools and databases, using metagenomic and metatranscriptomic data, to elucidate microbial systems and their interactions with human diseases. Our goal is to deliver reproducible and integrated analyses of complex gut microbiome data, detect functional and taxonomic abundances (biomarkers) in a microbial community, and infer significant associations between clinical measurements of human diseases and transformed microbial biomarkers.

Recent news

[Jan-05-2022] Yuzhou Chang has successfully completed his Ph.D. candidacy defense. Congratulations!

[Dec-10-2021] Yuzhou Chang was awarded for Excellence in Research (Grad Student) in the Department of Biomedical Informatics of the year 2021. Congratulations!

[Dec-10-2021] Dr. Jing Zhao was awarded for Excellence in Collaborative Research (Staff-Grant) in the Department of Biomedical Informatics of the year 2021. Congratulations!

[Nov-16-2021] Dr. Anjun Ma has been invited for a presentation titled “Graph neural network applications in single-cell Multi-omics analysis” at Front Line Genomics as part of the Integrated Single-cell multi-omics session on December 9th.

[Nov-13-2021] The manuscript “Artificial Intelligence in Clinical Research of Cancers” has been accepted for publication in Briefings in Bioinformatics. Congratulations, Dr. Jing Zhao!

[Nov-9-2021] Dr. Qin Ma is reported as an innovator in medicine by the OSU College of Medicine news channel for co-leading the Ohio State coordinating center for the NCI’s new $85 million PE-CGS network that will combat disparities in cancer genome sequencing.

[Oct-21-2021] Yuzhou Chang has been selected for presentation for the upcoming Rocky 2021 conference at Snowmass, Colorado (December 2-4).

[Oct-20-2021] The TriState SenNet Tissue Mapping Center (U54) was officially funded by NIH. Congratulations!

[Oct-20-2021] Dr. Anjun Ma has been promoted to Research Scientist in the Department of Biomedical Informatics. Big congratulations!

[Oct-6-2021] Dr. Qin Ma takes an interview about Decoding cell behavior and disease with AI and single-cell transcriptomic at Drug Discovery News.

[Sep-10-2021] Dr. Jing Zhao has been promoted to Assistant Professor (Clinical) in the Department of Biomedical Informatics, effective on October 01, 2021. Big congratulations!

[August-24-2021] Dr. Qin Ma will give an invited presentation on September 22nd at Nature portfolio webcast, with the topic of “single-cell multi-omics methods in cancer research”. Register now for free!

[August-23-2021] Dr. Qin Ma was appointed editorial board member with Computational and Structural Biotechnology Journal.

[August-2-2021] The manuscript “Deep Transfer Learning of Drug Sensitivity by Integrating Bulk and Single-cell RNA-seq data” is online on bioRxiv.

[July-28-2021] The manuscript “scGNN is a novel graph neural network model for single-cell RNA-Seq analysis” is reported in the 97th percentile of the 320,570 tracked articles of a similar age in all journals and ranked 1st of the tracked articles of a similar age in Nature Communications.

[July-28-2021] The manuscript “scREAD: A Single-Cell RNA-Seq Database for Alzheimer’s Disease” was recently listed on SSRN’s Top Ten download list for: NeurosciRN: Neuroinformatics & Information Systems (Topic).

[July-9-2021] The manuscript “RESEPT: tissue architecture inference and visualization from spatially resolved transcriptomics” is online on bioRxiv.

[July-8-2021] The manuscript “Spatially resolved transcriptomics reveals unique gene signatures associated with human temporal cortical architecture and Alzheimer’s pathology” is online on bioRxiv.

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