ASIH09 workshop

Abstracts

A Gentle Introduction to Ontologies for Biology

Hilmar Lapp (1), Todd J. Vision (1,2)

1 US National Evolutionary Synthesis Center, Durham, North Carolina, USA 2 University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

As biology has become increasingly data-rich, the reliance on databases and computation to integrate and mine the vast body of knowledge traditionally reported in the literature has grown dramatically. This has inspired the development of computational technologies to allow the exploration and linking of diverse types of data across biological databases at unprecedented scales. One of the most important technologies is an “ontology”, a hierarchically structured, controlled vocabulary of well-defined terms and the logical relationships that hold between them. Ontologies have been applied with tremendous success to transform scientific results traditionally reported as free text into a digital representation that is unambiguous, uniform across disciplines, and readily computable. For example, ontologies of biochemical functions and biological processes are used to unambiguously record what is known about a gene's function. Anatomy ontologies are now being used to unequivocally describe the morphological characteristics visible in a specimen image. Efforts (including two in ichthyology and herpetology) are underway to develop ontologies that will ultimately span the breadth of biological knowledge, which will have a profound impact on the way that biologists interact with data collections in the future. In order to be useful community resources, ontologies must accurately capture the state of biological knowledge, which requires that the biological community through their experts play an active role in their development. Here, I will provide a beginner’s guide to the world of ontologies and offer a roadmap for how biologists can best take advantage of, and contribute to, the growing suite of bio-ontology resources.

Phenoscape: Using Ontologies to Link Comparative Morphology to Genes

Paula Mabee

University of South Dakota

[final version?] Decades of comparative anatomical studies in ichthyology and herpetology have resulted in a rich body of ‘free-text’ data. As these data grow, they are increasingly hard to align and synthesize across taxonomic groups, and synthetic questions concerning the developmental and genetic basis of evolutionary changes in morphology cannot be easily or efficiently addressed. In order for this volume of comparative anatomical data to be analyzed in a developmental genetic context, it must first be rendered computable. One way to achieve this is to use ontologies. Using ostariophysan fishes as a prototype, the Phenoscape project has developed a system that includes ontologies representing expert knowledge of anatomy and taxonomy (the Teleost Anatomy Ontology and the Teleost Taxonomy Ontology), software for data curation (Phenex), and a knowledgebase that supports ontology-based reasoning about evolutionary phenotype data (PhenoscapeKB, http://phenoscape.org/kb). To date, over 5,000 characters from the phylogenetic literature have been annotated for 8,300 species, resulting in over eight million annotated phenotypes. PhenoscapeKB combines these evolutionary phenotypes with information about genetically characterized phenotype from ZFIN, the zebrafish community database. Through ontology-based reasoning over expert knowledge in taxonomy, comparative anatomy and developmental genetics, PhenoscapeKB can be used to address a host of questions spanning the domains of genetics, development and evolutionary biology, such as the nature of the genetic changes underlying phenotypic variation among taxa in nature.

Anne Maglia (1) Presenting Jennifer Leopold (1) Susan Gauch (2) Analia Pugener (1) (1) Missouri University of Science and Technology, Rolla, MO, United States (2) University of Arkansas, Fayetteville, AR, United States

Development of an Anatomical Ontology for Amphibians

Herein, we describe our ongoing efforts to develop a robust ontology for amphibian anatomy (www.amphibanat.org) that accommodates the diversity of anatomical structures present in the group. We discuss the design and implementation of the project, current resolutions to issues we have encountered, and future enhancements to the ontology. We also comment on efforts to integrate other data sets with the amphibian anatomical ontology.

Marc Robinson-Rechavi Bgee: Integrating ontology and homology for the study of gene expression evolution

Abstract

The study of the evolution of developmental processes (evo-devo) has shown that the primary source of change in the evolution of phenotypes is changes in gene expression. Comparing gene expression patterns between animals thus is a major step to understand their evolution. This approach requires dedicated bioinformatics tools to perform high throughput analyses. Thus we have developed Bgee, a database designed to compare expression patterns between animals, by implementing ontologies describing anatomies and developmental stages of species, and then designing homology relationships between anatomies and comparison criteria between developmental stages. To define homology relationships between anatomical features we have developed the software Homolonto, which uses a modified ontology alignment approach to propose homology relationships between ontologies. Bgee then uses these aligned ontologies, onto which heterogeneous expression data types are mapped. These include microarrays, in situ hybridization, and ESTs, from human, mouse, xenopus and zebrafish. Bgee is available at http://bgee.unil.ch/