Farid Rashidi

2-6300, bldg10, NIH
frashidi AT iu DOT edu

I am a data scientist and researcher working in the field of computational oncology. Currently, I am a fellow at the National Cancer Institute doing research on cancer vaccine in the Laboratory of Human Carcinogenesis under the supervision of Xin Wei Wang. I received my Ph.D. from Indiana University in computer science where I developed computational tools to infer tumor heterogeneity and cancer evolution using single-cell sequencing data. I completed my Ph.D. thesis as a predoctoral visiting fellow at the National Institutes of Health in Cancer Data Science Laboratory under the supervision of Cenk Sahinalp. I accomplished my Master's thesis at the Sharif University of Technology where I worked on the learning of alternative splicing problems, jointly supervised by Abolfazl Motahari and Hamid Rabiee. I completed my Bachelor's thesis at the Amirkabir University of Technology in Iran. My research interests are in developing novel bioinformatics methods for investigating high-throughput genomics and single-cell sequencing data to understand biological processes, with a particular interest in cancer.


P8 Profiles of expressed mutations in single cells reveal subclonal expansion patterns and therapeutic impact of intratumor heterogeneity
bioRxiv Full text Poster Webpage Code Presentation
P7 Epigenomic tumor evolution modeling with single-cell methylation data profiling
bioRxiv Full text
P6 Fast intratumor heterogeneity inference from single-cell sequencing data
Nature Computational Science Full text Supplementary Code
P5 Review on Studying the History of Tumor Evolution from Single-Cell Sequencing Data by Exploring the Space of Binary Matrices
Journal of Computational Biology Full text
P4 A Transcriptionally Distinct Subpopulation of Healthy Acinar Cells Exhibit Features of Pancreatic Progenitors and PDAC
Cancer Research Full text Supplementary
P3 PhISCS-BnB: a fast branch and bound algorithm for the perfect tumor phylogeny reconstruction problem
Bioinformatics ISMB 2020 Proceedings Full text Supplementary Code Presentation
P2 Clonal Evolution and Heterogeneity of Osimertinib Acquired Resistance Mechanisms in EGFR Mutant Lung Cancer
Cell Reports Medicine Full text Supplementary
P1 PhISCS: a combinatorial approach for subperfect tumor phylogeny reconstruction via integrative use of single-cell and bulk sequencing data
Genome Research Full text Supplementary Code Presentation


S6 scPhylo-tools: a python toolkit for single-cell tumor phylogenetic analysis
Webpage Code Star Fork
S5 Trisicell: a scalable tumor phylogeny reconstruction and validation tool using single-cell data
Webpage Code Publication Star Fork
S4 PhISCS: a tool for sub-perfect tumor phylogeny reconstruction via integrative use of single-cell and bulk sequencing data
Code Publication Star Fork
S3 PhISCS-BnB: a fast tool for reconstructing the perfect tumor phylogeny using single-ceqll data via branch and bound algorithm
Code Publication Star Fork
S2 HUNTRESS: a provably fast intratumor heterogeneity inference from single-cell sequencing data
Code Star Fork
S1 Kaggle Solutions: a searchable list of almost all available solutions and ideas shared by top performers in the past Kaggle competitions
Webpage Code Star Fork