Arabidopsis bioinformatics: tools and strategies.

Autor: Cantó-Pastor A; Department of Plant Biology and Genome Center, University of California Davis, 1 Shields Avenue, Davis, CA, 95616, USA., Mason GA; Department of Plant Biology and Genome Center, University of California Davis, 1 Shields Avenue, Davis, CA, 95616, USA., Brady SM; Department of Plant Biology and Genome Center, University of California Davis, 1 Shields Avenue, Davis, CA, 95616, USA., Provart NJ; Department of Cell and Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, 25 Willcocks Street, Toronto, ON, M5S 3B2, Canada.
Jazyk: angličtina
Zdroj: The Plant journal : for cell and molecular biology [Plant J] 2021 Dec; Vol. 108 (6), pp. 1585-1596. Date of Electronic Publication: 2021 Nov 09.
DOI: 10.1111/tpj.15547
Abstrakt: The sequencing of the Arabidopsis thaliana genome 21 years ago ushered in the genomics era for plant research. Since then, an incredible variety of bioinformatic tools permit easy access to large repositories of genomic, transcriptomic, proteomic, epigenomic and other '-omic' data. In this review, we cover some more recent tools (and highlight the 'classics') for exploring such data in order to help formulate quality, testable hypotheses, often without having to generate new experimental data. We cover tools for examining gene expression and co-expression patterns, undertaking promoter analyses and gene set enrichment analyses, and exploring protein-protein and protein-DNA interactions. We will touch on tools that integrate different data sets at the end of the article.
(© 2021 Society for Experimental Biology and John Wiley & Sons Ltd.)
Databáze: MEDLINE
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