Dept. of Genetics
Dept. of Computer Science
Department of Genetics
300 Pasteur Dr., Lane Building, L301
Stanford, CA 94305-5120, USA [Map]
E-mail: anshul @ kundaje .net ; akundaje @ stanford .edu
Phone: (650)-723-2353 ; Fax: (650)-725-1534
- Develop large-scale, statistical data processing pipelines for the analysis of functional genomic data (e.g. ChIP-seq data)
- Develop machine learning methods to predict regulatory elements (e.g. enhancers), their context-specific activity and underlying sequence grammars (regulatory motif discovery)
- Develop machine learning methods to learn complex gene regulation programs by integrating large-scale regulatory maps with massive gene expression compendia
- Decipher causal regulatory dynamics by analyzing temporal (e.g. differentiation and reprogramming) and perturbation (e.g. drug response and knockdown) experiments
- Model the relationship between genetic variation, regulatory variation and expression variation in healthy and diseased individuals
2012-2013, I was a Research Scientist in Manolis Kellis' lab studying epigenomic and chromatin state dynamics across organisms, cell-types and individuals as part of the Roadmap Epigenomics Project and the mod/ENCODE (Encyclopedia for DNA elements) consortium.
2003-2008, I was a graduate student (PhD degree) in Christina Leslie
's lab in the Computer Science Dept. at Columbia University in New York. I developed Machine Learning methods for modeling transcriptional gene regulation in yeast and worm.
RECENT PUBLICATIONS / CONFERENCE TALKS
- Large-scale quality analysis of published ChIP-seq data
Marinov GK, Kundaje A, Park PJ, Wold BJ
G3 (Bethesda). 2013 Dec 17. pii: g3.113.008680v1. doi: 10.1534/g3.113.008680
- Extensive Variation in Chromatin States Across Humans [Website] [Data]
Kasowski M*, Kyriazopoulou-Panagiotopoulou S*, Grubert F*, Zaugg JB*, Kundaje A*, Liu Y, Boyle AP, Zhang QC, Zakharia Q, Spacek DV, Li J, Xie D, Olarerin-George A, Steinmetz LM, Hogenesch JB, Kellis M, Batzoglou S, Snyder M
Science. 2013 Oct 17; DOI:10.1126/science.1242510
* Equal contribution
- Epigenomic variation across species, cell-types, populations and individuals [Talk]
Selected Platform Talk at American Society of Human Genetics (ASHG) 2013
- Dynamics of chromatin state and gene regulation across human cell-types and individuals [Talk]
Invited talk at BIRS Statistical Data Integration Challenges in Computational Biology: Regulatory Networks and Personalized Medicine, Banff, Canada, Aug 2013
- Comparative analysis of chromatin state dynamics across organisms, cell types and individuals [Talk]
Selected talk at Cold Spring Harbor Labs - Biology of Genomes meeting, May 2013
- Integrative annotation of chromatin elements from ENCODE data. [Website] [Code1] [Code2] [Code3]
- Hoffman MM, Ernst J, Wilder SP, Kundaje A, Harris RS, Libbrecht M, Giardine B, Ellenbogen PM, Bilmes JA, Birney E, Hardison RC, Dunham I, Kellis M, Noble WS.
- Nucleic Acids Res. 2013 Jan;41(2):827-41. doi: 10.1093/nar/gks1284. Epub 2012 Dec 5.