Understanding gene regulatory mechanisms by integrating ChIP-seq and RNA-seq data: statistical solutions to biological problems. (Articolo in rivista)

Type

• Prodotto della ricerca (Classe)
• Articolo in rivista (Classe)

Label

• Understanding gene regulatory mechanisms by integrating ChIP-seq and RNA-seq data: statistical solutions to biological problems. (Articolo in rivista) (literal)

Anno

• 2014-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.3389/fcell.2014.00051 (literal)

Alternative label

• Angelini, Claudia; Costa, Valerio (2014)
  Understanding gene regulatory mechanisms by integrating ChIP-seq and RNA-seq data: statistical solutions to biological problems.
  in Frontiers in Cell and Developmental Biology
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Angelini, Claudia; Costa, Valerio (literal)

Pagina inizio

• 51 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 2 (literal)

Rivista

• Frontiers in Cell and Developmental Biology (Rivista)

Note

• ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Istituto per le Applicazioni del Calcolo \"M. Picone\" - CNR Napoli, Italy ; Computational and Biology Open Laboratory (ComBOlab) Napoli, Italy. Computational and Biology Open Laboratory (ComBOlab) Napoli, Italy ; Institute of Genetics and Biophysics \"A. Buzzati-Traverso\" - CNR Napoli, Italy. (literal)

Titolo

• Understanding gene regulatory mechanisms by integrating ChIP-seq and RNA-seq data: statistical solutions to biological problems. (literal)

Abstract

• The availability of omic data produced from international consortia, as well as from worldwide laboratories, is offering the possibility both to answer long-standing questions in biomedicine/molecular biology and to formulate novel hypotheses to test. However, the impact of such data is not fully exploited due to a limited availability of multi-omic data integration tools and methods. In this paper, we discuss the interplay between gene expression and epigenetic markers/transcription factors. We show how integrating ChIP-seq and RNA-seq data can help to elucidate gene regulatory mechanisms. In particular, we discuss the two following questions: (i) Can transcription factor occupancies or histone modification data predict gene expression? (ii) Can ChIP-seq and RNA-seq data be used to infer gene regulatory networks? We propose potential directions for statistical data integration. We discuss the importance of incorporating underestimated aspects (such as alternative splicing and long-range chromatin interactions). We also highlight the lack of data benchmarks and the need to develop tools for data integration from a statistical viewpoint, designed in the spirit of reproducible research. (literal)

Prodotto di

• Istituto per le applicazioni del calcolo \"Mauro Picone\" (IAC) (Istituto)
• Plasticità genomica: dal genoma ai sistemi biologici (SV.P13.003.001) (Modulo)
• Istituto di genetica e biofisica \"Adriano Buzzati Traverso\" (IGB) (Istituto)
• Algoritmi Statistici orientati al grid computing per la genetica (INT.P02.004.001) (Modulo)

Autore CNR

• VALERIO COSTA (Unità di personale interno)
• CLAUDIA ANGELINI (Unità di personale interno)

Incoming links:

Prodotto

• Istituto per le applicazioni del calcolo \"Mauro Picone\" (IAC) (Istituto)
• Istituto di genetica e biofisica \"Adriano Buzzati Traverso\" (IGB) (Istituto)
• Algoritmi Statistici orientati al grid computing per la genetica (INT.P02.004.001) (Modulo)
• Plasticità genomica: dal genoma ai sistemi biologici (SV.P13.003.001) (Modulo)

Autore CNR di

• CLAUDIA ANGELINI (Unità di personale interno)
• VALERIO COSTA (Unità di personale interno)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Frontiers in Cell and Developmental Biology (Rivista)