Mercedeh Javanbakht Movassagh
Cards
About
Titles
Associate Research Scientist
Biography
Dr. Movassagh is an Associate Research Scientist with a focus on infectious disease computational biology and bioinformatics, at Yale School of Medicine. She got her BS from University of Virginia, Masters in Biochemistry and Bioinformatics from George Washington University and PhD from University of Massachusetts Medical School in Computational Biology and Bioinformatics. Her post-doctoral fellow ship was at Harvard School of Public Health and Dana Farber Cancer Institute departments of Biostatistics and Data science respectively with a focus on infectious disease computational biology and global public health in under resourced communities and countries. She is also interested in investigating the role of pathogens in development of diseases in neonates, and children such as but not limited to neonatal sepsis, post infectious hydrocephalus, Burkitt Lymphoma and diarrhea using computational biology and bioinformatics analysis and methods development.
Appointments
Neurosurgery
Associate Research ScientistPrimary
Other Departments & Organizations
- Neurosurgery
- Red College Affiliates
- Schiff Lab
Education & Training
- MS
- George Washington University, Biochemistry and Bioinformatics
- PhD
- University of Massachusetts Medical School , Computational Biology and Bioinformatics
- BS
- University of Virginia, Biology
Research
Overview
Detailed expertise and methods development:
Development of computational and statistical methods for infectious disease genomics and sequencing data analysis (mirTarRnaSeq, mbQTL, VDJdive, RNA2DNAlign and PathSeeker).
Machine learning (Random Forest, SVMs, Topic Models, Clustering, Elastic Nets, Regressions, etc).
Next generation sequencing (NGS) analysis (RNA, microRNA (miRNA), whole genome sequencing (WGS), microbiome sequencing (16s rRNA) and T cell receptor (TCR) single cell sequencing.
Population genetics and ancestry analysis for WGS.
Genome wide association studies (GWAS).
Scalable processing of sparse sequencing data such as microbiome data.
Detailed Research interests:
Infectious disease (microbial, viral, parasitic and fungal), neonatal sepsis, hydrocephalus, RNAs and ncRNAs, computational biology, metagenomics, bioinformatics and biostatistics, machine learning, tropical medicine, global public health, and pathogenic cancers such as Burkitt Lymphoma, and interplay of host and human microbiome.