Universität zu Köln

Krempel, Rasmus, Kulkarni, Pranav, Yim, Annie, Lang, Ulrich ORCID: 0000-0001-7166-0805, Habermann, Bianca ORCID: 0000-0002-2457-7504 and Frommolt, Peter ORCID: 0000-0002-1966-8014 (2018). Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB). BMC Bioinformatics, 19. LONDON: BIOMED CENTRAL LTD. ISSN 1471-2105

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Abstract

Background: Recent cancer genome studies on many human cancer types have relied on multiple molecular high-throughput technologies. Given the vast amount of data that has been generated, there are surprisingly few databases which facilitate access to these data and make them available for flexible analysis queries in the broad research community. If used in their entirety and provided at a high structural level, these data can be directed into constantly increasing databases which bear an enormous potential to serve as a basis for machine learning technologies with the goal to support research and healthcare with predictions of clinically relevant traits. Results: We have developed the Cancer Systems Biology Database (CancerSysDB), a resource for highly flexible queries and analysis of cancer-related data across multiple data types and multiple studies. The CancerSysDB can be adopted by any center for the organization of their locally acquired data and its integration with publicly available data from multiple studies. A publicly available main instance of the CancerSysDB can be used to obtain highly flexible queries across multiple data types as shown by highly relevant use cases. In addition, we demonstrate how the CancerSysDB can be used for predictive cancer classification based on whole-exome data from 9091 patients in The Cancer Genome Atlas (TCGA) research network. Conclusions: Our database bears the potential to be used for large-scale integrative queries and predictive analytics of clinically relevant traits.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Krempel, Rasmus UNSPECIFIED UNSPECIFIED UNSPECIFIED Kulkarni, Pranav UNSPECIFIED UNSPECIFIED UNSPECIFIED Yim, Annie UNSPECIFIED UNSPECIFIED UNSPECIFIED Lang, Ulrich UNSPECIFIED orcid.org/0000-0001-7166-0805 UNSPECIFIED Habermann, Bianca UNSPECIFIED orcid.org/0000-0002-2457-7504 UNSPECIFIED Frommolt, Peter UNSPECIFIED orcid.org/0000-0002-1966-8014 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-189099
DOI:	10.1186/s12859-018-2157-7
Journal or Publication Title:	BMC Bioinformatics
Volume:	19
Date:	2018
Publisher:	BIOMED CENTRAL LTD
Place of Publication:	LONDON
ISSN:	1471-2105
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Mathematics and Computer Science > Mathematical Institute
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language SUCCINYL-COA SYNTHETASES; RENAL-CELL CARCINOMA; P53 MUTATIONS; EXPRESSION Multiple languages Biochemical Research Methods; Biotechnology & Applied Microbiology; Mathematical & Computational Biology Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/18909