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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
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.
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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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