semantic technologies

AI4GH Seminar Series - Large-scale Text and Data Integration for Cancer Genomics Research

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B19 L3 H2

Prof. Rebholz-Schuhmann has long-term experience in semantics driven data analytics research, as well in life sciences as in other domains.

Large-scale Text and Data Integration for Cancer Genomics Research

Prof. D, Rebholz-Schuhmann (University Cologne, Germany​)​

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B19 L3 H2

Abstract This talk will give an overview of data and text mining in the life science domain, but will also point out the use of semantic technologies for other domains. Such solutions cover the integration of heterogeneous data sources based on Semantic Web standards (e.g., TCGA, Cosmic, others), the development of smart technologies (e.g., stream processing), graph and literature analytics, and open data initiatives. Application domains are biomedical solutions in cancer genomics and targeted projects together with industrial partners exploiting Semantic Web technologies in general. The

Accelerating biomedical discovery with an Internet of FAIR data and services

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B9 L2 H1 R2322

In this talk, I will discuss our work to create computational standards, platforms, and methods to wrangle knowledge into simple, but effective representations based on semantic web technologies that are maximally FAIR - Findable, Accessible, Interoperable, and Reuseable - and to further use these for biomedical knowledge discovery. But only with additional crucial developments will this emerging Internet of FAIR data and services enable automated scientific discovery on a global scale.

Patrick Westphal

Visiting Student, Bio-Ontology Research Group
Patrick Westphal was a visiting student at Professor Robert Hoehndorf's Bio-Ontology Research Group (BORG) at King Abdullah University of Science and Technology (KAUST). During his three months (Jan 2016 – Mar 2016) internship at the Computational Bioscience Research Center (CBRC), he worked with the Bio-Ontology Research Group where he contributed to different projects aiming at finding correlations and causalities in relations between genotypes and phenotypes, and genes, diseases, and drugs. The applied techniques were usually backed by OWL ontologies or knowledge bases expressed in other