Abstract: Functionally altered biological mechanisms arising from disease-associated polymorphisms remain difficult to characterize when those variants are intergenic, or, fall between genes. The present invention uses computational modelling of single-nucleotide polymorphisms (SNPs) drawn from genome-wide association studies (GWAS) or other databases to identify SNP pairs, including SNP pairs where at least one SNP is outside a protein-coding region of a gene, having convergent biological mechanisms. Additional databases, including genomic databases, biological regulatory databases, and databases related to molecular function, are used to further identify and validate the similarity of the biological mechanisms of the SNP pairs. Prioritized SNP pairs having increased similarity of biological mechanisms are then used to identify disease mechanisms, candidate therapeutic drugs, and candidate therapeutic targets among downstream effectors of intergenic SNPs.

Abstract: Systems and methods for extracting and encoding genotype-phenotype information from journal articles and other publications are provided. In some embodiments, the disclosed subject matter includes a preprocessor, boundary identifier, parser, phrase recognizer and an encoder to convert natural-language input text and parameters into structured text. The structured text can take the form of codes which account for genotype-phenotype information and are compatible with a controlled vocabulary.

Abstract: A method for creating an amalgamated bioinformatics database from at least a first database and a second database is presented. Concepts are identified in a first field from the records of the first database. A second field from the records of the second database which has data related to the first field is also identified. A first set of concepts is identified by traversing a mediating database using terms associated with the first field and a second set of concepts is also identified by traversing the mediating database using terms associated with the second field. Either the first set of concepts or the second set of concepts, or both, is identified using non-trivial terminological mapping. The set of related concepts in the first set of concepts and the second set of concepts is identified and a record is generated in the amalgamated bioinformatics database.

Abstract: A method for creating an amalgamated bioinformatics database from at least a first database and a second database is presented. Concepts are identified in a first field from the records of the first database. A second field from the records of the second database which has data related to the first field is also identified. A first set of concepts is identified by traversing a mediating database using terms associated with the first field and a second set of concepts is also identified by traversing the mediating database using terms associated with the second field. Either the first set of concepts or the second set of concepts, or both, is identified using non-trivial terminological mapping. The set of related concepts in the first set of concepts and the second set of concepts is identified and a record is generated in the amalgamated bioinformatics database.

Abstract: The present invention relates to the systematic use of terminology and knowledge based technologies to enable high-throughput mapping between databases having different vocabularies. In particular embodiments, it may be used to map between a database having a phenotypic terminology descriptive of non-human animals and a database having a broad-coverage clinical (anthropocentric) terminology.