A rich genome-wide resource of mouse networks at the isoform level, which was generated using a unique framework that was originally developed to infer isoform functions. This network was built through integrating heterogeneous genomic and protein data, including RNA-seq, exon array, protein docking and pseudo-amino acid composition. Through simulation and cross-validation studies, we demonstrated the accuracy of the algorithm in predicting isoform-level functional relationships. We showed that this network enables the users to reveal functional differences of the isoforms of the same gene, as illustrated by literature evidence with Anxa6 (annexin a6) as an example.
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Institute for Systems Biology, Seattle, WA, USA; Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Electrical Engineering and Computer Science, Ann Arbor, MI, USA
Isoform Network funding source(s)
This work is supported by grants NSF CAREER 1452656, EU-FP VII Systems Biology of Rare Disease, the University of Michigan O’Brien Kidney Translational Core Center, and by U54ES017885 to the University of Michigan M-LEEaD Center.