Qualitative and quantitative modeling of single-cell transcriptomics and its application in cardiomyopathy
Date: 2026/04/27 – 2026/04/27
Dissertation Title: Qualitative and quantitative modeling of single-cell transcriptomics and its application in cardiomyopathy
Speaker: Jinpu Cai, Ph.D. candidate at SJTU Global College
Time: April 27th from 1:30 p.m. to 3:30 p.m., 2026 (Beijing Time)
Location: Room 202, The Global Institute of Future Technology
Abstract
This dissertation presents a systematic study on qualitative and quantitative modeling of single-cell transcriptomics, with a focus on applications in cardiomyopathy. It proposes MULE, a mutual exclusivity–based framework for identifying gene modules and capturing cell-type–specific regulatory patterns. To model quantitative variation, hyperspherical embedding methods are developed, followed by GAIA, an information geometry–based framework that unifies discrete and continuous expression features under a consistent metric. The proposed methods improve the representation of single-cell data and enhance performance in downstream analyses, including clustering and spatial domain identification. Application to cardiomyopathy datasets identifies disease-associated cardiomyocyte subtypes and highlights key genes such as SLC6A6 and SPOCK1. These results provide new insights into the molecular mechanisms of cardiomyopathy and establish a computational foundation for precision diagnosis and targeted therapeutic strategies.
Biography
Jinpu Cai received the B.S. degree in Software Engineering from the College of Software, Jilin University, Changchun, China, in June 2021. He is currently pursuing the Ph.D. degree in Information and Communication Engineering. His research focuses on single-cell multi-omics analysis and bioinformatics. His work has been published in international journals and conferences, including Briefings in Bioinformatics, RECOMB, and ACM-BCB. He also received the Best Paper Award at ACM-BCB 2024.