University of Pittsburgh

Predictive cell-specific gene regulatory models

Assistant Professor, ISP Faculty Candidate
Date: 
Friday, February 19, 2021 - 12:30pm - 1:30pm

Abstract: The development and function of specialized cell types are dependent on the interplay between complex signaling and transcriptional programs. We present SPaRTAN (Single-cell Proteomic and RNA based Transcription factor Activity Network), a computational method to link surface proteins to transcription factors (TFs) by exploiting cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) datasets with cis-regulatory information. SPaRTAN is applied to peripheral blood mononuclear cells (PBMCs) and tumor tissue datasets to demonstrate its utility in predicting cell-specific TF activity and their coupling to signaling pathways. To validate SPaRTAN-derived predictions, we perform flow cytometry analyses in peripheral blood from healthy donors and confirm the context-specific differential activity of TFs associated with surface proteins. SPaRTAN provides critical biological insights into the signal-regulated TFs that underlie key developmental or differentiation transitions and activation states of cells (e.g. within the immune system).

Bio: Hatice Ülkü Osmanbeyoğlu is an Assistant Professor of the Biomedical Informatics Department and UPMC Hillman Cancer Center at University of Pittsburgh Medical School. Her research focuses on developing data-driven computational approaches to understand disease mechanisms in order to assist in the development of personalizing anticancer treatments. Previously, she was a postdoctoral research associate at Memorial Sloan Kettering Cancer Center (MSKCC). She obtained her Ph.D. in Biomedical Informatics from University of Pittsburgh and holds a MS degree in Electrical and Computer Engineering from Carnegie Mellon University and MS in Bioengineering from University of Pittsburgh. She completed her BS in Computer Engineering from Northeastern University (Summa Cum Laude). She is a recipient of the NIH NCI Pathway to Independence Award, Memorial Sloan Kettering Postdoctoral Research Award and the Innovation in Cancer Informatics Award.

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