Ting Liu, Xueli Pan, Xu Wang, K. Feenstra, J. Heringa, Zhisheng Huang
{"title":"用知识图谱探索精神障碍的微生物-肠-脑轴","authors":"Ting Liu, Xueli Pan, Xu Wang, K. Feenstra, J. Heringa, Zhisheng Huang","doi":"10.2991/jaims.d.201208.001","DOIUrl":null,"url":null,"abstract":"Gut microbiota has a significant influence on brain-related diseases through the communication routes of the gut-brain axis. Manyspeciesofgutmicrobiotaproduceavarietyofneurotransmitters.Inessence,theneurotransmittersarechemicalsthatinflu-ence mood, cognition, and behavior of the host. The relationships between gut microbiota and neurotransmitters has received much attention in medical and biomedical research. However, the integration of the various proposed neurotransmitter signal routes that underpin these relationships has not yet been studied well. To unlock the influence of gut microbiota on mental health via neurotransmitters, the microbiota-gut-brain (MGB) axis, we gather the decentralized results in the existing studies into a structured knowledge base. In this paper, we therefore propose a novel Microbiota Knowledge Graph based on a newly constructed knowledge graph for uncovering the potential associations among gut microbiota, neurotransmitters, and mental disorders which we refer to as MiKG. It includes many interfaces that link to well-known biomedical ontologies, e.g. UMLS, MeSH, KEGG, and SNOMED CT, and is extendable by linking to future ontologies to further exploit the relationships between gut microbiota and neurotransmitters. This paper present MiKG, an effective knowledge graph, that can be used to investigate the MGB axis using the relationships among gut microbiota, neurotransmitters, and mental disorders.","PeriodicalId":196434,"journal":{"name":"Journal of Artificial Intelligence for Medical Sciences","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Exploring the Microbiota-Gut-Brain Axis for Mental Disorders with Knowledge Graphs\",\"authors\":\"Ting Liu, Xueli Pan, Xu Wang, K. Feenstra, J. Heringa, Zhisheng Huang\",\"doi\":\"10.2991/jaims.d.201208.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Gut microbiota has a significant influence on brain-related diseases through the communication routes of the gut-brain axis. Manyspeciesofgutmicrobiotaproduceavarietyofneurotransmitters.Inessence,theneurotransmittersarechemicalsthatinflu-ence mood, cognition, and behavior of the host. The relationships between gut microbiota and neurotransmitters has received much attention in medical and biomedical research. However, the integration of the various proposed neurotransmitter signal routes that underpin these relationships has not yet been studied well. To unlock the influence of gut microbiota on mental health via neurotransmitters, the microbiota-gut-brain (MGB) axis, we gather the decentralized results in the existing studies into a structured knowledge base. In this paper, we therefore propose a novel Microbiota Knowledge Graph based on a newly constructed knowledge graph for uncovering the potential associations among gut microbiota, neurotransmitters, and mental disorders which we refer to as MiKG. It includes many interfaces that link to well-known biomedical ontologies, e.g. UMLS, MeSH, KEGG, and SNOMED CT, and is extendable by linking to future ontologies to further exploit the relationships between gut microbiota and neurotransmitters. This paper present MiKG, an effective knowledge graph, that can be used to investigate the MGB axis using the relationships among gut microbiota, neurotransmitters, and mental disorders.\",\"PeriodicalId\":196434,\"journal\":{\"name\":\"Journal of Artificial Intelligence for Medical Sciences\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Artificial Intelligence for Medical Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/jaims.d.201208.001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Artificial Intelligence for Medical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/jaims.d.201208.001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring the Microbiota-Gut-Brain Axis for Mental Disorders with Knowledge Graphs
Gut microbiota has a significant influence on brain-related diseases through the communication routes of the gut-brain axis. Manyspeciesofgutmicrobiotaproduceavarietyofneurotransmitters.Inessence,theneurotransmittersarechemicalsthatinflu-ence mood, cognition, and behavior of the host. The relationships between gut microbiota and neurotransmitters has received much attention in medical and biomedical research. However, the integration of the various proposed neurotransmitter signal routes that underpin these relationships has not yet been studied well. To unlock the influence of gut microbiota on mental health via neurotransmitters, the microbiota-gut-brain (MGB) axis, we gather the decentralized results in the existing studies into a structured knowledge base. In this paper, we therefore propose a novel Microbiota Knowledge Graph based on a newly constructed knowledge graph for uncovering the potential associations among gut microbiota, neurotransmitters, and mental disorders which we refer to as MiKG. It includes many interfaces that link to well-known biomedical ontologies, e.g. UMLS, MeSH, KEGG, and SNOMED CT, and is extendable by linking to future ontologies to further exploit the relationships between gut microbiota and neurotransmitters. This paper present MiKG, an effective knowledge graph, that can be used to investigate the MGB axis using the relationships among gut microbiota, neurotransmitters, and mental disorders.