Literature DB >> 18294967

Predicting biological networks from genomic data.

Eoghan D Harrington1, Lars J Jensen, Peer Bork.   

Abstract

Continuing improvements in DNA sequencing technologies are providing us with vast amounts of genomic data from an ever-widening range of organisms. The resulting challenge for bioinformatics is to interpret this deluge of data and place it back into its biological context. Biological networks provide a conceptual framework with which we can describe part of this context, namely the different interactions that occur between the molecular components of a cell. Here, we review the computational methods available to predict biological networks from genomic sequence data and discuss how they relate to high-throughput experimental methods.

Mesh:

Year:  2008        PMID: 18294967     DOI: 10.1016/j.febslet.2008.02.033

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  19 in total

Review 1.  Emerging methods in protein co-evolution.

Authors:  David de Juan; Florencio Pazos; Alfonso Valencia
Journal:  Nat Rev Genet       Date:  2013-03-05       Impact factor: 53.242

Review 2.  Structural bioinformatics of the interactome.

Authors:  Donald Petrey; Barry Honig
Journal:  Annu Rev Biophys       Date:  2014       Impact factor: 12.981

Review 3.  Linking Genes to Cardiovascular Diseases: Gene Action and Gene-Environment Interactions.

Authors:  Ares Pasipoularides
Journal:  J Cardiovasc Transl Res       Date:  2015-11-06       Impact factor: 4.132

4.  Evolutionary plasticity determination by orthologous groups distribution.

Authors:  Rodrigo J S Dalmolin; Mauro A A Castro; José L Rybarczyk Filho; Luis H T Souza; Rita M C de Almeida; José C F Moreira
Journal:  Biol Direct       Date:  2011-05-17       Impact factor: 4.540

5.  Selection of organisms for the co-evolution-based study of protein interactions.

Authors:  Dorota Herman; David Ochoa; David Juan; Daniel Lopez; Alfonso Valencia; Florencio Pazos
Journal:  BMC Bioinformatics       Date:  2011-09-12       Impact factor: 3.169

6.  Sequence-based feature prediction and annotation of proteins.

Authors:  Agnieszka S Juncker; Lars J Jensen; Andrea Pierleoni; Andreas Bernsel; Michael L Tress; Peer Bork; Gunnar von Heijne; Alfonso Valencia; Christos A Ouzounis; Rita Casadio; Søren Brunak
Journal:  Genome Biol       Date:  2009-02-02       Impact factor: 13.583

7.  Novel protein-protein interactions inferred from literature context.

Authors:  Herman H H B M van Haagen; Peter A C 't Hoen; Alessandro Botelho Bovo; Antoine de Morrée; Erik M van Mulligen; Christine Chichester; Jan A Kors; Johan T den Dunnen; Gert-Jan B van Ommen; Silvère M van der Maarel; Vinícius Medina Kern; Barend Mons; Martijn J Schuemie
Journal:  PLoS One       Date:  2009-11-18       Impact factor: 3.240

8.  Effect of reference genome selection on the performance of computational methods for genome-wide protein-protein interaction prediction.

Authors:  Vijaykumar Yogesh Muley; Akash Ranjan
Journal:  PLoS One       Date:  2012-07-26       Impact factor: 3.240

9.  Gene network homology in prokaryotes using a similarity search approach: queries of quorum sensing signal transduction.

Authors:  David N Quan; William E Bentley
Journal:  PLoS Comput Biol       Date:  2012-08-16       Impact factor: 4.475

10.  Computational prediction of protein-protein interactions in Leishmania predicted proteomes.

Authors:  Antonio M Rezende; Edson L Folador; Daniela de M Resende; Jeronimo C Ruiz
Journal:  PLoS One       Date:  2012-12-10       Impact factor: 3.240

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