Anshul Kundaje

Summary

Affiliation: Stanford University
Country: USA

Publications

  1. pmc Ubiquitous heterogeneity and asymmetry of the chromatin environment at regulatory elements
    Anshul Kundaje
    Department of Computer Science, Stanford University, Stanford, California 94305, USA
    Genome Res 22:1735-47. 2012
  2. pmc Modeling gene expression using chromatin features in various cellular contexts
    Xianjun Dong
    Program in Bioinformatics and Integrative Biology, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA
    Genome Biol 13:R53. 2012
  3. pmc Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors
    Kevin Y Yip
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 13:R48. 2012
  4. ncbi request reprint Learning regulatory programs that accurately predict differential expression with MEDUSA
    Anshul Kundaje
    Department of Computer Science, Center for Computational Learning Systems, Columbia University, New York, NY 10065, USA
    Ann N Y Acad Sci 1115:178-202. 2007
  5. ncbi request reprint Combining sequence and time series expression data to learn transcriptional modules
    Anshul Kundaje
    Department of Computer Science, Columbia University, New York 10027, USA
    IEEE/ACM Trans Comput Biol Bioinform 2:194-202. 2005
  6. pmc Linking disease associations with regulatory information in the human genome
    Marc A Schaub
    Department of Computer Science, Stanford University, Stanford, California 94305, USA
    Genome Res 22:1748-59. 2012
  7. pmc ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia
    Stephen G Landt
    Department of Genetics, Stanford University, Stanford, California 94305, USA
    Genome Res 22:1813-31. 2012
  8. pmc A classification-based framework for predicting and analyzing gene regulatory response
    Anshul Kundaje
    Department of Computer Science, Columbia University, New York, NY 10027, USA
    BMC Bioinformatics 7:S5. 2006

Detail Information

Publications8

  1. pmc Ubiquitous heterogeneity and asymmetry of the chromatin environment at regulatory elements
    Anshul Kundaje
    Department of Computer Science, Stanford University, Stanford, California 94305, USA
    Genome Res 22:1735-47. 2012
    ..Meta-analyses of the signal profiles revealed a common vocabulary of chromatin signals shared across multiple cell lines and binding proteins...
  2. pmc Modeling gene expression using chromatin features in various cellular contexts
    Xianjun Dong
    Program in Bioinformatics and Integrative Biology, Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA 01605, USA
    Genome Biol 13:R53. 2012
    ..ENCODE also generated the genome-wide mapping of eleven histone marks, one histone variant, and DNase I hypersensitivity sites in seven cell lines...
  3. pmc Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors
    Kevin Y Yip
    Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
    Genome Biol 13:R48. 2012
    ..While this large amount of data creates a valuable resource, it is nonetheless overwhelmingly complex and simultaneously incomplete since it covers only a small fraction of all human transcription factors...
  4. ncbi request reprint Learning regulatory programs that accurately predict differential expression with MEDUSA
    Anshul Kundaje
    Department of Computer Science, Center for Computational Learning Systems, Columbia University, New York, NY 10065, USA
    Ann N Y Acad Sci 1115:178-202. 2007
    ..With MEDUSA, statistical validation becomes a prerequisite for hypothesis generation and network building rather than a secondary consideration...
  5. ncbi request reprint Combining sequence and time series expression data to learn transcriptional modules
    Anshul Kundaje
    Department of Computer Science, Columbia University, New York 10027, USA
    IEEE/ACM Trans Comput Biol Bioinform 2:194-202. 2005
    ....
  6. pmc Linking disease associations with regulatory information in the human genome
    Marc A Schaub
    Department of Computer Science, Stanford University, Stanford, California 94305, USA
    Genome Res 22:1748-59. 2012
    ..Our results show that the experimental data sets generated by the ENCODE Consortium can be successfully used to suggest functional hypotheses for variants associated with diseases and other phenotypes...
  7. pmc ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia
    Stephen G Landt
    Department of Genetics, Stanford University, Stanford, California 94305, USA
    Genome Res 22:1813-31. 2012
    ..All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals...
  8. pmc A classification-based framework for predicting and analyzing gene regulatory response
    Anshul Kundaje
    Department of Computer Science, Columbia University, New York, NY 10027, USA
    BMC Bioinformatics 7:S5. 2006
    ..Using the Adaboost algorithm, GeneClass learns a prediction function in the form of an alternating decision tree, a margin-based generalization of a decision tree...