data integration

AI4GH Seminar Series | Predicting Protein Function and Phenotype Associations

Maxat Kulmanov, Research Scientist, Bio-Ontology Research Group

Oct 10, 12:00 - 13:00

B2 R5220

biology biomedicine artificial intelligence knowledge discovery data integration protein function prediction

The amount of available protein sequences is rapidly increasing, mainly as a consequence of the development and application of high throughput sequencing technologies in the life sciences.

AI4GH Seminar Series - Machine Learning with Biological Knowledge Graphs

Mona Alshahrani, Ph.D., Computer Science

Oct 24, 12:00 - 13:00

B2 R5220

bioinformatics data integration machine learning knowledge graphs human health

Abstract Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval, and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. We develop novel methods for feature learning on biological knowledge graphs and apply them to the prediction of edges in the knowledge graph representing problems of finding candidate genes of diseases, or drugs

Mona Alshahrani defends her thesis proposal

1 min read · Tue, Oct 16 2018

data integration machine learning human bioinformatics

Mona Alshahrani, a Ph.D. candidate under the supervision of Assistant Professor Robert Hoehndorf, defended her thesis proposal on October 10, 2018.

Senay Kafkas

Research Scientist, Bio-Ontology Research Group

data mining data integration information extraction named entity recognition bioinformatics

Research Interests Senay's research interests include biomedical text/data mining, Natural Language Processing (NLP), and Next Generation Sequencing (NGS) data analysis. Scientific and Professional Membership International Society of Computational Biology (ISCB) (2010-present). KAUST Affiliations Bio-Ontology Research Group (BORG). Computational Bioscience Research Center (CBRC). Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE). Education Profile Ph.D., Computer Engineering, Eastern Mediterranean University, Cyprus, 2012. M.Sc., Computer Engineering, Eastern

Mona Alshahrani

Ph.D., Computer Science

machine learning human bioinformatics data integration network-based approaches

Mona Alshahrani obtained her Ph.D. degree in Computer Science under the supervision of Professor Robert Hoehndorf at the Bio-Ontology Research Group (BORG) at King Abdullah University of Science and Technology (KAUST). Research Interests Machine Learning, human bioinformatics, data integration. The combination of neuro-symbolic methods over ontologies and semantic RDF graphs with statistical methods. Their applications in data analysis and features representations in several biomedical applications such as phenotypes prediction, drug repurposing, and others. I'm also interested in network