Abstract

1. Genome Genomics Knowledge Platform Biological Object Model Variome Regulome Transcriptome Proteome PathMaker Canvas Interactome Pharmacogenome Metabolome Physiome Pathome TNF, IL5, TNFRSF14, IL12B, IL12A, IL8, IL1B, IL4R, LTB, RAG1, TNFRSF6, TNFRSF17, APOE, TNFRSF7, TNFRSF4, TNFRSF9, TNFRSF5, F3, LTA GPB Integrated Annotation Large intestinal structure Organ with organ cavity Hollow viscus Intestines Signatures? Prevention? Treatment? Mechanisms? Biological Pathways Etiologies? Normal Cellular Function Network Representation Biological Explanation Mechanistic Explanation Novel Treatments Environment Disease Processes Genotype Biological Entities Biomedical Discovery Process Cognitive Processing (Researcher/Scientist Reasoning) PathBuilder Inborn Genetic Diseases Neoplasms Large Intestine Colon structure Region of large intestine Protein-Protein Interactions Ontologies Other Databases Sequence Databases Pathway Databases MedLine Protein Domains & 3D Structure Variation (SNPs) Ontology Explorer FANCG, NBS1, RB1, TP53, CDKN2A Hereditary Neoplastic Syndromes Colon Complex Builder Hereditary NonPolyposis Colon Cancer Gene Expression HNPCC (hMSH2, hMLH1, hPMS1, hPMS2) GO Clusterer PreBIND • 12 Siblings (UMLS – Concepts) • Adenomatous Polyposis Coli • Basal Cell Nevus Syndrome • Colorectal Neoplasms, Hereditary Nonpolyposis • Dysplastic Nevus Syndrome • Exostoses, Multiple Hereditary • Hamartoma Syndrome, Multiple • Li-Fraumeni Syndrome • Multiple Endocrine Neoplasia • Nephroblastoma • Neurofibromatoses • Peutz-Jeghers Syndrome • Sturge-Weber Syndrome GeneRIF Taxonomy Protein Interactions OMIM Gene Summary GKP Object HPRD Expert Curated Biological Entities Disease Ontology Anatomy Ontology Publishable Gene Molecule Map BioMaterial Ontologies An Integrative Approach for the Study of Sequence Variation Impact on Biological Processes, Diseases and Environmental Agents’ Risk Sivakumar Gowrisankar, Amol S Deshmukh, Anil G Jegga and Bruce J Aronow Department of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center and University of Cincinnati A Systems Biology Integrative Approach Abstract XPrInt: Extracting & Compiling Protein Interactions NIEHS Candidate Genes’ Categorization Based on GO (Biological Process) The integration of genomic sequence analyses from multiple species and strains, along with protein interaction data and gene expression profiles that reflect specific biological states and processes has opened many new avenues to understand specific biological systems. Nevertheless, formidable challenges remain to be overcome for the improvement of prediction, diagnosis, prognosis, and treatment of human diseases. Can we infer from large molecular datasets how different biological entities are organized and interact, and then predict the effect that genetic polymorphisms or sequence variations might confer on interconnected biological processes? The integration of heterogeneous data and information in fact is a key issue in functional genomics. An appropriate data model and consistent methods for its integrated representation, analysis, and visualization has the potential to pave the way for the emergence of discovery-driven science, enhance hypothesis-generation, and provide new focus for experimental validation and refinement. Thus, to represent the presence and impact of polymorphisms further in the context of biological pathways, we have sought to unify our representation of molecular, biological, and environmental entities such that biological knowledge from experts and biomedical literature could be assembled in a storyboard canvas. For example, the representation of a disease could consist of a biological process composed of one or more pathways, within which, entities (gene products, complexes, and cellular and subcellular components) are subjected to one or more interactions and transitions to disease term associated states. We have begun the development of a suite of applications using a common database structure that can represent biological processes using a host of publicly available data sources including gene objects and biological ontologies that in turn represent systematic abstractions of biomedical literature and expert knowledge. As part of this exercise, we have compiled all existing protein-protein interactions from “interactome” rich databases (PreBIND, MINT, DIP and HPRD) and mine the biomedical literature for novel interactions unrepresented in these specialized databases. Our compiled interactions data comply with the standards set out by Proteomics Standards Initiative (PSI) facilitating easy data exchange. As available annotations increase the challenge is to integrate biological process representation in such a way as to increase our understanding rather than obscure in convoluted figures or excessive detail. The use of a network visualizer provides not only a lucid means of summarizing existing biological knowledge about molecular behavior but also helps in elucidating the potential implications sequence variations can have on protein-protein interactions or the binding of specific transcription factors. Are these functionally clustered proteins involved in a common biological network or interaction? Co-citation in literature abstracts using gene/protein symbols and “interactome-specific” keywords Does a SNP in one or more biological entities result in aberrations within a pathway and manifest as a disease or contribute to increased susceptibility to disease or an altered response to therapeutic agents? GKP-PathMaker PatholoGene PatholoGene – Development of a system to link biological entities, anatomy, pathways and diseases using the UMLS Semantic Network, NCBI-OMIM and MedLine abstract parsing with ICD10 disease terms and gene symbols. The Semantic Network, through its semantic types, provides a categorization of all UMLS Metathesaurusconcepts. The links between the semantic types provide the structure for the Network and represent important relationships in the biomedical domain. The UMLS Metathesaurus contains information about biomedical concepts and terms from many controlled vocabularies and classifications used in patient records, bibliographic and full-text databases, and expert systems. As a test case we illustrate the analysis of colon cancer as a function of anatomy, pathology, etiology and disease progression. Future Directions Unified Representation of Disease States and Biological Processes using Clinical Phenotype, Molecular Signatures, and Genetic Attributes New Insights & Hypotheses Pathways and Processes-Centered Biomedical Knowledge Disease State B Patient-Centered Clinical Observations Disease State A Disease Process Modeling Tool Pathologene Report: Extracting relationships between disease, anatomy and genes. Therapeutic Intervention Analysis, Diagnosis and Prediction Sample-Centered Genetic and Genomic Data References & Support • XPrInt and PatholoGene: http://abstrainer.cchmc.org • UMLS Knowledge Source Server: http://umlsks.nlm.nih.gov • Open Biological Ontologies: http://obo.sourceforge.net • Support: NIEHS U01 ES11038 Mouse Centers Genomics Consortium