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3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures
Many studies have used position-specific scoring matrices (PSSM) profiles to characterize residues in protein structures and to predict a broad range of protein features. Moreover, PSSM profiles of Protein Data Bank (PDB) entries have been recalculated in many works for different purposes. Although...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6149929/ https://www.ncbi.nlm.nih.gov/pubmed/29244774 http://dx.doi.org/10.3390/molecules22122230 |
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author | Sanchez-Garcia, Ruben Sorzano, Carlos Oscar Sanchez Carazo, Jose Maria Segura, Joan |
author_facet | Sanchez-Garcia, Ruben Sorzano, Carlos Oscar Sanchez Carazo, Jose Maria Segura, Joan |
author_sort | Sanchez-Garcia, Ruben |
collection | PubMed |
description | Many studies have used position-specific scoring matrices (PSSM) profiles to characterize residues in protein structures and to predict a broad range of protein features. Moreover, PSSM profiles of Protein Data Bank (PDB) entries have been recalculated in many works for different purposes. Although the computational cost of calculating a single PSSM profile is affordable, many statistical studies or machine learning-based methods used thousands of profiles to achieve their goals, thereby leading to a substantial increase of the computational cost. In this work we present a new database compiling PSSM profiles for the proteins of the PDB. Currently, the database contains 333,532 protein chain profiles involving 123,135 different PDB entries. |
format | Online Article Text |
id | pubmed-6149929 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61499292018-11-13 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures Sanchez-Garcia, Ruben Sorzano, Carlos Oscar Sanchez Carazo, Jose Maria Segura, Joan Molecules Technical Note Many studies have used position-specific scoring matrices (PSSM) profiles to characterize residues in protein structures and to predict a broad range of protein features. Moreover, PSSM profiles of Protein Data Bank (PDB) entries have been recalculated in many works for different purposes. Although the computational cost of calculating a single PSSM profile is affordable, many statistical studies or machine learning-based methods used thousands of profiles to achieve their goals, thereby leading to a substantial increase of the computational cost. In this work we present a new database compiling PSSM profiles for the proteins of the PDB. Currently, the database contains 333,532 protein chain profiles involving 123,135 different PDB entries. MDPI 2017-12-15 /pmc/articles/PMC6149929/ /pubmed/29244774 http://dx.doi.org/10.3390/molecules22122230 Text en © 2017 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 | Technical Note Sanchez-Garcia, Ruben Sorzano, Carlos Oscar Sanchez Carazo, Jose Maria Segura, Joan 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures |
title | 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures |
title_full | 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures |
title_fullStr | 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures |
title_full_unstemmed | 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures |
title_short | 3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures |
title_sort | 3dcons-db: a database of position-specific scoring matrices in protein structures |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6149929/ https://www.ncbi.nlm.nih.gov/pubmed/29244774 http://dx.doi.org/10.3390/molecules22122230 |
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