A network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. We report the development of an information system that provides this network as a natural way of accessing the more than ten million abstracts in PubMed. By employing genes and proteins as hyperlinks between sentences and abstracts, we convert the information in PubMed into one navigable resource and bring all the advantages of the internet to scientific literature investigation. Moreover, this literature network can be superimposed upon experimental interaction data (e.g. yeast-two hybrid data from Drosophila and C.elegans) to make possible a simultaneous analysis of novel and existing knowledge. The network presented in iHOP contains half a million sentences and 30000 different genes from human, mouse, Drosophila, C. elegans, zebrafish, Arabidopsis, yeast and E. coli.