TuBA: Tunable biclustering algorithm reveals clinically relevant tumor transcriptional profiles in breast cancer

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  1. Now published in GigaScience doi: 10.1093/gigascience/giz064

    Amartya Singh 1Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, USA2Center for Systems and Computational Biology, Rutgers Cancer Institute, Rutgers University, New Brunswick, NJ, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteGyan Bhanot 1Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, USA2Center for Systems and Computational Biology, Rutgers Cancer Institute, Rutgers University, New Brunswick, NJ, USA3Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteHossein Khiabanian 1Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, USA2Center for Systems and Computational Biology, Rutgers Cancer Institute, Rutgers University, New Brunswick, NJ, USA3Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ, USA4Department of Pathology and Laboratory Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USAFind this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Hossein Khiabanian

    A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giz064 ), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

    These peer reviews were as follows:

    Reviewer 1: http://dx.doi.org/10.5524/REVIEW.101761 Reviewer 2: http://dx.doi.org/10.5524/REVIEW.101762 Reviewer 3: http://dx.doi.org/10.5524/REVIEW.101763