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Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization.
Paul, Piby; Antonydhason, Vimala; Gopal, Judy; Haga, Steve W; Hasan, Nazim; Oh, Jae-Wook.
Afiliação
  • Paul P; St. Jude Childrens Cancer Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA.
  • Antonydhason V; Department of Microbiology and Immunology, Institute for Biomedicine, Gothenburg University, 413 90 Gothenburg, Sweden.
  • Gopal J; Department of Environmental Health Sciences, Konkuk University, Seoul 143-701, Korea.
  • Haga SW; Department of Computer Science and Engineering, National Sun Yat Sen University, Kaohsiung 804, Taiwan.
  • Hasan N; Department of Chemistry, Faculty of Science, Jazan University, P.O. Box 114, Jazan 45142, Saudi Arabia.
  • Oh JW; Department of Stem Cell and Regenerative Biotechnology, Konkuk University, Seoul 05029, Korea.
Int J Mol Sci ; 21(3)2020 Jan 31.
Article em En | MEDLINE | ID: mdl-32024005
ABSTRACT
The clinical sampling of urine is noninvasive and unrestricted, whereby huge volumes can be easily obtained. This makes urine a valuable resource for the diagnoses of diseases. Urinary and renal proteomics have resulted in considerable progress in kidney-based disease diagnosis through biomarker discovery and treatment. This review summarizes the bioinformatics tools available for this area of proteomics and the milestones reached using these tools in clinical research. The scant research publications and the even more limited bioinformatic tool options available for urinary and renal proteomics are highlighted in this review. The need for more attention and input from bioinformaticians is highlighted, so that progressive achievements and releases can be made. With just a handful of existing tools for renal and urinary proteomic research available, this review identifies a gap worth targeting by protein chemists and bioinformaticians. The probable causes for the lack of enthusiasm in this area are also speculated upon in this review. This is the first review that consolidates the bioinformatics applications specifically for renal and urinary proteomics.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Urina / Biologia Computacional / Rim Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Int J Mol Sci Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Urina / Biologia Computacional / Rim Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Int J Mol Sci Ano de publicação: 2020 Tipo de documento: Article