Preimplantation development regulatory pathway construction through a text-mining approach

Publication type:
Journal article
Metadata:
Autoren
  • Elisa Donnard
  • Adriano Barbosa-Silva
  • Rafael LM Guedes
  • Gabriel R Fernandes
  • Henrique Velloso
  • Matthew J Kohn
  • Miguel A Andrade-Navarro
  • J Miguel Ortega
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000303921800003&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1186/1471-2164-12-S4-S3
Externe Identifier
  • Clarivate Analytics Document Solution ID: 940VS
  • PubMed Identifier: 22369103
ISSN
1471-2164
Zeitschrift
BMC GENOMICS
Artikelnummer
ARTN S3
Datum der Veröffentlichung
2011
Status
Published
Titel
Preimplantation development regulatory pathway construction through a text-mining approach
Sub types
  • Article
  • Proceedings Paper
Ausgabe der Zeitschrift
12

Data source: Web of Science (Lite)

Other metadata sources:
Abstract
<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>The integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>In this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>The generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as “seeds” for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.</jats:p> </jats:sec>
Autoren
  • Elisa Donnard
  • Adriano Barbosa-Silva
  • Rafael LM Guedes
  • Gabriel R Fernandes
  • Henrique Velloso
  • Matthew J Kohn
  • Miguel A Andrade-Navarro
  • J Miguel Ortega
DOI
10.1186/1471-2164-12-s4-s3
eISSN
1471-2164
Ausgabe der Veröffentlichung
S4
Zeitschrift
BMC Genomics
Sprache
en
Artikelnummer
S3
Online publication date
2011
Datum der Veröffentlichung
2011
Status
Published
Herausgeber
Springer Science and Business Media LLC
Herausgeber URL
http://dx.doi.org/10.1186/1471-2164-12-s4-s3
Datum der Datenerfassung
2021
Titel
Preimplantation development regulatory pathway construction through a text-mining approach
Ausgabe der Zeitschrift
12

Data source: Crossref

Abstract
<h4>Background</h4>The integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms.<h4>Results</h4>In this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements.<h4>Conclusions</h4>The generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as "seeds" for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.
Addresses
  • Laboratório Biodados, Dept. de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, 31270-901, Belo Horizonte - MG, Brazil.
Autoren
  • Elisa Donnard
  • Adriano Barbosa-Silva
  • Rafael LM Guedes
  • Gabriel R Fernandes
  • Henrique Velloso
  • Matthew J Kohn
  • Miguel A Andrade-Navarro
  • J Miguel Ortega
DOI
10.1186/1471-2164-12-s4-s3
eISSN
1471-2164
Externe Identifier
  • PubMed Identifier: 22369103
  • PubMed Central ID: PMC3287586
Open access
true
ISSN
1471-2164
Zeitschrift
BMC genomics
Schlüsselwörter
  • Animals
  • Humans
  • Mice
  • Stem Cell Transplantation
  • Cluster Analysis
  • Embryonic Development
  • Software
  • Information Storage and Retrieval
  • Databases, Factual
  • Gene Regulatory Networks
  • Data Mining
Sprache
eng
Medium
Print-Electronic
Online publication date
2011
Open access status
Open Access
Paginierung
S3
Datum der Veröffentlichung
2011
Status
Published
Publisher licence
CC BY
Datum der Datenerfassung
2012
Titel
Preimplantation development regulatory pathway construction through a text-mining approach.
Sub types
  • research-article
  • Journal Article
Ausgabe der Zeitschrift
12 Suppl 4

Files

https://bmcgenomics.biomedcentral.com/counter/pdf/10.1186/1471-2164-12-S4-S3 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22369103/pdf/?tool=EBI https://europepmc.org/articles/PMC3287586?pdf=render

Data source: Europe PubMed Central

Abstract
BACKGROUND: The integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms. RESULTS: In this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements. CONCLUSIONS: The generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as "seeds" for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.
Autoren
  • Elisa Donnard
  • Adriano Barbosa-Silva
  • Rafael LM Guedes
  • Gabriel R Fernandes
  • Henrique Velloso
  • Matthew J Kohn
  • Miguel A Andrade-Navarro
  • J Miguel Ortega
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/22369103
DOI
10.1186/1471-2164-12-S4-S3
eISSN
1471-2164
Externe Identifier
  • PubMed Central ID: PMC3287586
Ausgabe der Veröffentlichung
Suppl 4
Zeitschrift
BMC Genomics
Schlüsselwörter
  • Animals
  • Cluster Analysis
  • Data Mining
  • Databases, Factual
  • Embryonic Development
  • Gene Regulatory Networks
  • Humans
  • Information Storage and Retrieval
  • Mice
  • Software
  • Stem Cell Transplantation
Sprache
eng
Country
England
Paginierung
S3
PII
1471-2164-12-S4-S3
Datum der Veröffentlichung
2011
Status
Published
Datum, an dem der Datensatz öffentlich gemacht wurde
2012
Titel
Preimplantation development regulatory pathway construction through a text-mining approach.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
12 Suppl 4

Data source: PubMed

Beziehungen:
Property of

Tools