Research Interests

Artificial intelligence (AI) and single-cell studies have been making waves in the science and technology communities. AI offers a broad range of methods that can be used to investigate diverse data- and hypothesis-driven questions in single-cell biology. The highly heterogeneous nature of single-cell data can be analyzed across a wide range of research topics by generalizing deep-learning model design and optimization in a hypothesis-free manner. Our lab focuses on the research of single-cell multi-omics data, aiming to develop cutting-edge computational tools to discover underlying mechanisms in diverse biological systems.
Ma, Q., Xu, D. Deep learning shapes single-cell data analysis. Nat Rev Mol Cell Biol (2022)

Highlighted Projects



1. Regulatory mechanisms in complex tissues. 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 deep learning algorithms for enhancer-GRN construction and rare cell population discoveries in cases, such as aging cells and minimal residue diseases.
GrantsR01GM131399-01 (PI), U54AG075931 (Core PI), NSF1945971 (PI)
2. Immuno-oncology. Single-cell multi-omics has brought transformative insights into immuno-oncology, demonstrating success in describing novel immune subsets and defining important regulators of antitumor immunity. One significant challenge in immuno-oncology is identifying the heterogeneity of immune cells in tumors and their differentiation process. To overcome these limitations, a scMulti-omics study can offer detailed identification of diverse immune subsets at a higher resolution and provide an opportunity to understand the contribution of immune cells to tumor progression. Our lab endeavors single-cell applications in immuno-oncological areas.
GrantsR01CA262069-01 (Co-I), R01AI162779-02 (Co-I), U24CA252977 (MPI)
3. Tissue module in human diseases. Spatially resolved transcriptomics provides a new way to define spatial contexts in human diseases. It is challenging to accurately characterize tissue architectures and the underlying biological functions from spatial transcriptomic. Our project aims to use graph neural networks to reconstruct tissue architectures and identify spatially variable genes and specific regulatory relations. Another goal is to identify cell-cell communications as well as signal transduction regulatory networks from spatial transcriptome data.
GrantsR21HG012482 (MPI)
4. Neurodegenerative disease. Single-cell RNA-sequencing (scRNA-seq) and single-nucleus RNA-sequencing (snRNA-seq) studies have provided remarkable insights into understanding human brains. Our lab takes the advantage of single-cell multi-omics and spatial transcriptomic data to discover the mystery of the molecular mechanisms in neural systems and the pathogenesis of Alzheimer’s disease (AD).
Grants: R01MH124870-02 (Co-I), R01AG075092 (Co-I), R01DK126008-02 (Co-I)
5. Microbiome and host interactions. 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.
Grants: R01MH129589-01 (Co-I), CCTS Pilot (PI; 2020 completed)

Recent news

[Sep-26-2022] The manuscript “SUSD2 suppresses CD8+ T cell antitumor immunity by targeting IL-2 receptor signaling” has been accepted for publication in Nature Immunology and will be available online soon!

[Sep-23-2022] Dr. Jordan Krull will join BMBL and PIIO immuno-oncology informatics group as a post-doc researcher. Welcome!

[Sep-7-2022] Our collaborative study “Durability of Booster mRNA Vaccine against SARS-CoV-2 BA.2.12.1, BA.4, and BA.5 Subvariants” has been officially published on New England Journal of Medicine!

[Aug-12-2022] The manuscript “Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning” has been accepted for publication in Computational and Structural Biotechnology Journal and will be available online soon!

[Jul-29-2022] We are pleased to announce the appointment of Qin Ma, PhD, as the Section Chief of Computational Biology and Bioinformatics in the Department of Biomedical Informatics, OSU.

[Jul-25-2022] Dr. Qin Ma and Dr. Anjun Ma have been invited as guest editors for the special issue “Single-Cell and Spatial Multi-Omics Technologies in Human Health” of Biomolecules. Submissions are welcome!

[Jul-20-2022] The manuscript “Deep Learning Analysis of Single-Cell Data in Empowering Clinical Implementation” has been published on Clinical and Translational Medicine!

[Jul-18-2022] The manuscript “A Bayesian Multivariate Mixture Model for High Throughput Spatial Transcriptomics” has been accepted for publication in Biometrics and will be available online soon!

[Jul-12-2022] Our collaborative study “Sampling and ranking spatial transcriptomics data embeddings to identify tissue architecture” with Dr. Dong Xu has been accepted by Frontiers in Genetics!

[Jul-10-2022] Our collaborative study “FACT subunit SUPT16H associates with BRD4 and contributes to silencing of interferon signaling” has been officially accepted by Nucleic Acids Research and will be available online soon!

[Jul-06-2022] The Computational Biology and Chemistry (CBAC) journal, in which Dr. Qin Ma serves as an Editor, has achieved a new high impact factor of 3.737! The impact factor of CBAC has continuously increased with a huge bump from 1.8 (2019) and 2.877 (2020) to 3.737 (2021).

[Jul-06-2022] Our collaborative study “A Concurrent Canonical and Modified miRNAome Pan-Cancer Study on TCGA and TARGET Cohorts Leads to an Enhanced Resolution in Cancer” has been provisionally accepted by Cancer Research.

[Jul-01-2022] Our collaborative study “Microglia coordinate cellular interactions during spinal cord repair in mice” has been officially accepted by Nature Communications and will be available online soon!

[Jun-29-2022] The manuscript “Sex-Biased Adaptive Immune Regulation in Cancer Development and Therapy” has been accepted by iScience and will be available online soon!

[Jun-23-2022] Mrs. Jia Qu has been enrolled in the BMI graduate program and will join BMBL next semester. Welcome!

[Jun-21-2022] Our XSEDE Research Grant ‘A Computational Pipeline for Cell Type Classification and Cell-type-specific Gene Markers Identification based on Single-cell RNA-Sequencing Data’ has been awarded for three months extension.

[Jun-17-2022] We are pleased to announce the appointment of Qin Ma, PhD, as leader of the Immuno-Oncology Informatics Group (IOIG) within the Pelotonia Institute for Immuno-Oncology (PIIO) at the OSUCCC – James. He will be responsible for bolstering the data-science needs of the PIIO and will help us eliminate the bottleneck of data analysis. Please check the details here. Cheers!

[Jun-16-2022] Our manuscript “DESSO-DB: A web database for sequence and shape motif analyses and identification” has been officially published in the Computational and Structural Biotechnology Journal (IF=7.2). Xiaoying Wang and Cankun Wang are the co-first authors. Congratulations!

[Jun-13-2022] Our review manuscript “Deep Learning Analysis of Single-Cell Data in Empowering Clinical Implementation” has been officially accepted by Clinical and Translational Medicine (IF=11.5).

[May-19-2022] Our collaborative study “A shared disease-associated oligodendrocyte signature among multiple CNS pathologies” has been officially accepted by Nature Neuroscience and will be available online soon!

[May-18-2022] The review article “The use of single-cell multi-omics in immuno-oncology” has been officially published online in Nature Communications!

[May-06-2022] Mr. Mohnish Karthikeyan joins BMBL as a new high school student volunteer. Welcome!

[May-06-2022] Our review article “Single-cell multi-omics in immuno-oncology” has been officially accepted by Nature Communications and will be available online soon!

[Apr-21-2022] The article “A New Machine Learning-Based Framework for Mapping Uncertainty Analysis in RNA-Seq Read Alignment and Gene Expression Estimation” is among the topmost viewed articles in Frontiers in Genetics with 6778 views.

[Apr-14-2022] Our collaborative work with Dr. Zihai Li and PIIO, entitled “Androgen conspires with the CD8+ T cell exhaustion program and contributes to sex bias in cancer“, has been officially published in Science Immunology (IF= 17.73)!

[Apr-05-2022] Mr. Qin Ma has been invited to present at the CTSI Analytics Colloquium, University of Rochester Medical Center, on April 25th.  Online registration is now available. Check details here.

[Mar-31-2022] Our collaborative work (Wolframin is a novel regulator of tau pathology and neurodegeneration) with Dr. Hongjun Fu has been accepted by Acta neuropathological (IF= 18.17)!

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