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Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization
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 dis...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038205/ https://www.ncbi.nlm.nih.gov/pubmed/32024005 http://dx.doi.org/10.3390/ijms21030961 |
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author | Paul, Piby Antonydhason, Vimala Gopal, Judy Haga, Steve W. Hasan, Nazim Oh, Jae-Wook |
author_facet | Paul, Piby Antonydhason, Vimala Gopal, Judy Haga, Steve W. Hasan, Nazim Oh, Jae-Wook |
author_sort | Paul, Piby |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7038205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70382052020-03-10 Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization Paul, Piby Antonydhason, Vimala Gopal, Judy Haga, Steve W. Hasan, Nazim Oh, Jae-Wook Int J Mol Sci Review 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. MDPI 2020-01-31 /pmc/articles/PMC7038205/ /pubmed/32024005 http://dx.doi.org/10.3390/ijms21030961 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Paul, Piby Antonydhason, Vimala Gopal, Judy Haga, Steve W. Hasan, Nazim Oh, Jae-Wook Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization |
title | Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization |
title_full | Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization |
title_fullStr | Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization |
title_full_unstemmed | Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization |
title_short | Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization |
title_sort | bioinformatics for renal and urinary proteomics: call for aggrandization |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038205/ https://www.ncbi.nlm.nih.gov/pubmed/32024005 http://dx.doi.org/10.3390/ijms21030961 |
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