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BioProspecting: novel marker discovery obtained by mining the bibleome

机译:生物勘探:通过挖掘圣经组获得新的标记物发现

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摘要

BioProspecting is a novel approach that enabled our team to mine data related to genetic markers from the New England Journal of Medicine (NEJM) utilizing SNOMED CT and the Human Gene Onotology (HUGO). The Biomedical Informatics Research Collaborative was able to link genes and disorders using the Multi-threaded Clinical Vocabulary Server (MCVS) and natural language processing engine, whose output creates an ontology-network using the semantic encodings of the literature that is organized by these two terminologies. We identified relationships between (genes or proteins) and (diseases or drugs) as linked by metabolic functions and identified potentially novel functional relationships between, for example, genes and diseases (e.g. Article #1 ([Gene - IL27] = > {Enzyme - Dipeptidyl Carboxypeptidase 1}) and Article #2 ({Enzyme - Dipeptidyl Carboxypeptidase 1} < = [Disorder - Type II DM]) showing a metabolic link between IL27 and Type II DM). In this manuscript we describe our method for developing the database and its content as well as its potential to assist in the discovery of novel markers and drugs.
机译:BioProspecting是一种新颖的方法,使我们的团队能够利用SNOMED CT和人类基因本体论(HUGO)来挖掘《新英格兰医学杂志》(NEJM)的遗传标记相关数据。生物医学信息学研究协作者能够使用多线程临床词汇服务器(MCVS)和自然语言处理引擎链接基因和疾病,其输出使用这两种术语所组织的文献的语义编码创建了一个本体网络。 。我们通过代谢功能确定了(基因或蛋白质)与(疾病或药物)之间的关系,并确定了例如基因和疾病之间潜在的新型功能关系(例如,第1条([Gene-IL27] => {Enzyme-二肽基羧肽酶1})和文章#2({酶-二肽羧肽酶1} <= [疾病-II型DM])显示了IL27和II型DM之间的代谢联系。在本手稿中,我们描述了开发数据库的方法及其内容,以及其辅助发现新型标记物和药物的潜力。

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