@conference {ICBO_2018_52, title = {ICBO_2018_52: The integrative use of anatomy ontology and protein-protein interaction networks to study evolutionary phenotypic transitions}, booktitle = {International Conference on Biomedical Ontology (ICBO 2018)}, series = {Proceedings of the International Conference on Biological Ontology (2018)}, year = {2018}, month = {08/06/2018}, publisher = {International Conference on Biological Ontology}, organization = {International Conference on Biological Ontology}, abstract = {

Studying evolutionary phenotypic transitions, such as the fin to limb transition, is popular in evolutionary biology. The recent advances in next-generation technologies have accumulated large volumes of genomics and proteomics data, which can be used to analyze the genetic basis for evolutionary phenotypic transitions. Protein-protein interaction (PPI) networks can be used to predict candidate genes and identify gene modules related to evolutionary phenotypes; however, they suffer from low gene prediction accuracy. Therefore, an integrative framework was developed using PPI networks and anatomy ontology, which significantly improved the accuracy of network-based candidate gene predictions in zebrafish and mouse. This integrative framework will also be used to identify gene modules associated with the fin to limb transition and to study the changes in these modules which lead to the phenotypic change.

}, keywords = {anatomy ontology, data integration, gene prediction, network analysis, protein-protein interactions}, url = {http://ceur-ws.org/Vol-2285/ICBO_2018_paper_52.pdf }, author = {Pasan Fernando and Erliang Zeng and Paula Mabee} } @conference {ICBO_2018_62, title = {ICBO_2018_62: Reasoning over anatomical homology in the Phenoscape KB}, booktitle = {International Conference on Biomedical Ontology (ICBO 2018)}, series = {Proceedings of the International Conference on Biological Ontology (2018)}, year = {2018}, month = {08/06/2018}, publisher = {International Conference on Biological Ontology}, organization = {International Conference on Biological Ontology}, abstract = {

The Phenoscape project (www.phenoscape.org) has semantically annotated the features of species from the comparative literature, enabling links between candidate genes and novel species phenotypes for which they might be responsible. To enable discovery of homologous phenotypes and associated genes, we incorporated machine-reasoning with knowledge about homology into the Phenoscape Knowledgebase (KB). We show that with homology reasoning enabled, the results of database queries can be expanded to incorporate shared evolutionary history. We discuss the challenges in developing a logical model of homology assertions and implications for database queries, as well as theoretical entailment and practical performance tradeoffs between alternative models.

}, keywords = {anatomy ontology, evolution, homology, phenotypes, reasoning}, url = {http://ceur-ws.org/Vol-2285/ICBO_2018_paper_62.pdf }, author = {Paula Mabee and James Balhoff and Wasila Dahdul and Hilmar Lapp and Christopher Mungall and Todd Vision} }