The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Multi -omics and metabolic modelling pipelines: Challenges and tools for systems microbiology
Open accessAbstract
Integrated -omics approaches are quickly spreading across microbiology research labs, leading to (i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organization and (ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from -omics experiments. In this work, we present opportunities and challenges of multi -omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists.
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Beg, Q. K., Vazquez, A., Ernst, J., de Menezes, M. A., Bar-Joseph, Z., Barabási, A.-L., & Oltvai, Z. N. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609845104 · Cited by 368
The challenges of integrating multi-omic data sets
Palsson, B., & Zengler, K. (2010) · Nature Chemical Biology · doi:10.1038/nchembio.462 · Cited by 178
Chaibub Neto, E., Keller, M. P., Attie, A. D., & Yandell, B. S. (2010) · The Annals of Applied Statistics · doi:10.1214/09-aoas288 · Cited by 110
Integrative “Omics”-Approach Discovers Dynamic and Regulatory Features of Bacterial Stress Responses
Berghoff, B. A., Konzer, A., Mank, N. N., Looso, M., Rische, T., Förstner, K. U., Krüger, M., & Klug, G. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003576 · Cited by 54
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Toju, H., Peay, K. G., Yamamichi, M., Narisawa, K., Hiruma, K., Naito, K., Fukuda, S., Ushio, M., Nakaoka, S., Onoda, Y., et al. (2018) · Nature Plants · doi:10.1038/s41477-018-0139-4 · Cited by 1,077
Systems biology and multi-omics integration: viewpoints from the metabolomics research community
Pinu, F. R., Beale, D. J., Paten, A. M., Kouremenos, K., Swarup, S., Schirra, H. J., & Wishart, D. (2019) · Metabolites · doi:10.3390/metabo9040076 · Cited by 723
Integrated omics: tools, advances and future approaches
Misra, B. B., Langefeld, C., Olivier, M., & Cox, L. A. (2019) · Journal of Molecular Endocrinology · doi:10.1530/jme-18-0055 · Cited by 686
What Makes a Bacterial Species Pathogenic?:Comparative Genomic Analysis of the Genus Leptospira
Fouts, D. E., Matthias, M. A., Adhikarla, H., Adler, B., Amorim-Santos, L., Berg, D. E., Bulach, D., Buschiazzo, A., Chang, Y.-F., Galloway, R. L., et al. (2016) · PLOS Neglected Tropical Diseases · doi:10.1371/journal.pntd.0004403 · Cited by 317
Tan, B., Ng, C., Nshimyimana, J. P., Loh, L. L., Gin, K. Y.-H., & Thompson, J. R. (2015) · Frontiers in Microbiology · doi:10.3389/fmicb.2015.01027 · Cited by 297
Metadata
- Authors
- Fondi, M., & Liò, P.
- Venue
- Microbiological Research
- Publisher
- Elsevier BV
- Published
- 2015-02
- Volume
- 171
- Pages
- 52-64
- ISSN
- 0944-5013 (ISSN-L)
- OpenAlex
- W2950497661
- Cited by
- 165
- References
- 4
- FWCI
- 6.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
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