Network analyses of sperm-egg recognition and binding: ready to rethink fertility mechanisms?

ABSTRACT: The rapid growth of published literature makes biomedical text mining increasingly invaluable for unpacking implicit knowledge hidden in unstructured text. We employed biomedical text mining and biological networks analyses to research the process of sperm egg recognition and binding (SERB). We selected from the literature the molecules expressed either on spermatozoa or on oocytes thought to be involved in SERB and, using an automated literature search software (Agilent Literature Search), we realized a network, SERBN, characterized by a hierarchical scale free and a small world topology. We used an integrated approach, either based on selection of hubs or by a cluster analysis, to discern the key molecules of SERB. We found that in most cases some of them are not directly situated on spe

SUBMITTER: Bernabo N 

PROVIDER: S-EPMC4253145 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature