Looking at cerebellar malformations through text-mined interactomes of mice and humans.

• Main Authors: Ivan Iossifov, Raul Rodriguez-Esteban, Ilya Mayzus, Kathleen J Millen, Andrey Rzhetsky
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2009-11-01
• Series: PLoS Computational Biology
• Online Access: http://europepmc.org/articles/PMC2767227?pdf=render
• ISSN: 1553-734X; 1553-7358

We have generated and made publicly available two very large networks of molecular interactions: 49,493 mouse-specific and 52,518 human-specific interactions. These networks were generated through automated analysis of 368,331 full-text research articles and 8,039,972 article abstracts from the PubMed database, using the GeneWays system. Our networks cover a wide spectrum of molecular interactions, such as bind, phosphorylate, glycosylate, and activate; 207 of these interaction types occur more than 1,000 times in our unfiltered, multi-species data set. Because mouse and human genes are linked through an orthological relationship, human and mouse networks are amenable to straightforward, joint computational analysis. Using our newly generated networks and known associations between mouse genes and cerebellar malformation phenotypes, we predicted a number of new associations between genes and five cerebellar phenotypes (small cerebellum, absent cerebellum, cerebellar degeneration, abnormal foliation, and abnormal vermis). Using a battery of statistical tests, we showed that genes that are associated with cerebellar phenotypes tend to form compact network clusters. Further, we observed that cerebellar malformation phenotypes tend to be associated with highly connected genes. This tendency was stronger for developmental phenotypes and weaker for cerebellar degeneration.