Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB)

Rasmus Krempel , Pranav Kulkarni , Annie Yim (1) , Ulrich Lang (2) , Bianca Habermann (3) , Peter Frommolt (4)

1 Computational Biology Group [Martinsried, Germany]
2 Ingenieurgesellschaft Prof. Kobus und Partner GmbH
3 Computational Biology Group [Martinsried, Germany]
4 Cologne Center for Genomics

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.

Domaines: Sciences du Vivant [q-bio]

Rasmus Krempel, Pranav Kulkarni, Annie Yim, Ulrich Lang, Bianca Habermann, et al.. Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB). BMC Bioinformatics, 2018, 19 (1), ⟨10.1186/s12859-018-2157-7⟩. ⟨hal-02017637⟩