{"title":"thd -三聚体法对接受干扰素治疗的多发性硬化症患者基因表达数据的研究","authors":"A. Rachma, S. Soemartojo, T. Siswantining","doi":"10.1063/5.0058711","DOIUrl":null,"url":null,"abstract":"THD-Tricluster method is a triclustering analysis with a biclustering-based approach. The THD-Tricluster method uses the Shifting-and-Scaling Similarity (SSSim) value to form a bicluster first and shows it by forming a tricluster. The SSSim value uses Shifting-and-Scaling Correlation to use an interface with shifting and scaling patterns as well as intertemporal coherence and compares it with the threshold value. THD-Tricluster method was performed on treatment response data to interferon-beta therapy in multiple sclerosis patients. The optimal scenario is a scenario with a coverage value scenario that uses the highest threshold value. In this scenario, there are two types of tricluster, namely the tricluster which has a collection of genes in responsive patients and patients who are not responsive to therapy. The differences collection of genes in both tricluster can be used by medical professionals in the development of interferon-beta therapy treatments to create a therapy response on multiple sclerosis disease.","PeriodicalId":20561,"journal":{"name":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","volume":"6 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"THD-Tricluster method on gene expression data of multiple sclerosis patients receiving interferon-beta therapy\",\"authors\":\"A. Rachma, S. Soemartojo, T. Siswantining\",\"doi\":\"10.1063/5.0058711\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"THD-Tricluster method is a triclustering analysis with a biclustering-based approach. The THD-Tricluster method uses the Shifting-and-Scaling Similarity (SSSim) value to form a bicluster first and shows it by forming a tricluster. The SSSim value uses Shifting-and-Scaling Correlation to use an interface with shifting and scaling patterns as well as intertemporal coherence and compares it with the threshold value. THD-Tricluster method was performed on treatment response data to interferon-beta therapy in multiple sclerosis patients. The optimal scenario is a scenario with a coverage value scenario that uses the highest threshold value. In this scenario, there are two types of tricluster, namely the tricluster which has a collection of genes in responsive patients and patients who are not responsive to therapy. The differences collection of genes in both tricluster can be used by medical professionals in the development of interferon-beta therapy treatments to create a therapy response on multiple sclerosis disease.\",\"PeriodicalId\":20561,\"journal\":{\"name\":\"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1063/5.0058711\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PROCEEDINGS OF THE 6TH INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2020 (ISCPMS 2020)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1063/5.0058711","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
THD-Tricluster method on gene expression data of multiple sclerosis patients receiving interferon-beta therapy
THD-Tricluster method is a triclustering analysis with a biclustering-based approach. The THD-Tricluster method uses the Shifting-and-Scaling Similarity (SSSim) value to form a bicluster first and shows it by forming a tricluster. The SSSim value uses Shifting-and-Scaling Correlation to use an interface with shifting and scaling patterns as well as intertemporal coherence and compares it with the threshold value. THD-Tricluster method was performed on treatment response data to interferon-beta therapy in multiple sclerosis patients. The optimal scenario is a scenario with a coverage value scenario that uses the highest threshold value. In this scenario, there are two types of tricluster, namely the tricluster which has a collection of genes in responsive patients and patients who are not responsive to therapy. The differences collection of genes in both tricluster can be used by medical professionals in the development of interferon-beta therapy treatments to create a therapy response on multiple sclerosis disease.