We are very pleased to announce that our group got a paper accepted at the Oxford Bioinformatics Journal.
Oxford Bioinformatics Journal is a bi-weekly peer-reviewed scientific journal that focuses on genome bioinformatics and computational biology. The journal is leading its field, and publishes scientific papers that are relevant to academic and industrial researchers.
Here is the pre-print of the accepted paper with its abstract:
- BioKEEN: A library for learning and evaluating biological knowledge graph embeddings by Mehdi Ali, Charles Tapley Hoyt, Daniel Domingo-Fernandez, Jens Lehmann, and Hajira Jabeen.
Abstract: Knowledge graph embeddings (KGEs) have received significant attention in other domains due to their ability to predict links and create dense representations for graphs’ nodes and edges. However, the software ecosystem for their application to bioinformatics remains limited and inaccessible for users without expertise in programming and machine learning. Therefore, we developed BioKEEN (Biological KnowlEdge EmbeddiNgs) and PyKEEN (Python KnowlEdge EmbeddiNgs) to facilitate their easy use through an interactive command line interface. Finally, we present a case study in which we used a novel biological pathway mapping resource to predict links that represent pathway crosstalks and hierarchies. Availability: BioKEEN and PyKEEN are open source Python packages publicly available under the MIT License at https://github.com/SmartDataAnalytics/BioKEEN and https://github.com/SmartDataAnalytics/PyKEEN as well as through PyPI.
Acknowledgement
We thank our partners from the Bio2Vec, MLwin, and SimpleML projects for their assistance. This research was supported by Bio2Vec project (http://bio2vec.net/, CRG6 grant 3454) with funding from King Abdullah University of Science and Technology (KAUST).