A National Center for Biotechnology Information team outlines improvements to the Virus Variation Resource, a database that currently houses sequences representing seven new and previously available viral modules. The resource is equipped with pipelines to bring together GenBank sequence data for the seven viral groups, the researchers say, while providing opportunities to annotate these genomes, align multiple sequences, develop phylogenetic tress, and do additional types of standardized analyses. "The resource now includes expanded data processing pipelines and analysis tools," they write, "and supports selection and retrieval of nucleotide and protein sequences from four new viral groups: Ebolaviruses, MERS coronavirus, rotavirus, and Zika virus."
Investigators from Harbin Medical University in China present a computational strategy for classifying somatic mutations in cancer, both in terms of their broader genetic context and predicted functional effects. The team applied this so-called "hallmark-associated cooperation under specific genetic context," or HCOC, approach to analyze expression, mutation, and copy number data for 3,753 tumors from a dozen cancer types assessed through the Cancer Genome Atlas project, revealing almost 1,200 cooperative genomic alteration events. When they took a closer look at almost two dozen cooperative events that were identified in glioblastoma tumors, for example, the researchers saw hints that such analyses can help classify patients into prognostically informative groups and/or identify events that tend to accompany driver gene mutations.
Researchers from the National Center for Advancing Translational Science, the University of New Mexico, and elsewhere describe resources developed through the "Illuminating the Druggable Genome" group's effort to tally protein targets that might be susceptible to drug treatment. In particular, the team focused on two related resources: the National Institutes of Health resource Pharos and the Target Central Resource Database (TCRD), which brings together gene and protein datasets that can be accessed through Pharos. "Given the wide variety of data types collected by TCRD," the authors note, "effective access and presentation via Pharos enables users to find what they want, but also point users in the direction of related, possibly relevant information that they may not have considered initially."