Integrative omics - from data to biology

2018 | journal article; research paper. A publication with affiliation to the University of Göttingen.

Jump to: Cite & Linked | Documents & Media | Details | Version history

Cite this publication

​Integrative omics - from data to biology​
Dihazi, H.; Asif, A. R; Beißbarth, T. ; Bohrer, R.; Feussner, K.; Feussner, I. & Jahn, O.  et al.​ (2018) 
Expert Review of Proteomics15(6) pp. 463​-466​.​ DOI: https://doi.org/10.1080/14789450.2018.1476143 

Documents & Media

License

GRO License GRO License

Details

Authors
Dihazi, Hassan; Asif, Abdul R; Beißbarth, Tim ; Bohrer, Rainer; Feussner, Kirstin; Feussner, Ivo; Jahn, Olaf ; Lenz, Christof; Majcherczyk, Andrzej; Schmidt, Bernhard; Schmitt, Kerstin; Urlaub, Henning; Valerius, Oliver
Abstract
Multi-omic approaches are promising a broader view on cellular processes and a deeper understanding of biological systems. with strongly improved high-throughput methods the amounts of data generated have become huge, and their handling challenging. Area Covered: New bioinformatic tools and pipelines for the integration of data from different omics disciplines continue to emerge, and will support scientists to reliably interpret data in the context of biological processes. comprehensive data integration strategies will fundamentally improve systems biology and systems medicine. to present recent developments of integrative omics, the göttingen proteomics forum (gpf) organized its 6th symposium on the 23rd of november 2017, as part of a series of regular gpf symposia. more than 140 scientists attended the event that highlighted the challenges and opportunities but also the caveats of integrating data from different omics disciplines. Expert commentary: The continuous exponential growth in omics data require similar development in software solutions for handling this challenge. Integrative omics tools offer the chance to handle this challenge but profound investigations and coordinated efforts are required to boost this field.
Issue Date
2018
Journal
Expert Review of Proteomics 
Organization
Gesellschaft für wissenschaftliche Datenverarbeitung 
ISSN
1478-9450; 1744-8387
eISSN
1744-8387
Language
English

Reference

Citations


Social Media