PMC:3990764 / 1660-4333 JSONTXT

{"project":"2_test","denotations":[{"id":"24748859-12404162-44838000","span":{"begin":136,"end":137},"obj":"12404162"},{"id":"24748859-17663424-44838001","span":{"begin":139,"end":140},"obj":"17663424"},{"id":"24748859-19017771-44838002","span":{"begin":366,"end":367},"obj":"19017771"},{"id":"24748859-12723012-44838003","span":{"begin":559,"end":560},"obj":"12723012"},{"id":"24748859-22540250-44838004","span":{"begin":870,"end":871},"obj":"22540250"},{"id":"24748859-9082131-44838005","span":{"begin":994,"end":995},"obj":"9082131"},{"id":"24748859-19597789-44838006","span":{"begin":1122,"end":1123},"obj":"19597789"}],"text":"Introduction\nTremendous efforts have been made to identify ethnicity-specific single-nucleotide polymorphisms (SNPs) in human diseases [1, 2]. Dosage effect or disease susceptibility is not equal among ethnic groups. Type 2 diabetes prevalence is 12.8%, 8.4%, and 6.6% in non-Hispanic blacks, in Mexican-Americans, and in non-Hispanic whites aged 20 years or older [3]. Ethnic differences were causes of environmental exposure and experiences with health care, and these ethnic disparities likely influence different outcomes in people with certain diseases [4]. Genetic differences also cannot ignore its important role in determining ethnic disparities. Despite recent advances in the genetic studies for ethnic disparities, little is known about how ethnic genetic differences contribute to inter-ethnic disparities in disease risk or disease-related complex traits [5].\nRecently, semantic modeling has gained attention as a powerful tool for organizing and integrating biological big data [6]. Semantic technology is needed to provide the knowledge to gain an adequate interpretation of integrated biological systems [7]. Recent advances in ontology development, like semantic modeling, are considered to contribute to the next-generation approach by enabling the researcher to actually ask scientific questions instead of constructing complicated databases for scientific questions and answers [8]. This combination of data integration and visualization could provide important insights into heterogeneous data on millions of genes, chemical compounds, diseases, and pathways [9, 10].\nTo model a semantic network, the BioXM software is a customizable knowledge management program for large scientific data, and the latest solution is designed to provide meaningful interactions through graphical browsing [11]. Through an advanced query builder, the knowledge consisting of many different and connected queries is flexibly examined. In this way, models for a research project can be constructed and extended effectively. Many data modeling studies and software developments have been advanced, but there are relatively few studies using semantic modeling for ethnicity-specific SNPs.\nTo evaluate the ethnic disparities, in the current study, we identified ethnicity-specific SNPs for three populations, including North Americans with European ancestry (CEU), Japanese from Tokyo (JPT), and Yorubans from Ibadan (YRI) from HapMap, and constructed a semantic model for ethnicity-specific SNPs. We expect that semantic model-based research will provide valuable information on ethnicity-specific gene-based SNPs and strongly affect useful knowledge in ethnic disparities."}

{"project":"NEUROSES","denotations":[{"id":"T84","span":{"begin":168,"end":182},"obj":"PATO_0001043"},{"id":"T85","span":{"begin":616,"end":620},"obj":"CHEBI_50906"},{"id":"T86","span":{"begin":664,"end":670},"obj":"PATO_0001484"},{"id":"T87","span":{"begin":1126,"end":1132},"obj":"PATO_0001484"},{"id":"T88","span":{"begin":854,"end":861},"obj":"PATO_0001504"},{"id":"T89","span":{"begin":984,"end":987},"obj":"PATO_0000586"},{"id":"T90","span":{"begin":1689,"end":1694},"obj":"PATO_0000586"},{"id":"T91","span":{"begin":1064,"end":1072},"obj":"PATO_0001627"},{"id":"T92","span":{"begin":1727,"end":1735},"obj":"CHEBI_75958"},{"id":"T93","span":{"begin":1827,"end":1835},"obj":"PATO_0000694"},{"id":"T94","span":{"begin":2089,"end":2097},"obj":"PATO_0000694"},{"id":"T83","span":{"begin":85,"end":95},"obj":"CHEBI_36976"}],"text":"Introduction\nTremendous efforts have been made to identify ethnicity-specific single-nucleotide polymorphisms (SNPs) in human diseases [1, 2]. Dosage effect or disease susceptibility is not equal among ethnic groups. Type 2 diabetes prevalence is 12.8%, 8.4%, and 6.6% in non-Hispanic blacks, in Mexican-Americans, and in non-Hispanic whites aged 20 years or older [3]. Ethnic differences were causes of environmental exposure and experiences with health care, and these ethnic disparities likely influence different outcomes in people with certain diseases [4]. Genetic differences also cannot ignore its important role in determining ethnic disparities. Despite recent advances in the genetic studies for ethnic disparities, little is known about how ethnic genetic differences contribute to inter-ethnic disparities in disease risk or disease-related complex traits [5].\nRecently, semantic modeling has gained attention as a powerful tool for organizing and integrating biological big data [6]. Semantic technology is needed to provide the knowledge to gain an adequate interpretation of integrated biological systems [7]. Recent advances in ontology development, like semantic modeling, are considered to contribute to the next-generation approach by enabling the researcher to actually ask scientific questions instead of constructing complicated databases for scientific questions and answers [8]. This combination of data integration and visualization could provide important insights into heterogeneous data on millions of genes, chemical compounds, diseases, and pathways [9, 10].\nTo model a semantic network, the BioXM software is a customizable knowledge management program for large scientific data, and the latest solution is designed to provide meaningful interactions through graphical browsing [11]. Through an advanced query builder, the knowledge consisting of many different and connected queries is flexibly examined. In this way, models for a research project can be constructed and extended effectively. Many data modeling studies and software developments have been advanced, but there are relatively few studies using semantic modeling for ethnicity-specific SNPs.\nTo evaluate the ethnic disparities, in the current study, we identified ethnicity-specific SNPs for three populations, including North Americans with European ancestry (CEU), Japanese from Tokyo (JPT), and Yorubans from Ibadan (YRI) from HapMap, and constructed a semantic model for ethnicity-specific SNPs. We expect that semantic model-based research will provide valuable information on ethnicity-specific gene-based SNPs and strongly affect useful knowledge in ethnic disparities."}