Aortic dissection(AD)is one of the most serious diseases with high mortality,and its diagnosis mainly depends on computed tomography(CT)results.Most existing automatic diagnosis methods of AD are only suitable for AD ...Aortic dissection(AD)is one of the most serious diseases with high mortality,and its diagnosis mainly depends on computed tomography(CT)results.Most existing automatic diagnosis methods of AD are only suitable for AD recognition,which usually require preselection of CT images and cannot be further classified to different types.In this work,we constructed a dataset of 105 cases with a total of 49021 slices,including 31043 slices expertlevel annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep learning.The proposed region of interest(RoI)extraction algorithm based on sequence information(RESI)can realize high-precision for RoI identification in the first stage.Then DenseNet-121 is applied for further diagnosis.Specially,the proposed method can judge the type of AD without preselection of CT images.The experimental results show that the accuracy of Stanford typing classification of AD is 89.19%,and the accuracy at the slice-level reaches 97.41%,which outperform the state-ofart methods.It can provide important decision-making information for the determination of further surgical treatment plan for patients.展开更多
Fertility is the most crucial step in the development process,which is controlled by many fertility-related proteins,including spermatogenesis-,oogenesis-and embryogenesis-related proteins.The identification of fertil...Fertility is the most crucial step in the development process,which is controlled by many fertility-related proteins,including spermatogenesis-,oogenesis-and embryogenesis-related proteins.The identification of fertility-related proteins can provide important clues for studying the role of these proteins in development.Therefore,in this study,we constructed a two-layer classifier to identify fertility-related proteins.In this classifier,we first used the composition of amino acids(AA)and their physical and chemical properties to code these three fertility-related proteins.Then,the feature set is optimized by analysis of variance(ANOVA)and incremental feature selection(IFS)to obtain the optimal feature subset.Through five-fold cross-validation(CV)and independent data tests,the performance of models constructed by different machine learning(ML)methods is evaluated and compared.Finally,based on support vector machine(SVM),we obtained a two-layer model to classify three fertility-related proteins.On the independent test data set,the accuracy(ACC)and the area under the receiver operating characteristic curve(AUC)of the first layer classifier are 81.95%and 0.89,respectively,and them of the second layer classifier are 84.74%and 0.90,respectively.These results show that the proposed model has stable performance and satisfactory prediction accuracy,and can become a powerful model to identify more fertility related proteins.展开更多
Mungbean （Vigna radiata （L.） Wilczek） is a unique species in its ability to fix atmospheric nitrogen, with early maturity, and relatively good drought resistance. We used 454 sequencing technology for transcriptom...Mungbean （Vigna radiata （L.） Wilczek） is a unique species in its ability to fix atmospheric nitrogen, with early maturity, and relatively good drought resistance. We used 454 sequencing technology for transcriptome sequencing. A total of 150 159 and 142 993 reads produced 5 254 and 6 374 large contigs （〉_500 bp） with an average length of 833 and 853 for Sunhwa and Jangan, respectively. Functional annotation to known sequences yielded 41.34% and 41.74% unigenes for Jangan and Sunhwa. A higher number of simple sequence repeat （SSR） motifs was identified in Jangan （1 630） compared with that of Sunhwa （1 334）. A similar SSR distribution pattern was observed in both varieties. A total of 8 249 single nucleotide polymorphisms （SNPs） and indels with 2 098 high-confidence candidates were identified in the two mungbean varieties. The average distance between individual SNPs was -860 bp. Our report demonstrates the utility of transcriptomic data for implementing a functional annotation and development of genetic markers. We also provide large resource sequence data for mungbean improvement programs.展开更多
The genome sequence information in combination with DNA microarrays promises to revolutionize the way of cellu-lar and molecular biological research by allowing complex mixtures of RNA and DNA to interrogated in a par...The genome sequence information in combination with DNA microarrays promises to revolutionize the way of cellu-lar and molecular biological research by allowing complex mixtures of RNA and DNA to interrogated in a parallel and quantita-tive fashion. DNA microarrays can be used to measure levels of gene expression for tens of thousands of gene simultane-ously and take advantage of all available sequence information for experimental design and data interpretation in pursuit of biological understanding. Recent progress in experimental genomics allows DNA microarrays not simply to provide a cata-logue of all the genes and information about their function, but to understand how the components work together to comprise functioning cells and organisms. This brief review gives a survey of DNA microarrays technology and its applications in ge-nome and gene function analysis, gene expression studies, biological signal and defense system, cell cycle regulation, mechanism of transcriptional regulation, proteomics, and the functionality of food component.展开更多
The introduction of next-generation sequencing(NGS) technology in testing for hereditary cancer susceptibility allows testing of multiple cancer susceptibility genes simultaneously. While there are many potential bene...The introduction of next-generation sequencing(NGS) technology in testing for hereditary cancer susceptibility allows testing of multiple cancer susceptibility genes simultaneously. While there are many potential benefits to utilizing this technology in the hereditary cancer clinic, including efficiency of time and cost, there are also important limitations that must be considered. The best panel for the given clinical situation should be selected to minimize the number of variants of unknown significance. The inclusion in panels of low penetrance or newly identified genes without specific actionability can be problematic for interpretation.Genetic counselors are an essential part of the hereditary cancer risk assessment team, helping the medical team select the most appropriate test and interpret the often complex results. Genetic counselors obtain an extended family history, counsel patients on the available tests and the potential implications of results for themselves and their family members(pre-test counseling), explain to patients the implications of the test results(post-test counseling), and assist in testing family members at risk.展开更多
基金This work was supported in part by the National Natural Science Foundation of China(No.62002392)in part by the Key Research and Development Plan of Hunan Province(No.2019SK2022)+2 种基金in part by the Natural Science Foundation of Hunan Province(No.2020JJ4140 and 2020JJ4141)in part by the Science Research Projects of Hunan Provincial Education Department(No.19B584)in part by the Postgraduate Excellent teaching team Project of Hunan Province[Grant[2019]370-133].
文摘Aortic dissection(AD)is one of the most serious diseases with high mortality,and its diagnosis mainly depends on computed tomography(CT)results.Most existing automatic diagnosis methods of AD are only suitable for AD recognition,which usually require preselection of CT images and cannot be further classified to different types.In this work,we constructed a dataset of 105 cases with a total of 49021 slices,including 31043 slices expertlevel annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep learning.The proposed region of interest(RoI)extraction algorithm based on sequence information(RESI)can realize high-precision for RoI identification in the first stage.Then DenseNet-121 is applied for further diagnosis.Specially,the proposed method can judge the type of AD without preselection of CT images.The experimental results show that the accuracy of Stanford typing classification of AD is 89.19%,and the accuracy at the slice-level reaches 97.41%,which outperform the state-ofart methods.It can provide important decision-making information for the determination of further surgical treatment plan for patients.
基金funded by the Sichuan Major Science and Technology Project(2021ZDZX0009)the National Natural Science Foundation of China(Grant No.035Z2060).
文摘Fertility is the most crucial step in the development process,which is controlled by many fertility-related proteins,including spermatogenesis-,oogenesis-and embryogenesis-related proteins.The identification of fertility-related proteins can provide important clues for studying the role of these proteins in development.Therefore,in this study,we constructed a two-layer classifier to identify fertility-related proteins.In this classifier,we first used the composition of amino acids(AA)and their physical and chemical properties to code these three fertility-related proteins.Then,the feature set is optimized by analysis of variance(ANOVA)and incremental feature selection(IFS)to obtain the optimal feature subset.Through five-fold cross-validation(CV)and independent data tests,the performance of models constructed by different machine learning(ML)methods is evaluated and compared.Finally,based on support vector machine(SVM),we obtained a two-layer model to classify three fertility-related proteins.On the independent test data set,the accuracy(ACC)and the area under the receiver operating characteristic curve(AUC)of the first layer classifier are 81.95%and 0.89,respectively,and them of the second layer classifier are 84.74%and 0.90,respectively.These results show that the proposed model has stable performance and satisfactory prediction accuracy,and can become a powerful model to identify more fertility related proteins.
基金support of the "Cooperative Research Program for Agriculture Science & Technology Development (Project No. 200908FHT020609001)" Rural Development Administration (RDA),Republic of Korea
文摘Mungbean （Vigna radiata （L.） Wilczek） is a unique species in its ability to fix atmospheric nitrogen, with early maturity, and relatively good drought resistance. We used 454 sequencing technology for transcriptome sequencing. A total of 150 159 and 142 993 reads produced 5 254 and 6 374 large contigs （〉_500 bp） with an average length of 833 and 853 for Sunhwa and Jangan, respectively. Functional annotation to known sequences yielded 41.34% and 41.74% unigenes for Jangan and Sunhwa. A higher number of simple sequence repeat （SSR） motifs was identified in Jangan （1 630） compared with that of Sunhwa （1 334）. A similar SSR distribution pattern was observed in both varieties. A total of 8 249 single nucleotide polymorphisms （SNPs） and indels with 2 098 high-confidence candidates were identified in the two mungbean varieties. The average distance between individual SNPs was -860 bp. Our report demonstrates the utility of transcriptomic data for implementing a functional annotation and development of genetic markers. We also provide large resource sequence data for mungbean improvement programs.
文摘The genome sequence information in combination with DNA microarrays promises to revolutionize the way of cellu-lar and molecular biological research by allowing complex mixtures of RNA and DNA to interrogated in a parallel and quantita-tive fashion. DNA microarrays can be used to measure levels of gene expression for tens of thousands of gene simultane-ously and take advantage of all available sequence information for experimental design and data interpretation in pursuit of biological understanding. Recent progress in experimental genomics allows DNA microarrays not simply to provide a cata-logue of all the genes and information about their function, but to understand how the components work together to comprise functioning cells and organisms. This brief review gives a survey of DNA microarrays technology and its applications in ge-nome and gene function analysis, gene expression studies, biological signal and defense system, cell cycle regulation, mechanism of transcriptional regulation, proteomics, and the functionality of food component.
文摘The introduction of next-generation sequencing(NGS) technology in testing for hereditary cancer susceptibility allows testing of multiple cancer susceptibility genes simultaneously. While there are many potential benefits to utilizing this technology in the hereditary cancer clinic, including efficiency of time and cost, there are also important limitations that must be considered. The best panel for the given clinical situation should be selected to minimize the number of variants of unknown significance. The inclusion in panels of low penetrance or newly identified genes without specific actionability can be problematic for interpretation.Genetic counselors are an essential part of the hereditary cancer risk assessment team, helping the medical team select the most appropriate test and interpret the often complex results. Genetic counselors obtain an extended family history, counsel patients on the available tests and the potential implications of results for themselves and their family members(pre-test counseling), explain to patients the implications of the test results(post-test counseling), and assist in testing family members at risk.
