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The evolution of computational research in a data-centric world.
Deshpande, Dhrithi; Chhugani, Karishma; Ramesh, Tejasvene; Pellegrini, Matteo; Shiffman, Sagiv; Abedalthagafi, Malak S; Alqahtani, Saleh; Ye, Jimmie; Liu, Xiaole Shirley; Leek, Jeffrey T; Brazma, Alvis; Ophoff, Roel A; Rao, Gauri; Butte, Atul J; Moore, Jason H; Katritch, Vsevolod; Mangul, Serghei.
Affiliation
  • Deshpande D; Titus Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA 90089, USA. Electronic address: dhrithideshpande@gmail.com.
  • Chhugani K; Titus Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA 90089, USA.
  • Ramesh T; Department of Pharmacology and Pharmaceutical Sciences, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA 90089, USA.
  • Pellegrini M; Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA.
  • Shiffman S; Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
  • Abedalthagafi MS; Genomics Research Department, King Fahad Medical City, Riyadh, Saudi Arabia; Department of Pathology & Laboratory Medicine, Emory University Hospital, Atlanta, GA, USA.
  • Alqahtani S; The Liver Transplant Unit, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia; The Division of Gastroenterology and Hepatology, Johns Hopkins University, Baltimore, MD 21205, USA.
  • Ye J; Department of Epidemiology & Biostatistics, Institute for Human Genetics, University of California, San Francisco, 513 Parnassus Avenue S965F, San Francisco, CA 94143, USA.
  • Liu XS; GV20 Oncotherapy, One Broadway, 14th Floor, Kendall Square, Cambridge, MA 02142, USA.
  • Leek JT; Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Data Science Lab, John Hopkins University, 615 N. Wolfe Street, Baltimore, MD 21205, USA.
  • Brazma A; EMBL European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK.
  • Ophoff RA; Department of Psychiatry and Human Genetics, Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
  • Rao G; Titus Department of Clinical Pharmacy, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA 90089, USA.
  • Butte AJ; Bakar Computational Health Sciences Institute, University of California, San Francisco, 490 Illinois Street, San Francisco, CA 94158, USA.
  • Moore JH; Department of Computational Biomedicine, Cedars-Sinai Medical Center, 700 N. San Vicente Boulevard, Pacific Design Center Suite G540, West Hollywood, CA 90068, USA.
  • Katritch V; Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90007, USA.
  • Mangul S; Department of Quantitative and Computational Biology, USC Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90007, USA. Electronic address: serghei.mangul@gmail.com.
Cell ; 187(17): 4449-4457, 2024 Aug 22.
Article de En | MEDLINE | ID: mdl-39178828
ABSTRACT
Computational data-centric research techniques play a prevalent and multi-disciplinary role in life science research. In the past, scientists in wet labs generated the data, and computational researchers focused on creating tools for the analysis of those data. Computational researchers are now becoming more independent and taking leadership roles within biomedical projects, leveraging the increased availability of public data. We are now able to generate vast amounts of data, and the challenge has shifted from data generation to data analysis. Here we discuss the pitfalls, challenges, and opportunities facing the field of data-centric research in biology. We discuss the evolving perception of computational data-driven research and its rise as an independent domain in biomedical research while also addressing the significant collaborative opportunities that arise from integrating computational research with experimental and translational biology. Additionally, we discuss the future of data-centric research and its applications across various areas of the biomedical field.
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Biologie informatique / Recherche biomédicale Limites: Humans Langue: En Journal: Cell Année: 2024 Type de document: Article Pays de publication: États-Unis d'Amérique
Texte intégral
Ajouter à My VHL
Imprimer
XML
PubMed Links
Recherche sur Google

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Biologie informatique / Recherche biomédicale Limites: Humans Langue: En Journal: Cell Année: 2024 Type de document: Article Pays de publication: États-Unis d'Amérique