| Literature DB >> 35524132 |
Thomas Denecker1, Gaëlle Lelandais2.
Abstract
Omics data are very valuable for researchers in biology, but the work required to develop a solid expertise in their analysis contrasts with the rapidity with which the omics technologies evolve. Data accumulate in public databases, and despite significant advances in bioinformatics softwares to integrate them, data analysis remains a burden for those who perform experiments. Beyond the issue of dealing with a very large number of results, we believe that working with omics data requires a change in the way scientific problems are solved. In this chapter, we explain pitfalls and tips we found during our functional genomics projects in yeasts. Our main lesson is that, if applying a protocol does not guarantee a successful project, following simple rules can help to become strategic and intentional, thus avoiding an endless drift into an ocean of possibilities.Entities:
Keywords: Analysis cycle; Data; Information; Knowledge; Omics; Visualization
Mesh:
Year: 2022 PMID: 35524132 DOI: 10.1007/978-1-0716-2257-5_25
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745