Qaiser Mehmood

Date/Time: 11.05.2017, 09:00 

Location: D2.2.094 

Abstract

Next Generation Sequencing (NGS) is playing a vital role in the therapeutic decision making for the cancer prognosis and treatment. NGS technologies produces a massive amount of datasets from different publishers. Consequently, the process of sharing and aggregating this heterogenous datasets are thwarted by issues such as relevant data discovery, linking and querying. One of the key challenge in cancer genomics medicine is to discover the gene-disease-drug associations that enhance the development of new techniques tailored specific for an individual patient targeting prevention, diagnosis and treatment of the disease. We propose a semantically- interlinked platform called BIOOPENER that glues together heterogeneous cancer and biomedical repositories. The key approach is to discover, filling in missing links and querying these datasets to bring back the desired results. Since BIOOPENER works on top of graph data so investigating into best linking and optimized SPARQL query techniques are parts of this research work.

Bio

Qaiser Mehmood holds the MSc degree in computer engineering from Mid Sweden University, Sweden. He is a PhD student at Insight Centre for Data Analytics (formerly: Digital Enterpirse Research Insititute DERI), National University Of Ireland Galway Ireland. His research interests include Semantic Web, Query Federation, Data Cataloguing and Linking. As a PhD student his research work is mainly focused on SPARQL Property Paths and Graph mining.