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SIGNOR: a database of causal relationships between biological entities
Assembly of large biochemical networks can be achieved by confronting new cell-specific experimental data with an interaction subspace constrained by prior literature evidence. The SIGnaling Network Open Resource, SIGNOR (available on line at http://signor.uniroma2.it), was developed to support such...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702784/ https://www.ncbi.nlm.nih.gov/pubmed/26467481 http://dx.doi.org/10.1093/nar/gkv1048 |
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author | Perfetto, Livia Briganti, Leonardo Calderone, Alberto Perpetuini, Andrea Cerquone Iannuccelli, Marta Langone, Francesca Licata, Luana Marinkovic, Milica Mattioni, Anna Pavlidou, Theodora Peluso, Daniele Petrilli, Lucia Lisa Pirrò, Stefano Posca, Daniela Santonico, Elena Silvestri, Alessandra Spada, Filomena Castagnoli, Luisa Cesareni, Gianni |
author_facet | Perfetto, Livia Briganti, Leonardo Calderone, Alberto Perpetuini, Andrea Cerquone Iannuccelli, Marta Langone, Francesca Licata, Luana Marinkovic, Milica Mattioni, Anna Pavlidou, Theodora Peluso, Daniele Petrilli, Lucia Lisa Pirrò, Stefano Posca, Daniela Santonico, Elena Silvestri, Alessandra Spada, Filomena Castagnoli, Luisa Cesareni, Gianni |
author_sort | Perfetto, Livia |
collection | PubMed |
description | Assembly of large biochemical networks can be achieved by confronting new cell-specific experimental data with an interaction subspace constrained by prior literature evidence. The SIGnaling Network Open Resource, SIGNOR (available on line at http://signor.uniroma2.it), was developed to support such a strategy by providing a scaffold of prior experimental evidence of causal relationships between biological entities. The core of SIGNOR is a collection of approximately 12 000 manually-annotated causal relationships between over 2800 human proteins participating in signal transduction. Other entities annotated in SIGNOR are complexes, chemicals, phenotypes and stimuli. The information captured in SIGNOR can be represented as a signed directed graph illustrating the activation/inactivation relationships between signalling entities. Each entry is associated to the post-translational modifications that cause the activation/inactivation of the target proteins. More than 4900 modified residues causing a change in protein concentration or activity have been curated and linked to the modifying enzymes (about 351 human kinases and 94 phosphatases). Additional modifications such as ubiquitinations, sumoylations, acetylations and their effect on the modified target proteins are also annotated. This wealth of structured information can support experimental approaches based on multi-parametric analysis of cell systems after physiological or pathological perturbations and to assemble large logic models. |
format | Online Article Text |
id | pubmed-4702784 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47027842016-01-07 SIGNOR: a database of causal relationships between biological entities Perfetto, Livia Briganti, Leonardo Calderone, Alberto Perpetuini, Andrea Cerquone Iannuccelli, Marta Langone, Francesca Licata, Luana Marinkovic, Milica Mattioni, Anna Pavlidou, Theodora Peluso, Daniele Petrilli, Lucia Lisa Pirrò, Stefano Posca, Daniela Santonico, Elena Silvestri, Alessandra Spada, Filomena Castagnoli, Luisa Cesareni, Gianni Nucleic Acids Res Database Issue Assembly of large biochemical networks can be achieved by confronting new cell-specific experimental data with an interaction subspace constrained by prior literature evidence. The SIGnaling Network Open Resource, SIGNOR (available on line at http://signor.uniroma2.it), was developed to support such a strategy by providing a scaffold of prior experimental evidence of causal relationships between biological entities. The core of SIGNOR is a collection of approximately 12 000 manually-annotated causal relationships between over 2800 human proteins participating in signal transduction. Other entities annotated in SIGNOR are complexes, chemicals, phenotypes and stimuli. The information captured in SIGNOR can be represented as a signed directed graph illustrating the activation/inactivation relationships between signalling entities. Each entry is associated to the post-translational modifications that cause the activation/inactivation of the target proteins. More than 4900 modified residues causing a change in protein concentration or activity have been curated and linked to the modifying enzymes (about 351 human kinases and 94 phosphatases). Additional modifications such as ubiquitinations, sumoylations, acetylations and their effect on the modified target proteins are also annotated. This wealth of structured information can support experimental approaches based on multi-parametric analysis of cell systems after physiological or pathological perturbations and to assemble large logic models. Oxford University Press 2016-01-04 2015-10-13 /pmc/articles/PMC4702784/ /pubmed/26467481 http://dx.doi.org/10.1093/nar/gkv1048 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Perfetto, Livia Briganti, Leonardo Calderone, Alberto Perpetuini, Andrea Cerquone Iannuccelli, Marta Langone, Francesca Licata, Luana Marinkovic, Milica Mattioni, Anna Pavlidou, Theodora Peluso, Daniele Petrilli, Lucia Lisa Pirrò, Stefano Posca, Daniela Santonico, Elena Silvestri, Alessandra Spada, Filomena Castagnoli, Luisa Cesareni, Gianni SIGNOR: a database of causal relationships between biological entities |
title | SIGNOR: a database of causal relationships between biological entities |
title_full | SIGNOR: a database of causal relationships between biological entities |
title_fullStr | SIGNOR: a database of causal relationships between biological entities |
title_full_unstemmed | SIGNOR: a database of causal relationships between biological entities |
title_short | SIGNOR: a database of causal relationships between biological entities |
title_sort | signor: a database of causal relationships between biological entities |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702784/ https://www.ncbi.nlm.nih.gov/pubmed/26467481 http://dx.doi.org/10.1093/nar/gkv1048 |
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