Zachary Thomas

PhD

PhD Student

image analisys MATLAB Python R R Programming scRNA-Seq (Single-cell RNA Sequencing) Spatial Transcriptomics Transcriptomics

Peer-reviewed publication(s) 1st author peer-reviewed publication(s) Funding

· Doctoral Student Researcher in Dr. Rong Lu's lab studying hematopoietic stem cells. Research topics include identifying cell-cell communication networks in the hematopoietic system and studying the effects of the circadian clock on hematopoiesis. · Heterogeneous intercellular communication of hematopoietic stem cells in the mouse bone marrow. Developed a novel computational algorithm to quantify intercellular signaling in hematopoietic stem and progenitor cells (HSPCs), introducing a Spatiomolecular Signaling Potential (SSP) metric. Integrated multi-modal datasets (ligand-receptor expression, cell abundance, and spatial positioning) to model cell-cell communication within the bone marrow microenvironment. Built a comprehensive database of signaling interactions across HSPC populations using both published and newly generated mouse datasets. Identified previously uncharacterized signaling pathways and feedback mechanisms between stem cells and downstream immune progenitors. Discovered stage- and lineage-specific correlations between signaling pathways, revealing regulatory patterns across hematopoietic differentiation. Applied gene-level analysis to classify HSPC populations de novo, improving understanding of functional heterogeneity. Validated computational predictions through transplantation experiments, identifying novel regulators of hematopoiesis. Characterized discrete cell-fate transition phases by analyzing coordinated shifts in signaling networks along differentiation trajectories. Designed and deployed the Hematopoiesis Intercellular Signaling Explorer (HISE), an accessible resource for exploring cell-cell communication and signaling networks. Established a generalizable computational framework for analyzing dynamic intercellular signaling applicable to complex biological systems.

· Research assistant in Dr. Chonghzi Zang's Lab for Computational Biology at UVA. Research topics include identifying functional transcription factors in various cancer types and functional genome organization in colorectal cancer. · BART Cancer: A web resource for transcriptional regulators in cancer genome. Integrated over 10,000 gene expression profiling RNA-seq datasets and 7,000 ChIP-seq datasets to predict and display putative transcriptional regulators across 15 different cancer types. BART Cancer also displays the activities of over 900 transcriptional regulators across cancer types, by integrating computational prediction results from BART and from the Cistrome Cancer database. The website database can be found at bartcancer.org. Presented at the 28th Conference on Intelligent Systems for Molecular Biology. · Functional genome organization in colorectal cancer: an integrative data science approach. Fourth year capstone project with the goal of developing a computational pipeline for analyzing tumor Hi-C data with integrating a compendium of 3D genome data from the public domain. The pipeline aims to identify cancer specific CTCF binding sites as well as putative transcriptional regulators involved in the tumorigenesis of colorectal cancer.