In recent years,molecular identification technology has become the predominant approach for the identification of traditional Chinese medicine.The molecular identification techniques in recent years were analyzed and ...In recent years,molecular identification technology has become the predominant approach for the identification of traditional Chinese medicine.The molecular identification techniques in recent years were analyzed and summarized in this paper,such as RAPD,ISSR,RFLP,AFLP,SNP,and DNA bar code sequence analysis techniques.By consulting Sciencedirect databases and Web of Science databases,2348 related articles were found,of which 39 were related to molecular identification techniques and traditional Chinese medicine.The application of the molecular identification techniques in four aspects was reviewed,namely the identification on the authenticity(true or false),multi-source identification and genetic diversity,producing area,and growing year discrimination of traditional Chinese medicine.展开更多
To further improvc the application of DNA fingerprinting technique in adulterated food identification and traceability, the paper briefly introduced the ap- plication of common DNA fingerprinting techniques, such as s...To further improvc the application of DNA fingerprinting technique in adulterated food identification and traceability, the paper briefly introduced the ap- plication of common DNA fingerprinting techniques, such as species-specific PCR, RAPD, AFLP, ISSR, SSR and SNP in adulterated food identification and traceability.展开更多
Epigenetics is the study of phenotypic variations that do not alter DNA sequences.Cancer epigenetics has grown rapidly over the past few years as epigenetic alterations exist in all human cancers.One of these alterati...Epigenetics is the study of phenotypic variations that do not alter DNA sequences.Cancer epigenetics has grown rapidly over the past few years as epigenetic alterations exist in all human cancers.One of these alterations is DNA methylation;an epigenetic process that regulates gene expression and often occurs at tumor suppressor gene loci in cancer.Therefore,studying this methylation process may shed light on different gene functions that cannot otherwise be interpreted using the changes that occur in DNA sequences.Currently,microarray technologies;such as Illumina Infinium BeadChip assays;are used to study DNA methylation at an extremely large number of varying loci.At each DNA methylation site,a beta value(β)is used to reflect the methylation intensity.Therefore,clustering this data from various types of cancers may lead to the discovery of large partitions that can help objectively classify different types of cancers aswell as identify the relevant loci without user bias.This study proposed a Nested Big Data Clustering Genetic Algorithm(NBDC-GA);a novel evolutionary metaheuristic technique that can perform cluster-based feature selection based on the DNA methylation sites.The efficacy of the NBDC-GA was tested using real-world data sets retrieved from The Cancer Genome Atlas(TCGA);a cancer genomics program created by the NationalCancer Institute(NCI)and the NationalHuman Genome Research Institute.The performance of the NBDC-GA was then compared with that of a recently developed metaheuristic Immuno-Genetic Algorithm(IGA)that was tested using the same data sets.The NBDC-GA outperformed the IGA in terms of convergence performance.Furthermore,the NBDC-GA produced a more robust clustering configuration while simultaneously decreasing the dimensionality of features to a maximumof 67%and of 94.5%for individual cancer type and collective cancer,respectively.The proposed NBDC-GA was also able to identify two chromosomes with highly contrastingDNAmethylations activities that were previously linked to cancer.展开更多
基金supported by National Nature Science Foundation of China(81973284)Scientific Research Foundation of the Education Department of Liaoning Province(LJKZ0944).
文摘In recent years,molecular identification technology has become the predominant approach for the identification of traditional Chinese medicine.The molecular identification techniques in recent years were analyzed and summarized in this paper,such as RAPD,ISSR,RFLP,AFLP,SNP,and DNA bar code sequence analysis techniques.By consulting Sciencedirect databases and Web of Science databases,2348 related articles were found,of which 39 were related to molecular identification techniques and traditional Chinese medicine.The application of the molecular identification techniques in four aspects was reviewed,namely the identification on the authenticity(true or false),multi-source identification and genetic diversity,producing area,and growing year discrimination of traditional Chinese medicine.
基金Supported by the Youth Foundation of Sichuan Academy of Agricultural Sciences(2009QNJJ-037,2010QNJJ-031)the Monitoring on Alien Biological Invasion(the Project of Ministry of Agriculture)
文摘To further improvc the application of DNA fingerprinting technique in adulterated food identification and traceability, the paper briefly introduced the ap- plication of common DNA fingerprinting techniques, such as species-specific PCR, RAPD, AFLP, ISSR, SSR and SNP in adulterated food identification and traceability.
文摘Epigenetics is the study of phenotypic variations that do not alter DNA sequences.Cancer epigenetics has grown rapidly over the past few years as epigenetic alterations exist in all human cancers.One of these alterations is DNA methylation;an epigenetic process that regulates gene expression and often occurs at tumor suppressor gene loci in cancer.Therefore,studying this methylation process may shed light on different gene functions that cannot otherwise be interpreted using the changes that occur in DNA sequences.Currently,microarray technologies;such as Illumina Infinium BeadChip assays;are used to study DNA methylation at an extremely large number of varying loci.At each DNA methylation site,a beta value(β)is used to reflect the methylation intensity.Therefore,clustering this data from various types of cancers may lead to the discovery of large partitions that can help objectively classify different types of cancers aswell as identify the relevant loci without user bias.This study proposed a Nested Big Data Clustering Genetic Algorithm(NBDC-GA);a novel evolutionary metaheuristic technique that can perform cluster-based feature selection based on the DNA methylation sites.The efficacy of the NBDC-GA was tested using real-world data sets retrieved from The Cancer Genome Atlas(TCGA);a cancer genomics program created by the NationalCancer Institute(NCI)and the NationalHuman Genome Research Institute.The performance of the NBDC-GA was then compared with that of a recently developed metaheuristic Immuno-Genetic Algorithm(IGA)that was tested using the same data sets.The NBDC-GA outperformed the IGA in terms of convergence performance.Furthermore,the NBDC-GA produced a more robust clustering configuration while simultaneously decreasing the dimensionality of features to a maximumof 67%and of 94.5%for individual cancer type and collective cancer,respectively.The proposed NBDC-GA was also able to identify two chromosomes with highly contrastingDNAmethylations activities that were previously linked to cancer.
