Shivalika Pathania, PhD

Research

I am a computational biologist and bioinformatician. I am interested in integrating genetic, environmental, and clinical information to better understand complex disease risk, and in extending genetic findings to the systems level through multi-omics integration and network biology.

EHR-linked genomics and statistical genetics

At the University of Michigan, I integrate large-scale genomic datasets with clinical information derived from electronic health records (EHRs). My current research includes EHR-based phenotyping, polygenic risk scores (PRS), phenome-wide association studies (PheWAS), genome-wide association studies (GWAS), and predictive and statistical modeling.

Multi-omics integration and systems biology

My doctoral and postdoctoral research used computational systems biology and transcriptomics to study biological regulation and identify candidate genes and molecules. This work included integrating bulk RNA sequencing (RNA-seq), small-RNA, and degradome data, using differential expression, gene co-expression, and regulatory-network approaches to investigate genes, pathways, and regulatory mechanisms.

Computational resources and drug discovery

I have developed biological databases and used molecular docking, molecular dynamics, and network-based approaches to investigate bioactive molecules and potential therapeutic targets. Resources developed during my doctoral research include Phytochemica and SerpentinaDB.

Background

I completed my PhD research in Bioinformatics and Computational Biology at the CSIR-Institute of Himalayan Bioresource Technology. My degree was awarded through Guru Nanak Dev University, India.

Current role

I am a postdoctoral research fellow in the Department of Biostatistics at the University of Michigan. I joined the Fritsche Lab in 2025.