Adaptive Framework for Integrating Regulatory Pathways and Cellular Signaling in Single Cell Biology
Defense Date
2026
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Integrative Life Sciences
First Advisor
Preetam Ghosh
Abstract
Single-cell RNA sequencing (scRNA-seq) has transformed the study of cellular heterogeneity, enabling detailed characterization of cell types, regulatory programs, and disease-associated transcriptional changes. However, the growing number of computational methods for core analysis tasks introduces variability and limits reproducibility across datasets. In this dissertation, I present a generalizable computational framework for single-cell analysis that integrates regulatory pathways and cellular signaling to improve biological interpretability. First, I develop consensus-based methods for key scRNA-seq tasks, including cell clustering and gene regulatory network inference, leveraging a wisdom-of-crowds strategy to enhance performance across datasets. Second, I introduce novel approaches for cell-type-resolved marker gene selection and signaling-informed transcription factor activity estimation, incorporating both downstream gene expression and upstream cell–cell communication signals to better capture regulatory mechanisms. Finally, I apply state of the art single cell genomics analysis methods to disease contexts in neurology and cancer, using single-cell and spatial transcriptomics to uncover cell-type-specific signaling and transcriptional changes associated with disease progression and therapeutic response. Together, this work bridges methodological development and biomedical application, providing a unified framework for integrating cellular signaling and gene regulation in single-cell genomics.
Rights
© Musaddiq Lodi
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
5-7-2026