Literature DB >> 29762088

An Updated Taxonomy and a Graphical Summary Tool for Optimal Classification and Comprehension of Omics Research.

Nina Pirih1, Tanja Kunej1.   

Abstract

The volume of publications and the type of research approaches used in omics system sciences are vast and continue to expand rapidly. This increased complexity and heterogeneity of omics data are challenging data extraction, sensemaking, analyses, knowledge translation, and interpretation. An extended and dynamic taxonomy for the classification and summary of omics studies are essential. We present an updated taxonomy for classification of omics research studies based on four criteria: (1) type and number of genomic loci in a research study, (2) number of species and biological samples, (3) the type of omics technology (e.g., genomics, transcriptomics, and proteomics) and omics technology application type (e.g., pharmacogenomics and nutrigenomics), and (4) phenotypes. In addition, we present a graphical summary approach that enables the researchers to define the main characteristics of their study in a single figure, and offers the readers to rapidly grasp the published study and omics data. We searched the PubMed and the Web of Science from 09/2002 to 02/2018, including research and review articles, and identified 90 scientific publications. We propose a call toward omics studies' standardization for reporting in scientific literature. We anticipate the proposed classification scheme will usefully contribute to improved classification of published reports in genomics and other omics fields, and help data extraction from publications for future multiomics data integration.

Keywords:  classification; environmental omics; epigenomics; genomics; integrated omics; interactomics; metabolomics; miRNomics/ncRNomics; omics science; phenome; phenomics; proteomics; taxonomy; transcriptomics

Mesh:

Year:  2018        PMID: 29762088     DOI: 10.1089/omi.2017.0186

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  3 in total

Review 1.  Genomic Predictors of Asthma Phenotypes and Treatment Response.

Authors:  Natalia Hernandez-Pacheco; Maria Pino-Yanes; Carlos Flores
Journal:  Front Pediatr       Date:  2019-02-05       Impact factor: 3.418

2.  Reproducible phenotype alteration due to prolonged cooling of the pupae of Polyommatus icarus butterflies.

Authors:  Gábor Piszter; Krisztián Kertész; Zsolt Endre Horváth; Zsolt Bálint; László Péter Biró
Journal:  PLoS One       Date:  2019-11-25       Impact factor: 3.240

3.  Integration and Visualization of Regulatory Elements and Variations of the EPAS1 Gene in Human.

Authors:  Aleša Kristan; Nataša Debeljak; Tanja Kunej
Journal:  Genes (Basel)       Date:  2021-11-13       Impact factor: 4.096

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.