Section: New Results

Distributed Protein Graph Processing

The huge number of protein sequences in protein databases such as UniProtKB calls for rapid procedures to annotate them automatically. We are using existing protein annotations to predict the annotations of new or non-reviewed proteins. In this context, we developed the “DistNBLP” method for annotating protein sequences using a graph representation and a distributed label propagation algorithm. DistNBLP uses the BLADYG framework [38] to process protein graphs on multiple compute nodes by applying a neighbourhood-based label propagation algorithm in a distributed way. We applied DistNBLP in the recent “CAFA 3” (critical Assessment of Protein Function Annotation) community experiment to annotate new protein sequences automatically. This work was presented as a poster at ISMB/ECCB-2017 [34]. We are also interested in feature selection for subgraph patterns. In collaboration with the LIMOS laboratory at Université Clermont Auvergne we also developed a scalable approach using MapReduce for identifying sub-graphs having similar labels in very large graphs [51].