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Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements.

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Title: Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements.
Authors: Pratt HE; Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA., Andrews G; Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA., Shedd N; Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA., Phalke N; Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA., Li T; Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA.; Khoury College of Computer Science, Northeastern University, Boston, MA 02115, USA., Pampari A; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA., Jensen M; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA., Wen C; Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA.; Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA., Consortium P, Gandal MJ; Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA.; Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.; Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA., Geschwind DH; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.; Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.; Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA., Gerstein M; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.; Department of Computer Science, Yale University, New Haven, CT 06520, USA.; Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA., Moore J; Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA., Kundaje A; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.; Department of Computer Science, Stanford University, Stanford, CA 94305, USA., Colubri A; Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA., Weng Z; Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA.
Source: Science advances [Sci Adv] 2024 May 24; Vol. 10 (21), pp. eadj4452. Date of Electronic Publication: 2024 May 23.
Publication Type: Journal Article
Journal Info: Publisher: American Association for the Advancement of Science Country of Publication: United States NLM ID: 101653440 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2375-2548 (Electronic) Linking ISSN: 23752548 NLM ISO Abbreviation: Sci Adv Subsets: MEDLINE
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