Hakutulokset - Anshul Kundaje

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  1. 1
    Reverse-complement parameter sharing improves deep learning models for genomics

    Reverse-complement parameter sharing improves deep learning models for genomics Tekijä Avanti Shrikumar, Peyton Greenside, Anshul Kundaje

    Julkaistu 2017
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  2. 2
    GkmExplain: fast and accurate interpretation of nonlinear gapped k-mer SVMs

    GkmExplain: fast and accurate interpretation of nonlinear gapped k-mer SVMs Tekijä Avanti Shrikumar, Eva Prakash, Anshul Kundaje

    Julkaistu 2019
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    Artigo
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  3. 3
    Characterization of the direct targets of<scp>FOXO</scp>transcription factors throughout evolution

    Characterization of the direct targets of<scp>FOXO</scp>transcription factors throughout evolution Tekijä Ashley E. Webb, Anshul Kundaje, Anne Brunet

    Julkaistu 2016
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    Artigo
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  4. 4
    Denoising genome-wide histone ChIP-seq with convolutional neural networks

    Denoising genome-wide histone ChIP-seq with convolutional neural networks Tekijä Pang Wei Koh, Emma Pierson, Anshul Kundaje

    Julkaistu 2017
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    Artigo
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  5. 5
    The ENCODE Blacklist: Identification of Problematic Regions of the Genome

    The ENCODE Blacklist: Identification of Problematic Regions of the Genome Tekijä Haley M. Amemiya, Anshul Kundaje, Alan P. Boyle

    Julkaistu 2019
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    Artigo
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  6. 6
    Umap and Bismap: quantifying genome and methylome mappability

    Umap and Bismap: quantifying genome and methylome mappability Tekijä Mehran Karimzadeh, Carl Ernst, Anshul Kundaje, Michael M. Hoffman

    Julkaistu 2018
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    Artigo
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  7. 7
    Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts

    Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts Tekijä Surag Nair, Daniel Sunwook Kim, Jacob Perricone, Anshul Kundaje

    Julkaistu 2019
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    Artigo
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  8. 8
    MTSplice predicts effects of genetic variants on tissue-specific splicing

    MTSplice predicts effects of genetic variants on tissue-specific splicing Tekijä Jun Cheng, Muhammed Hasan Çelik, Anshul Kundaje, Julien Gagneur

    Julkaistu 2021
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    Artigo
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  9. 9
    Deciphering the impact of genetic variation on human polyadenylation using APARENT2

    Deciphering the impact of genetic variation on human polyadenylation using APARENT2 Tekijä Johannes Linder, Samantha E. Koplik, Anshul Kundaje, Georg Seelig

    Julkaistu 2022
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  10. 10
    Large-Scale Quality Analysis of Published ChIP-seq Data

    Large-Scale Quality Analysis of Published ChIP-seq Data Tekijä Georgi K. Marinov, Anshul Kundaje, Peter J. Park, B Wold

    Julkaistu 2013
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    Artigo
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  11. 11
    Predicting genetic regulatory response using classification

    Predicting genetic regulatory response using classification Tekijä Manuel Middendorf, Anshul Kundaje, Chris Wiggins, Yoav Freund, Christina Leslie

    Julkaistu 2004
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  12. 12
    Discovering epistatic feature interactions from neural network models of regulatory DNA sequences

    Discovering epistatic feature interactions from neural network models of regulatory DNA sequences Tekijä Peyton Greenside, Tyler C. Shimko, Polly M. Fordyce, Anshul Kundaje

    Julkaistu 2018
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  13. 13
    Initiation of mtDNA transcription is followed by pausing, and diverges across human cell types and during evolution

    Initiation of mtDNA transcription is followed by pausing, and diverges across human cell types and during evolution Tekijä Amit Blumberg, Edward J. Rice, Anshul Kundaje, Charles G. Danko, Dan Mishmar

    Julkaistu 2017
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    Artigo
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  14. 14
    Linking disease associations with regulatory information in the human genome

    Linking disease associations with regulatory information in the human genome Tekijä Marc A. Schaub, Alan P. Boyle, Anshul Kundaje, Serafim Batzoglou, M Snyder

    Julkaistu 2012
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  15. 15
    Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays

    Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays Tekijä Rajiv Movva, Peyton Greenside, Georgi K. Marinov, Surag Nair, Avanti Shrikumar, Anshul Kundaje

    Julkaistu 2019
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  16. 16
    Transcription-dependent domain-scale three-dimensional genome organization in the dinoflagellate Breviolum minutum

    Transcription-dependent domain-scale three-dimensional genome organization in the dinoflagellate Breviolum minutum Tekijä Georgi K. Marinov, Alexandro E. Trevino, T. Xiang, Anshul Kundaje, Arthur Grossman, William J. Greenleaf

    Julkaistu 2021
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  17. 17
    Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease

    Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease Tekijä Elizabeta Gjoneska, Andreas Pfenning, Hansruedi Mathys, Gerald Quon, Anshul Kundaje, Li-Huei Tsai, Manolis Kellis

    Julkaistu 2015
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  18. 18
    Domain-adaptive neural networks improve cross-species prediction of transcription factor binding

    Domain-adaptive neural networks improve cross-species prediction of transcription factor binding Tekijä Kelly Cochran, Divyanshi Srivastava, Avanti Shrikumar, Akshay Balsubramani, Ross C. Hardison, Anshul Kundaje, Shaun Mahony

    Julkaistu 2022
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  19. 19
    Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage

    Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage Tekijä Sahin Naqvi, Seungsoo Kim, Saman Tabatabaee, Anusri Pampari, Anshul Kundaje, Jonathan K. Pritchard, Joanna Wysocka

    Julkaistu 2025
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  20. 20
    Chromatin accessibility dynamics reveal novel functional enhancers in <i>C. elegans</i>

    Chromatin accessibility dynamics reveal novel functional enhancers in <i>C. elegans</i> Tekijä Aaron C. Daugherty, Robin W. Yeo, Jason D. Buenrostro, William J. Greenleaf, Anshul Kundaje, Anne Brunet

    Julkaistu 2017
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