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The interactome: Predicting the protein-protein interactions in cells
The term Interactome describes the set of all molecular interactions in cells, especially in the context of protein-protein interactions. These interactions are crucial for most cellular processes, so the full representation of the interaction repertoire is needed to understand the cell molecular ma...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SP Versita
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6275871/ https://www.ncbi.nlm.nih.gov/pubmed/18839074 http://dx.doi.org/10.2478/s11658-008-0024-7 |
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author | Plewczyński, Dariusz Ginalski, Krzysztof |
author_facet | Plewczyński, Dariusz Ginalski, Krzysztof |
author_sort | Plewczyński, Dariusz |
collection | PubMed |
description | The term Interactome describes the set of all molecular interactions in cells, especially in the context of protein-protein interactions. These interactions are crucial for most cellular processes, so the full representation of the interaction repertoire is needed to understand the cell molecular machinery at the system biology level. In this short review, we compare various methods for predicting protein-protein interactions using sequence and structure information. The ultimate goal of those approaches is to present the complete methodology for the automatic selection of interaction partners using their amino acid sequences and/or three dimensional structures, if known. Apart from a description of each method, details of the software or web interface needed for high throughput prediction on the whole genome scale are also provided. The proposed validation of the theoretical methods using experimental data would be a better assessment of their accuracy. |
format | Online Article Text |
id | pubmed-6275871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | SP Versita |
record_format | MEDLINE/PubMed |
spelling | pubmed-62758712018-12-10 The interactome: Predicting the protein-protein interactions in cells Plewczyński, Dariusz Ginalski, Krzysztof Cell Mol Biol Lett Mini Review The term Interactome describes the set of all molecular interactions in cells, especially in the context of protein-protein interactions. These interactions are crucial for most cellular processes, so the full representation of the interaction repertoire is needed to understand the cell molecular machinery at the system biology level. In this short review, we compare various methods for predicting protein-protein interactions using sequence and structure information. The ultimate goal of those approaches is to present the complete methodology for the automatic selection of interaction partners using their amino acid sequences and/or three dimensional structures, if known. Apart from a description of each method, details of the software or web interface needed for high throughput prediction on the whole genome scale are also provided. The proposed validation of the theoretical methods using experimental data would be a better assessment of their accuracy. SP Versita 2008-10-06 /pmc/articles/PMC6275871/ /pubmed/18839074 http://dx.doi.org/10.2478/s11658-008-0024-7 Text en © © Versita Warsaw and Springer-Verlag Berlin Heidelberg 2008 |
spellingShingle | Mini Review Plewczyński, Dariusz Ginalski, Krzysztof The interactome: Predicting the protein-protein interactions in cells |
title | The interactome: Predicting the protein-protein interactions in cells |
title_full | The interactome: Predicting the protein-protein interactions in cells |
title_fullStr | The interactome: Predicting the protein-protein interactions in cells |
title_full_unstemmed | The interactome: Predicting the protein-protein interactions in cells |
title_short | The interactome: Predicting the protein-protein interactions in cells |
title_sort | interactome: predicting the protein-protein interactions in cells |
topic | Mini Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6275871/ https://www.ncbi.nlm.nih.gov/pubmed/18839074 http://dx.doi.org/10.2478/s11658-008-0024-7 |
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