Finding genetic variants that predispose and regulate brain-related disorders has become a significant area of neuroscience research. However, limited success has been achieved with mental disorders such as autism, partly due to the difficulty in identifying endophenotypes, or intermediate phenotypes, of the disorder. Phenomics - the systematic cataloging of phenotypes on a genome-wide scale - has emerged as a scientific endeavor within psychiatric genetics to address this challenge. A limitation to the advancement of phenomics, however, is the lack of available methods and tools for modeling, managing, and reasoning about endophenotypes. This project will develop the Phenologue, a novel knowledge-based technology that can support collaborative efforts to acquire, manage, and reason about a disease phenome given experimental data and published findings. Among the project's research objectives are to develop an ontology of endophenotypes that maps brain connectivity, neural deficits, and genetic markers to develop logic-based methods to encode and classify endophenotypes, and to create tools to acquire new endophenotypes and annotate phenotype-genotype findings in online resources such as published literature. The research will help develop an autism ontology for the National Database for Autism Research (NDAR).