Find Faculty

Cigdem Sevim Bayrak, PhD

img_Cigdem Sevim Bayrak
ASSISTANT PROFESSOR | Genetics and Genomic Sciences
email
Research Topics
Bioinformatics, Computational Biology, Genetics, Human Genetics and Genetic Disorders, Mathematical and Computational Biology, Personalized Medicine, Protein Structure/Function, RNA
Modeling Cross-Tissue Regulation and Disease Risk Using Multi-Omics
This research focuses on developing interpretable computational and machine learning methods to integrate transcriptomic and multi-omic data for investigating cross-tissue gene regulation and the molecular mechanisms underlying complex diseases. Applications include developing blood-based predictive models for mild cognitive impairment and Alzheimer’s disease to identify molecular signatures associated with disease risk, heterogeneity, and progression.
Machine Learning for Functional Variant Interpretation
This research develops machine learning approaches to characterize the functional effects of genetic variants, particularly pathogenic gain-of-function and loss-of-function mutations. By integrating natural language processing, supervised learning, and sequence, structural, and evolutionary features, this work supports systematic variant classification and genome-wide prediction of variant function, advancing functional genomics and the interpretation of genetic contributions to human disease.
Network- and Pathway-Based Gene Prioritization in Complex Diseases
This research develops computational methods that integrate genetic and transcriptomic data with pathway and network information to prioritize disease-associated genes and variants. Applications across neurodevelopmental, neurological, metabolic, and inflammatory disorders aim to identify biologically meaningful genes, pathways, and molecular networks, providing mechanistic insights into disease biology and potential therapeutic targets.
Multi-Omic Subtyping of Vaccine Response
This research investigates heterogeneity in human vaccine responses through integrative analysis of transcriptomic, proteomic, glycomic, and metabolomic data. By identifying baseline molecular immune subtypes associated with antibody responses, this work aims to elucidate the biological determinants of vaccine responsiveness and support precision approaches to vaccine design and optimization.

PhD, Koç University

Postdoc, Icahn School of Medicine at Mount Sinai

Postdoc, New York University

Icahn (East) Building Floor 3

1425 Madison Ave

New York, NY 10029

Physicians and scientists on the faculty of the Icahn School of Medicine at Mount Sinai often interact with pharmaceutical, device, biotechnology companies, and other outside entities to improve patient care, develop new therapies and achieve scientific breakthroughs. In order to promote an ethical and transparent environment for conducting research, providing clinical care and teaching, Mount Sinai requires that salaried faculty inform the School of their outside financial relationships.

Dr. Sevim Bayrak has not yet completed reporting of industry relationships or has no industry relationships to report.

Mount Sinai's faculty policies relating to faculty collaboration with industry are posted on our website. Patients may wish to ask their physician about the activities they perform for companies.