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OMICtools: an informative directory for multi-omic data analysis
Open accessAbstract
Recent advances in 'omic' technologies have created unprecedented opportunities for biological research, but current software and database resources are extremely fragmented. OMICtools is a manually curated metadatabase that provides an overview of more than 4400 web-accessible tools related to genomics, transcriptomics, proteomics and metabolomics. All tools have been classified by omic technologies (next-generation sequencing, microarray, mass spectrometry and nuclear magnetic resonance) associated with published evaluations of tool performance. Information about each tool is derived either from a diverse set of developers, the scientific literature or from spontaneous submissions. OMICtools is expected to serve as a useful didactic resource not only for bioinformaticians but also for experimental researchers and clinicians. Database URL: http://omictools.com/.
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A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066
Microarray data analysis: from disarray to consolidation and consensus
Allison, D. B., Cui, X., Page, G. P., & Sabripour, M. (2006) · Nature Reviews Genetics · doi:10.1038/nrg1749 · Cited by 1,339
Mass spectrometry in high-throughput proteomics: ready for the big time
Nilsson, T., Mann, M., Aebersold, R., Yates, J. R., Bairoch, A., & Bergeron, J. J. M. (2010) · Nature Methods · doi:10.1038/nmeth0910-681 · Cited by 470
Vasilevsky, N. A., Brush, M. H., Paddock, H., Ponting, L., Tripathy, S. J., LaRocca, G. M., & Haendel, M. A. (2013) · PeerJ · doi:10.7717/peerj.148 · Cited by 271
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Abdelaal, T., Michielsen, L., Cats, D., Hoogduin, D., Mei, H., Reinders, M. J. T., & Mahfouz, A. (2019) · Genome Biology · doi:10.1186/s13059-019-1795-z · Cited by 628
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
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Rosati, E., Dowds, C. M., Liaskou, E., Henriksen, E. K. K., Karlsen, T. H., & Franke, A. (2017) · BMC Biotechnology · doi:10.1186/s12896-017-0379-9 · Cited by 322
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Robinson, E. K., Covarrubias, S., & Carpenter, S. (2020) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2019.194419 · Cited by 285
Metadata
- Authors
- Henry, V. J., Bandrowski, A. E., Pepin, A.-S., Gonzalez, B. J., & Desfeux, A.
- Venue
- Database
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-07-14
- Volume
- 2014
- Issue
- 0
- Pages
- bau069-bau069
- ISSN
- 1758-0463 (ISSN-L)
- OpenAlex
- W2135253885
- Cited by
- 240
- References
- 5
- FWCI
- 9.61
- Type
- journal article
- Language
- en
- Open access
- gold
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