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We are a computational omics lab at the University of Pittsburgh and affiliated with the Department of Biomedical Informatics, Bioengineering and UPMC Hillman Cancer Center. Our group's primary focus is on developing integrative machine learning approaches for extracting therapeutic and biological insights from highly heterogeneous omic datasets, clinical and drug response data, with the purpose of advancing precision medicine. Our projects span across the following areas: 

  • Cancer Genomics: Leveraging machine learning techniques to analyze genomic data from cancer patients, identifying genetic mutations, biomarkers, and potential therapeutic targets for personalized cancer treatment.

  • Single Cell and Spatial Omics: Developing statistical methods for single-cell multi-omics integration, integrating data from different omic layers (such as genomics, proteomics, transcriptomics, epigenomics) to gain a comprehensive understanding of cellular processes and disease mechanisms.

  • Epigenetics: Studying how epigenetic modifications influence an individual's response to different drugs and integrating epigenetic data with clinical information.

Our projects are executed through multi-disciplinary collaborations, recognizing that precision medicine requires expertise from various domains. By leveraging machine learning and integrating diverse datasets, our aim is to contribute to the advancement of precision medicine, ultimately leading to more targeted and effective treatments for patients.

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NEWS

2023

  • Elena Kim was honored with a poster award at the Center for Systems Immunology Retreat

  • Koushul Ramjattun was honored with the Best Student Paper 1st Place award at the Biomedical Informatics Training Program Retreat

  • Our paper in collaboration with Roy Lab, "Vascular endothelial profilin-1 drives a pro-tumorigenic tumor microenvironment and tumor progression in renal cancer", is accepted to publish in Journal of Biological Chemistry

  • Our paper "COVID-19db linkage maps of cell surface proteins and transcription factors in immune cells" is published in Journal of Medical Virology

  • Our book chapter "Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired Single-Cell Proteomes and Transcriptomes", is published.

  • The lab receives an NIGMS administrative supplement to support undergraduate summer research experience. Excited about Ambar Gautam's summer research.

  • Our paper in collaboration with Vignali and Oesterreich Lab, "Immune landscape in invasive ductal and lobular breast cancer reveals a divergent macrophage-driven microenvironment", is published in Nature Cancer

  • Sanghoon Lee receives Hillman Postdoctoral Fellowship for Innovative Cancer Research

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2022

  • Our paper "Isolated BAP1 loss in malignant pleural mesothelioma predicts immunogenicity with implications for immunotherapeutic response" is published in Cancers

  • The lab receives an Maximizing Investigators' Research Award (MIRA) for Early-Stage Investigators (R35)

  • Maneka Puligandla receives Hillman Medical Student Fellowship for Innovative Cancer Research 

  • Our paper "Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers" is published in Nucleic Acids Research

  • Our paper in collaboration with Bakkenist Lab, "Thymidine rescues ATR kinase inhibitor-induced deoxyuridine contamination in genomic DNA, cell death, and interferon-α/β expression", is published in Cell Reports

  • April Sagan's abstract “STAN, a computational framework for inferring spatially informed transcription factor activity networks” selected for oral presentation at the 14th annual RECOMB/ISCB Conference on Regulatory & Systems Genomics

  • Our paper "Chromatin accessibility and active transcription factors in primary human invasive lobular and ductal breast carcinomas" is published in Breast Cancer Research

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2021

  • Our paper in collaboration with Buckanovich Lab, "Cancer-associated MSC drive tumor immune exclusion and resistance to immunotherapy, which can be overcome by Hedgehog inhibition", is published in Science Advances

  • Our paper "SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators" is published in Nucleic Acids Research

  • Our paper in collaboration with Cheng Lab, "Targeting Aurora B kinase prevents and overcomes resistance to EGFR inhibitors in lung cancer by enhancing BIM- and PUMA-mediated apoptosis", is published in Cancer Cell

  • Our paper in collaboration with Duvvuri  Lab, "Recurrent human papillomavirus-related head and neck cancer undergoes metabolic re-programming and is driven by oxidative phosphorylation", is published in Clinical Cancer Research

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2019

  • The lab receives an Award from The Fund for Innovation in Cancer Informatics

  • Our paper in collaboration with Bakkenist Lab, "WEE1 kinase inhibitor AZD1775 induces CDK1 kinase-dependent origin firing in unperturbed G1 and S phase cells", is published in Proc Natl Acad Sci.

  • Our paper "Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers" is published in Nature Communications 

  • Our paper in collaboration with Bakkenist Lab, "An ATR and CHK1 kinase signaling mechanism that limits origin firing during unperturbed DNA replication", is published in Proc Natl Acad Sci.

  • The lab receives an NCI R00 Award

 
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