Predicting biological networks from genomic data

TY - JOUR

T1 - Predicting biological networks from genomic data

AU - Harrington, Eoghan D

AU - Jensen, Lars J

AU - Bork, Peer

PY - 2008

Y1 - 2008

N2 - 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.

AB - 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.

KW - Computational Biology

KW - Genomics

KW - Phylogeny

U2 - 10.1016/j.febslet.2008.02.033

DO - 10.1016/j.febslet.2008.02.033

M3 - Journal article

C2 - 18294967

SN - 0014-5793

VL - 582

SP - 1251

EP - 1258

JO - F E B S Letters

JF - F E B S Letters

IS - 8

ER -