FIMO: scanning for occurrences of a given motif von GRANT, Charles E, BAILEY, Timothy L, STAFFORD NOBLE, William

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Integrative detection and analysis of structural variation in cancer genomes von Dixon, Jesse R., Xu, Jie, Dileep, Vishnu, Zhan, Ye, Song, Fan, Le, Victoria T., Yardımcı, Galip Gürkan, Chakraborty, Abhijit, Bann, Darrin V., Wang, Yanli, Clark, Royden, Zhang, Lijun, Yang, Hongbo, Liu, Tingting, Iyyanki, Sriranga, An, Lin, Pool, Christopher, Sasaki, Takayo, Rivera-Mulia, Juan Carlos, Ozadam, Hakan, Lajoie, Bryan R., Kaul, Rajinder, Buckley, Michael, Lee, Kristen, Diegel, Morgan, Pezic, Dubravka, Ernst, Christina, Hadjur, Suzana, Odom, Duncan T., Stamatoyannopoulos, John A., Broach, James R., Hardison, Ross C., Ay, Ferhat, Noble, William Stafford, Dekker, Job, Gilbert, David M., Yue, Feng

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GenomeDISCO: a concordance score for chromosome conformation capture experiments using random walks on contact map graphs von Ursu, Oana, Boley, Nathan, Taranova, Maryna, Wang, Y X Rachel, Yardimci, Galip Gurkan, Stafford Noble, William, Kundaje, Anshul

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Kernel methods for predicting protein–protein interactions von Ben-Hur, Asa, Noble, William Stafford

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Machine learning applications in genetics and genomics von Libbrecht, Maxwell W., Noble, William Stafford

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Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation von Baur, Brittany, Shin, Junha, Schreiber, Jacob, Zhang, Shilu, Zhang, Yi, Manjunath, Mohith, Song, Jun S, Stafford Noble, William, Roy, Sushmita

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Matrix2png: a utility for visualizing matrix data von Pavlidis, Paul, Noble, William Stafford

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qvality: non-parametric estimation of q-values and posterior error probabilities von Käll, Lukas, Storey, John D., Noble, William Stafford

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Mismatch string kernels for discriminative protein classification von Leslie, Christina S., Eskin, Eleazar, Cohen, Adiel, Weston, Jason, Noble, William Stafford

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Ten simple rules for defining a computational biology project von Noble, William Stafford

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Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts von Ay, Ferhat, Bailey, Timothy L, Noble, William Stafford

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Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure von Lewis, Darrin P., Jebara, Tony, Noble, William Stafford

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Ten simple rules for writing a response to reviewers von Noble, William Stafford

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Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome von Schreiber, Jacob, Durham, Timothy, Bilmes, Jeffrey, Noble, William Stafford

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Improved similarity scores for comparing motifs von TANAKA, Emi, BAILEY, Timothy, GRANT, Charles E, STAFFORD NOBLE, William, KEICH, Uri

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HiCRep.py: fast comparison of Hi-C contact matrices in Python von Lin, Dejun, Sanders, Justin, Noble, William Stafford

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Massively parallel profiling and predictive modeling of the outcomes of CRISPR/Cas9-mediated double-strand break repair von Chen, Wei, McKenna, Aaron, Schreiber, Jacob, Haeussler, Maximilian, Yin, Yi, Agarwal, Vikram, Noble, William Stafford, Shendure, Jay

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A learned score function improves the power of mass spectrometry database search von Ananth, Varun, Sanders, Justin, Yilmaz, Melih, Wen, Bo, Oh, Sewoong, Noble, William Stafford

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A statistical approach for inferring the 3D structure of the genome von Varoquaux, Nelle, Ay, Ferhat, Noble, William Stafford, Vert, Jean-Philippe

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HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient von Yang, Tao, Zhang, Feipeng, Yardımcı, Galip Gürkan, Song, Fan, Hardison, Ross C, Noble, William Stafford, Yue, Feng, Li, Qunhua

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