Literature DB >> 11722287

Prediction of higher order functional networks from genomic data.

M Kanehisa1.   

Abstract

Post-genomics may be defined in different ways depending on how one views the challenges after the discovery of the genome. A traditional view is to follow the concept of the central dogma in molecular biology, namely from genome to transcriptome to proteome. Projects are ongoing to analyse gene expression profiles both at the mRNA and protein levels, and to catalogue protein 3D structure families, which will no doubt help the understanding of the information in the genome. However, once complete, such experimentally determined catalogues of genes, RNAs and proteins only tell us about the building blocks of life. They do not tell us much about how life operates as a system, such as higher order functional behaviours of the cell or the organism. Thus, an alternative view of post-genomics is to go up from the molecular level to the cellular level and eventually to still higher levels, i.e., the biological systems. Bioinformatics provides basic concepts as well as practical methods to integrate this view with the traditional view and to analyse complex interactions among building blocks and with dynamic environments.

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Year:  2001        PMID: 11722287     DOI: 10.1517/14622416.2.4.373

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  3 in total

1.  SIMCOMP/SUBCOMP: chemical structure search servers for network analyses.

Authors:  Masahiro Hattori; Nobuya Tanaka; Minoru Kanehisa; Susumu Goto
Journal:  Nucleic Acids Res       Date:  2010-05-11       Impact factor: 16.971

2.  Prior Biological Knowledge Improves Genomic Prediction of Growth-Related Traits in Arabidopsis thaliana.

Authors:  Muhammad Farooq; Aalt D J van Dijk; Harm Nijveen; Mark G M Aarts; Willem Kruijer; Thu-Phuong Nguyen; Shahid Mansoor; Dick de Ridder
Journal:  Front Genet       Date:  2021-01-20       Impact factor: 4.599

3.  Where Do We Stand in Regularization for Life Science Studies?

Authors:  Veronica Tozzo; Chloé-Agathe Azencott; Samuele Fiorini; Emanuele Fava; Andrea Trucco; Annalisa Barla
Journal:  J Comput Biol       Date:  2021-04-29       Impact factor: 1.479

  3 in total

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