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DescribePROT in 2023: more, higher-quality and experimental annotations and improved data download options.
Basu, Sushmita; Zhao, Bi; Biró, Bálint; Faraggi, Eshel; Gsponer, Jörg; Hu, Gang; Kloczkowski, Andrzej; Malhis, Nawar; Mirdita, Milot; Söding, Johannes; Steinegger, Martin; Wang, Duolin; Wang, Kui; Xu, Dong; Zhang, Jian; Kurgan, Lukasz.
Afiliación
  • Basu S; Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA.
  • Zhao B; Genomics Program, College of Public Health, University of South Florida, Tampa, FL, USA.
  • Biró B; Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA.
  • Faraggi E; Department of Animal Biotechnology, Hungarian University of Agriculture and Life Sciences, Gödöllo, Hungary.
  • Gsponer J; Physics Department, Indiana University, Indianapolis, IN, USA.
  • Hu G; Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada.
  • Kloczkowski A; School of Statistics and Data Science, LPMC and KLMDASR, Nankai University, Tianjin, P.R. China.
  • Malhis N; The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, USA.
  • Mirdita M; Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia, Canada.
  • Söding J; School of Biological Sciences, Seoul National University, Seoul, Republic of Korea.
  • Steinegger M; Quantitative and Computational Biology, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany.
  • Wang D; School of Biological Sciences, Seoul National University, Seoul, Republic of Korea.
  • Wang K; Institute of Molecular Biology & Genetics, Seoul National University, Seoul, Republic of Korea.
  • Xu D; Artificial Intelligence Institute, Seoul National University, Seoul, South Korea.
  • Zhang J; Department of Electrical Engineer and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, USA.
  • Kurgan L; School of Statistics and Data Science, LPMC and KLMDASR, Nankai University, Tianjin, P.R. China.
Nucleic Acids Res ; 52(D1): D426-D433, 2024 Jan 05.
Article en En | MEDLINE | ID: mdl-37933852
The DescribePROT database of amino acid-level descriptors of protein structures and functions was substantially expanded since its release in 2020. This expansion includes substantial increase in the size, scope, and quality of the underlying data, the addition of experimental structural information, the inclusion of new data download options, and an upgraded graphical interface. DescribePROT currently covers 19 structural and functional descriptors for proteins in 273 reference proteomes generated by 11 accurate and complementary predictive tools. Users can search our resource in multiple ways, interact with the data using the graphical interface, and download data at various scales including individual proteins, entire proteomes, and whole database. The annotations in DescribePROT are useful for a broad spectrum of studies that include investigations of protein structure and function, development and validation of predictive tools, and to support efforts in understanding molecular underpinnings of diseases and development of therapeutics. DescribePROT can be freely accessed at http://biomine.cs.vcu.edu/servers/DESCRIBEPROT/.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proteoma / Aminoácidos Idioma: En Revista: Nucleic Acids Res Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proteoma / Aminoácidos Idioma: En Revista: Nucleic Acids Res Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos