Farid Rashidi


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

I am a fellow at National Cancer Institute. Prior to that, I received my Ph.D. from Indiana University Bloomington in Computer Science where I worked on Tumor Heterogeneity and Cancer Evolution modeling using Single-cell sequencing data. I accomplished my Ph.D. thesis as a predoctoral fellow at National Institutes of Health in Cancer Data Science Laboratory under supervision of Dr. Cenk Sahinalp. I completed my Master's thesis at Sharif University of Technology where I worked on learning of Alternative Splicing problem, jointly supervised by Dr. Abolfazl Motahari and Dr. Hamid Rabiee. I accomplished my Bachelor's thesis from Amirkabir University of Technology in Iran.



Publications:


P7 Profiles of expressed mutations in single cells reveal subclonal expansion patterns and therapeutic impact of intratumor heterogeneity
bioRxiv Full text Poster Webpage Code Presentation
P6 Epigenomic tumor evolution modeling with single-cell methylation data profiling
bioRxiv Full text
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


Software:

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