Literature DB >> 21370077

Omics technologies, data and bioinformatics principles.

Maria V Schneider1, Sandra Orchard.   

Abstract

We provide an overview on the state of the art for the Omics technologies, the types of omics data and the bioinformatics resources relevant and related to Omics. We also illustrate the bioinformatics challenges of dealing with high-throughput data. This overview touches several fundamental aspects of Omics and bioinformatics: data standardisation, data sharing, storing Omics data appropriately and exploring Omics data in bioinformatics. Though the principles and concepts presented are true for the various different technological fields, we concentrate in three main Omics fields namely: genomics, transcriptomics and proteomics. Finally we address the integration of Omics data, and provide several useful links for bioinformatics and Omics.

Mesh:

Year:  2011        PMID: 21370077     DOI: 10.1007/978-1-61779-027-0_1

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  20 in total

Review 1.  Identification of aberrant pathways and network activities from high-throughput data.

Authors:  Jinlian Wang; Yuji Zhang; Catalin Marian; Habtom W Ressom
Journal:  Brief Bioinform       Date:  2012-01-27       Impact factor: 11.622

2.  Wavelet Screening identifies regions highly enriched for differentially methylated loci for orofacial clefts.

Authors:  William R P Denault; Julia Romanowska; Øystein A Haaland; Robert Lyle; Jack A Taylor; Zongli Xu; Rolv T Lie; Håkon K Gjessing; Astanand Jugessur
Journal:  NAR Genom Bioinform       Date:  2021-05-03

3.  Proteogenomics: emergence and promise.

Authors:  Sam Faulkner; Matthew D Dun; Hubert Hondermarck
Journal:  Cell Mol Life Sci       Date:  2015-01-22       Impact factor: 9.261

4.  Alterations in eicosanoid composition during embryonic development in the chorioallantoic membrane of the American alligator (Alligator mississippiensis) and domestic chicken (Gallus gallus).

Authors:  Theresa M Cantu; John A Bowden; Jacob Scott; Jimena B Pérez-Viscasillas; Kevin Huncik; Matthew P Guillette; Louis J Guillette
Journal:  Gen Comp Endocrinol       Date:  2016-07-09       Impact factor: 2.822

Review 5.  Transcriptomics and proteomics in stem cell research.

Authors:  Hai Wang; Qian Zhang; Xiangdong Fang
Journal:  Front Med       Date:  2014-06-27       Impact factor: 4.592

6.  Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example.

Authors:  Jaume Bacardit; Paweł Widera; Nicola Lazzarini; Natalio Krasnogor
Journal:  Big Data       Date:  2014-09-01       Impact factor: 2.128

7.  Sparse Bayesian classification and feature selection for biological expression data with high correlations.

Authors:  Xian Yang; Wei Pan; Yike Guo
Journal:  PLoS One       Date:  2017-12-27       Impact factor: 3.240

8.  The State of Data in Healthcare: Path Towards Standardization.

Authors:  Keith Feldman; Reid A Johnson; Nitesh V Chawla
Journal:  J Healthc Inform Res       Date:  2018-05-22

9.  Metadata harmonization-Standards are the key for a better usage of omics data for integrative microbiome analysis.

Authors:  Tomislav Cernava; Daria Rybakova; Michael Schloter; Gabriele Berg; François Buscot; Thomas Clavel; Alice Carolyn McHardy; Fernando Meyer; Folker Meyer; Jörg Overmann; Bärbel Stecher; Angela Sessitsch
Journal:  Environ Microbiome       Date:  2022-06-24

10.  Capacity Building of Health Professionals on Genetics and Genomics Practice: Evaluation of the Effectiveness of a Distance Learning Training Course for Italian Physicians.

Authors:  Giovanna Elisa Calabrò; Alessia Tognetto; Alfonso Mazzaccara; Donatella Barbina; Pietro Carbone; Debora Guerrera; Alessandra Di Pucchio; Antonio Federici; Walter Ricciardi; Stefania Boccia
Journal:  Front Genet       Date:  2021-03-15       Impact factor: 4.599

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