The DOI matches its Crossref record; 147 of the 147 references it cites were found in a registry or an index.
Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences
Open accessAbstract
Advances in the technologies and informatics used to generate and process large biological data sets (omics data) are promoting a critical shift in the study of biomedical sciences. While genomics, transcriptomics and proteinomics, coupled with bioinformatics and biostatistics, are gaining momentum, they are still, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. As other areas of biomedical sciences, including metabolomics, epigenomics and pharmacogenomics, are moving towards the omics scale, we are witnessing the rise of inter-disciplinary data integration strategies to support a better understanding of biological systems and eventually the development of successful precision medicine. This review cuts across the boundaries between genomics, transcriptomics and proteomics, summarizing how omics data are generated, analysed and shared, and provides an overview of the current strengths and weaknesses of this global approach. This work intends to target students and researchers seeking knowledge outside of their field of expertise and fosters a leap from the reductionist to the global-integrative analytical approach in research.
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Metadata
- Authors
- Manzoni, C., Kia, D. A., Vandrovcova, J., Hardy, J., Wood, N. W., Lewis, P. A., & Ferrari, R.
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-11-22
- Volume
- 19
- Issue
- 2
- Pages
- 286-302
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W2550535012
- Cited by
- 804
- References
- 147
- FWCI
- 15.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
- Funders
- Wellcome Trust (089698/Z/09/Z, 091673/Z/10/Z)
- MRC (WT089698)
- University of Sheffield
- Medical Research Council (MR/N026004/1, MR/L010933/1)
- University College London
- NIHR
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- Manzoni, C., Kia, D. A., Vandrovcova, J., Hardy, J., Wood, N. W., Lewis, P. A., & Ferrari, R. (2018). Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbw114
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
