{"title":"生物功能的量子涨落:人类microRNA记忆包对疾病的计算分析","authors":"Tatsunori Osone, Masaru Yoshikawa, Y. Fujii","doi":"10.1109/SAI.2016.7556131","DOIUrl":null,"url":null,"abstract":"Recent advances in computer technology and calculation theory have enabled us to simulate more complex and various phenomena on computer than before. Computer based calculation is used in wide fields from weather prediction to protein structure analysis. Precise simulations by adopting excellent models and appropriate algorithms have given us numerous novel information and understandings. Here, we showed a novel theoretical and quantitative algorithm for disease diagnosis. There are huge number of small RNA genes named microRNA (miRNA), a regulator of gene expression, in humans. It has recently been indicated that miRNAs have quantum character according to RNA wave 2000 model. Application of this quantum simulation to disease big data including miRNA expression level were executed by using cluster-computing. Algorithms based on this theory have revealed synergistic miRNA functions with quantum coherent and disease-implicated miRNA superposition spectrums have been discovered as miRNA memory. Our result revealed that disease may be able to express linear function between disease tissue and normal tissue by miRNA quantum superposition. In turn, only to calculation of miRNA quantum superposition could be needed to diagnose and cure disease. Thus, this is the first paper that significant correlations between miRNA quantum score and diseases were successfully observed in quantum fluctuation.","PeriodicalId":219896,"journal":{"name":"2016 SAI Computing Conference (SAI)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantum fluctuations in biological functions: Computational analysis of diseases with the human microRNA memory package\",\"authors\":\"Tatsunori Osone, Masaru Yoshikawa, Y. Fujii\",\"doi\":\"10.1109/SAI.2016.7556131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent advances in computer technology and calculation theory have enabled us to simulate more complex and various phenomena on computer than before. Computer based calculation is used in wide fields from weather prediction to protein structure analysis. Precise simulations by adopting excellent models and appropriate algorithms have given us numerous novel information and understandings. Here, we showed a novel theoretical and quantitative algorithm for disease diagnosis. There are huge number of small RNA genes named microRNA (miRNA), a regulator of gene expression, in humans. It has recently been indicated that miRNAs have quantum character according to RNA wave 2000 model. Application of this quantum simulation to disease big data including miRNA expression level were executed by using cluster-computing. Algorithms based on this theory have revealed synergistic miRNA functions with quantum coherent and disease-implicated miRNA superposition spectrums have been discovered as miRNA memory. Our result revealed that disease may be able to express linear function between disease tissue and normal tissue by miRNA quantum superposition. In turn, only to calculation of miRNA quantum superposition could be needed to diagnose and cure disease. Thus, this is the first paper that significant correlations between miRNA quantum score and diseases were successfully observed in quantum fluctuation.\",\"PeriodicalId\":219896,\"journal\":{\"name\":\"2016 SAI Computing Conference (SAI)\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 SAI Computing Conference (SAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAI.2016.7556131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 SAI Computing Conference (SAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAI.2016.7556131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quantum fluctuations in biological functions: Computational analysis of diseases with the human microRNA memory package
Recent advances in computer technology and calculation theory have enabled us to simulate more complex and various phenomena on computer than before. Computer based calculation is used in wide fields from weather prediction to protein structure analysis. Precise simulations by adopting excellent models and appropriate algorithms have given us numerous novel information and understandings. Here, we showed a novel theoretical and quantitative algorithm for disease diagnosis. There are huge number of small RNA genes named microRNA (miRNA), a regulator of gene expression, in humans. It has recently been indicated that miRNAs have quantum character according to RNA wave 2000 model. Application of this quantum simulation to disease big data including miRNA expression level were executed by using cluster-computing. Algorithms based on this theory have revealed synergistic miRNA functions with quantum coherent and disease-implicated miRNA superposition spectrums have been discovered as miRNA memory. Our result revealed that disease may be able to express linear function between disease tissue and normal tissue by miRNA quantum superposition. In turn, only to calculation of miRNA quantum superposition could be needed to diagnose and cure disease. Thus, this is the first paper that significant correlations between miRNA quantum score and diseases were successfully observed in quantum fluctuation.