Running summarizing tools on a new article

Abstract: One of the major challenges and opportunities for protein function prediction is how to integrate diverse function-relevant biological data, such as protein sequences, protein function annotations, spatial gene-gene interactions, and protein-protein interactions, to improve the accuracy of protein function prediction. Given a target protein sequence, our method generated an initial list of Gene Ontology (GO) function terms based on the known function annotations of the homologous proteins found by PSI-BLAST, the set of GO terms were then expanded according to the association rules between GO terms learned by mining the SWISS-Prot database, and finally the GO terms were further augmented by the function annotations of the neighboring proteins of the target protein found in protein-protein interaction networks of 23 species and the novel spatial gene-gene interaction networks of the human genome constructed from the Hi-C chromosomal conformation data of the genome. The individual probabilistic scores of these GO terms derived from these different sources were statistically combined into final scores to rank them. The GO terms ranked at top were then used as the function prediction of the target protein.