Background Cotton is a significant crop for fiber production;however,seed shape-related traits have been less investigated in comparison to fiber quality.Comprehending the genetic foundation of traits associated with ...Background Cotton is a significant crop for fiber production;however,seed shape-related traits have been less investigated in comparison to fiber quality.Comprehending the genetic foundation of traits associated with seed shape is crucial for improving the seed and fiber quality in cotton.Results A total of 238 cotton accessions were evaluated in four different environments over a period of two years.Traits including thousand grain weight(TGW),aspect ratio(AR),seed length,seed width,diameter,and roundness demonstrated high heritability and significant genetic variation,as indicated by phenotypic analysis.The association analysis involved 145 simple sequence repeats(SSR)markers and identified 50 loci significantly associated with six traits related to seed shape.The markers MON_DPL0504aa and BNL2535ba were identified as influencing multiple traits,including aspect ratio and thousand grain weight.Notably,markers such as HAU2588a and MUSS422aa had considerable influence on seed diameter and roundness.The identified markers represented an average phenotypic variance between 3.92%for seed length and 16.54%for TGW.Conclusions The research finds key loci for seed shape-related traits in cotton,providing significant potential for marker-assisted breeding.These findings establish a framework for breeding initiatives focused on enhancing seed quality,hence advancing the cotton production.展开更多
Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are...Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are similar for different closely spaced targets, there is ambiguity in using the kinematic information alone; the correct association probability will decrease in conventional joint probabilistic data association algorithm and track coalescence will occur easily. A modified algorithm of joint probabilistic data association with classification-aided is presented, which avoids track coalescence when tracking multiple neighboring targets. Firstly, an identification matrix is defined, which is used to simplify validation matrix to decrease computational complexity. Then, target class information is integrated into the data association process. Performance comparisons with and without the use of class information in JPDA are presented on multiple closely spaced maneuvering targets tracking problem. Simulation results quantify the benefits of classification-aided JPDA for improved multiple targets tracking, especially in the presence of association uncertainty in the kinematic measurement and target maneuvering. Simulation results indicate that the algorithm is valid.展开更多
In order to deal with the complex association relationships between classes in an object-oriented software system,a novel approach for identifying refactoring opportunities is proposed.The approach can be used to dete...In order to deal with the complex association relationships between classes in an object-oriented software system,a novel approach for identifying refactoring opportunities is proposed.The approach can be used to detect complex and duplicated many-to-many association relationships in source code,and to provide guidance for further refactoring.In the approach,source code is first transformed to an abstract syntax tree from which all data members of each class are extracted,then each class is characterized in connection with a set of association classes saving its data members.Next,classes in common associations are obtained by comparing different association classes sets in integrated analysis.Finally,on condition of pre-defined thresholds,all class sets in candidate for refactoring and their common association classes are saved and exported.This approach is tested on 4 projects.The results show that the precision is over 96%when the threshold is 3,and 100%when the threshold is 4.Meanwhile,this approach has good execution efficiency as the execution time taken for a project with more than 500 classes is less than 4 s,which also indicates that it can be applied to projects of different scales to identify their refactoring opportunities effectively.展开更多
A specialized Hungarian algorithm was developed here for the maximum likelihood data association problem with two implementation versions due to presence of false alarms and missed detections. The maximum likelihood d...A specialized Hungarian algorithm was developed here for the maximum likelihood data association problem with two implementation versions due to presence of false alarms and missed detections. The maximum likelihood data association problem is formulated as a bipartite weighted matching problem. Its duality and the optimality conditions are given. The Hungarian algorithm with its computational steps, data structure and computational complexity is presented. The two implementation versions, Hungarian forest （HF） algorithm and Hungarian tree （HT） algorithm, and their combination with the naYve auction initialization are discussed. The computational results show that HT algorithm is slightly faster than HF algorithm and they are both superior to the classic Munkres algorithm.展开更多
Aiming at three-passive-sensor location system, a generalized 3-dimension （3-D） assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-find...Aiming at three-passive-sensor location system, a generalized 3-dimension （3-D） assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-finding and property fusion information. The multi-target programming model is transformed into a single target programming problem to resolve, and its data association result is compared with the results which are solved by using one kind of information only. Simulation experiments show the effectiveness of the multi-target programming algorithm with higher data association accuracy and less calculation.展开更多
In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too...In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too close to each other. To enhance the tracking accuracy, the target signal classification information （TSCI） should be used to improve the data association. The TSCI is integrated in the data association process using the JPDA （joint probabilistic data association）. The use of the TSCI in the data association can improve discrimination by yielding a purer track and preserving continuity. To verify the validity of the application of TSCI, two simulation experiments are done on an air target-tracing problem, that is, one using the TSCI and the other not using the TSCI. The final comparison shows that the use of the TSCI can effectively improve tracking accuracy.展开更多
The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) i...The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) it should be the minimal and the simplest association rule set; 2) its predictive power should in no way be weaker than that of the complete association rule set so that the precision of the association rule set analysis can be guaranteed. By adopting the least association rule set, the pruning of weak rules can be effectively carried out so as to greatly reduce the number of frequent itemset, and therefore improve the mining efficiency. Finally, based on the classical Apriori algorithm, the upward closure property of weak rules is utilized to develop a corresponding efficient algorithm.展开更多
Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence w...Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.展开更多
OBJECTIVE To identify compound combinations as candidate multi-component drugs for the type 2 diabetes from natural product information.METHODS Chemical composition information of herbs in natural medicine was acquire...OBJECTIVE To identify compound combinations as candidate multi-component drugs for the type 2 diabetes from natural product information.METHODS Chemical composition information of herbs in natural medicine was acquired by integrating conventional databases;Traditional Chinese Medicine Information Database(TCM-ID)and Traditional Chinese Medicine Integrated Database(TCMID).Therapeutic effect of each herb on the type 2 diabetes was examined by analyzing annotated function information with a text-mining method.The Apriori algorithm,which is a classical method for extracting associations between object in large-scale databases,was employed to infer association rules between compound combinations and therapeutic effect on the target disease.The chemical composition and therapeutic information of each herb was used as a transaction,which consists of the chemical compound combination as an antecedent item set and the therapeutic effect as a consequent item.The association rules with high support and confidence value were suggested as candidate multi-component drugs for the type 2 diabetes.RESULTS Totally 40 941 association rules were inferred with support lower bound 0.05% and maximum rule length 4.With respect to support and confidence,the top-ranked compound combination was puerarin and daidzin(support=0.15%,confidence=100%).In addition,the top 16 compound combinations were composed of 11 individual chemical compounds;puerarin,daidzin,abscisic acid,batatisine,dopamine,cholesterol,daidzein,gamma-aminobutyric acid,stigmasterol,campesteryl ferulate,and campesterol.To validate therapeutic effect of the proposed compound combinations,literature evidences of each individual compound were investigated.Among the 11 individual compounds,six compounds were reported to be effective for the treatment of the diabetes mellitus.CONCLUSION By analyzing natural product in formation with association rule mining,16 compound combinations are suggested as candidate multi-component drugs for the type 2 diabetes.These compound combinations are recommended for further investigation in the context of drug development.展开更多
Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description fram...Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space, through constructing its state （abnormality） relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validiw is proved through case.展开更多
Background: Cotton fiber yield is a complex trait,which can be influenced by multiple agronomic traits.Unravelling the genetic basis of cotton fiber yield-related traits contributes to genetic improvement of cotton.Re...Background: Cotton fiber yield is a complex trait,which can be influenced by multiple agronomic traits.Unravelling the genetic basis of cotton fiber yield-related traits contributes to genetic improvement of cotton.Results: In this study,503 upland cotton varieties covering the four breeding stages(BS1–BS4,1911–2011)in China were used for association mapping and domestication analysis.One hundred and forty SSR markers significantly associated with ten fiber yield-related traits were identified,among which,29 markers showed an increasing trend contribution to cotton yield-related traits from BS1 to BS4,and 26 markers showed decreased trend effect.Four favorable alleles of 9 major loci(R^(2)≥3)were strongly selected during the breeding stages,and the candidate genes of the four strongly selected alleles were predicated according to the gene function annotation and tissue expression data.Conclusions :The study not only uncovers the genetic basis of 10 cotton yield-related traits but also provides genetic evidence for cotton improvement during the cotton breeding process in China.展开更多
Jinshajiang melange belt locates between Jianda\|Weixi island arc and Zhongzha massif. The melange belt and island arc makes up Jinshajiang plate junction. Although subsequent tectonic movements had complexed the stru...Jinshajiang melange belt locates between Jianda\|Weixi island arc and Zhongzha massif. The melange belt and island arc makes up Jinshajiang plate junction. Although subsequent tectonic movements had complexed the structural form of Jinshajiang melange belt, there are still a lots of structural block remained which carried amount of information about the tectonic evolution of the belt. Recent researches have identified several kinds of rock association in the structural blocks.(1) Ophiolite:The ophiolite consists of serpentinization ultramafite, ultramafic cumulus crystal rock (pyroxenite, dunite), gabbro, diabase cluster, ocean\|ridge type basalt, plagiogranite and radiolarian silicalite. The isotopic age shows that the ultramafite and basalt formed during Upper Carboniferous and Lower Permian. The silicalite is high in radiolaria of Lower Permian.(2) Rock association of oceanic island\|arc:The liptocoenosis of oceanic island\|arc scatter in melange belt, it mainly consists of sandy slate, pyroclastic rock, silicalite, basalt and andesite. A part of volcanic rock belongs to calc\|alkaline volcanic suite and the other is tholeiite. The petrochemistry, REE and microelement of volcanic rock have the feature of the rock in ocean\|island arc. The isotopic age of basalt shows that the ocean\|island arc formed in Lower Permian.展开更多
Aim Clopidogrel therapy is associated with a substantial variability in pharmacokinetics （PK） and pharmacodynamics （PD） responses. To date, known gene variants explain only a small proportion of the variabili- ty....Aim Clopidogrel therapy is associated with a substantial variability in pharmacokinetics （PK） and pharmacodynamics （PD） responses. To date, known gene variants explain only a small proportion of the variabili- ty. A genome-wide association study （GWAS） was conducted to identify new genetic loci modifying PD responses to clopidogrel in Chinese patients with coronary heart disease （CHD）. The initial GWAS by combination analysis of PIL/PD included 115 patients with CHD. The PK validation included 31 patients with CHD and the metabolizing functional validation included 32 human liver tissues. We identified novel variants in two transporter genes （ rs12456693 in SLC14A2 and kgpl 1138762 in ABCA1 ） and in N6AMT1 （rs2254638） associated with not only clo- pidogrel on-treated P2Y12 reaction unit （PRU） （P 〈 1 × 10^-4） , but also plasma clopidogrel active metabolite H4 concentration （P 〈 1 × 10^-2）. The significant association between rs12456693, kgpl 1138762, or rs2254638 and PK parameters of clopidogrel （P 〈 1 × 10^-2） was observed in additional CHD patients. Further, the N6AMT1 rs2254638 T variant was found to be associated decreased activation of clopidogrel （P -3.86 × 10^-2）. The new variants in N6AMT1 and ABCA1, together with CYP2C19 ＊ 2, dramatically improve the predictability of PRU varia- bility to 37.7% compared with the published value of approximately 20%. The present study identifies novel genet- ic loci modifying PIL/PD responses to clopidogrel, which contributes to a better understanding of the absorption and metabolic mechanisms that influence PD responses to clopidogrel treatment.展开更多
OBJECTIVE Genetic variants in the pharmacokinetic(PK)mechanism are the main underlying factors that modify the antiplatelet efficacy of clopidogrel.Hence,joint analysis of genetic variants that modify pharmacodynamic(...OBJECTIVE Genetic variants in the pharmacokinetic(PK)mechanism are the main underlying factors that modify the antiplatelet efficacy of clopidogrel.Hence,joint analysis of genetic variants that modify pharmacodynamic(PD)and PK responses to clopidogrel should be effective for identifying the genetic variants affecting the antiplatelet response to the drug.METHODS A genome-wide association study was conducted to identify new genetic loci that modify PD responses to clopidogrel and its active metabolite H4 in 115 Chinese patients with coronary heart disease(CHD).RESULTS We identified novel variants in two transporter genes(rs12456693 in SLC14A2 and rs2487032 in ABCA1)and in N6AMT1(rs2254638)associated with clopidogrel-treated P2Y12reaction unit(PRU)and plasma H4 concentration.The associations between these single nucleotide polymorphisms(SNPs)and PK parameters of clopidogrel and H4 were observed in 31 additional CHD patients(P<0.05).The new variants,together with CYP2C19*2 and clinical factors,dramatically improved the predictability of PRU variability to 37.7%compared with the published value of approximately 20%.The function of these SNPs on the activation of clopidogrel was validated in 32 liver S9 fractions,and the N6AMT1 rs2254638 T variant was found to be associated with decreased formation of H4(P=0.0386).Meanwhile,N6AMT1 rs2254638 was further identified to exert a marginal risk effect for MACE in an independent CHD patient cohort(OR:1.428,95%CI:0.978-2.086,P=0.0653,FDR=0.4726).In conclusion,we systematically identified new genetic variants as risk factors for the reduced efficacy of clopidogrel.CONCLUSION Our study findings enhanced the understanding of the absorption and metabolic mechanisms that influence PD responses to clopidogrel treatment.展开更多
Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the conc...Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association （DA） algorithm not combined with directional information.展开更多
Time:October 15-17,2017Venue:San Diego,California,USA Website:2017.myana.org Abstract deadline:September 11,2017The 142nd Annual Meeting of American Neurological Association(ANA2017)will be held on October 15-17,2017 in
A new algorithm for mining quantitative association rules with standard SQL is presented. The association rules are evaluated with the sufficiency gene LS of subjectivity Bayes reasoning. This algorithm is proved to b...A new algorithm for mining quantitative association rules with standard SQL is presented. The association rules are evaluated with the sufficiency gene LS of subjectivity Bayes reasoning. This algorithm is proved to be quick and effective with its application in Lujiang insects and pests database.展开更多
Background Cotton is an important cash crop in China and a key component of the global textile market.Verticil-lium wilt is a major factor affecting cotton yield.Single nucleotide polymorphism(SNP)markers and phenotyp...Background Cotton is an important cash crop in China and a key component of the global textile market.Verticil-lium wilt is a major factor affecting cotton yield.Single nucleotide polymorphism(SNP)markers and phenotypic data can be used to identify genetic markers and loci associated with cotton resistance to Verticillium wilt.We used eight upland cotton parent materials in this study to construct a multiparent advanced generation inter-cross(MAGIC)population comprising 320 lines.The Verticillium wilt resistance of the MAGIC population was identified in the green-house in 2019,and the average relative disease index(ARDI)was calculated.A genome-wide association study(GWAS)was performed to discover SNP markers/genes associated with Verticillium wilt resistance.Results ARDI of the MAGIC population showed wide variation,ranging from 16.7 to 79.4 across three replicates.This variation reflected a diverse range of resistance to Verticillium wilt within the population.Analysis of distribution pat-terns across the environments revealed consistent trends,with coefficients of variation between 12.25%and 21.96%.Families with higher ARDI values,indicating stronger resistance,were more common,likely due to genetic diver-sity and environmental factors.Population structure analysis divided the MAGIC population into three subgroups,with Group I showing higher genetic variation and Groups II and III displaying more uniform resistance performance.Principal component analysis(PCA)confirmed these divisions,highlighting the genetic diversity underlying Verticil-lium wilt resistance.Through GWAS,we identified 19 SNPs significantly associated with Verticillium wilt resistance,distributed across three chromosomes.The screening of candidate genes was performed on the transcriptome derived from resistant and susceptible cultivars,combined with gene annotation and tissue expression patterns,and two key candidate genes,Ghir_A01G006660 and Ghir_A02G008980,were found to be potentially associated with Verticillium wilt resistance.This suggests that these two candidate genes may play an important role in responding to Verticillium wilt.Conclusion This study aims to dissect the genetic basis of Verticillium wilt resistance in cotton by using a MAGIC population and GWAS.The study seeks to provide valuable genetic resources for marker-assisted breeding and enhance the understanding of resistance mechanisms to improve cotton resilience against Verticillium wilt.展开更多
基金supported by the Fund for BTNYGG(NYHXGG,2023AA102)the National Natural Science Foundation of China(32260510)+3 种基金the Key Project for Science,Technology Development of Shihezi city,Xinjiang Production and Construction Crops(2022NY01)Shihezi University high-level talent research project(RCZK202337)Science and Technology Major Project of the Department of Science and Technology of Xinjiang Uygur Autonomous region(2022A03004-1)the Key Programs for Science and Technology Development in Agricultural Field of Xinjiang Production and Construction Corps。
文摘Background Cotton is a significant crop for fiber production;however,seed shape-related traits have been less investigated in comparison to fiber quality.Comprehending the genetic foundation of traits associated with seed shape is crucial for improving the seed and fiber quality in cotton.Results A total of 238 cotton accessions were evaluated in four different environments over a period of two years.Traits including thousand grain weight(TGW),aspect ratio(AR),seed length,seed width,diameter,and roundness demonstrated high heritability and significant genetic variation,as indicated by phenotypic analysis.The association analysis involved 145 simple sequence repeats(SSR)markers and identified 50 loci significantly associated with six traits related to seed shape.The markers MON_DPL0504aa and BNL2535ba were identified as influencing multiple traits,including aspect ratio and thousand grain weight.Notably,markers such as HAU2588a and MUSS422aa had considerable influence on seed diameter and roundness.The identified markers represented an average phenotypic variance between 3.92%for seed length and 16.54%for TGW.Conclusions The research finds key loci for seed shape-related traits in cotton,providing significant potential for marker-assisted breeding.These findings establish a framework for breeding initiatives focused on enhancing seed quality,hence advancing the cotton production.
基金Defense Advanced Research Project "the Techniques of Information Integrated Processing and Fusion" in the Eleventh Five-Year Plan (513060302).
文摘Joint probabilistic data association is an effective method for tracking multiple targets in clutter, but only the target kinematic information is used in measure-to-track association. If the kinematic likelihoods are similar for different closely spaced targets, there is ambiguity in using the kinematic information alone; the correct association probability will decrease in conventional joint probabilistic data association algorithm and track coalescence will occur easily. A modified algorithm of joint probabilistic data association with classification-aided is presented, which avoids track coalescence when tracking multiple neighboring targets. Firstly, an identification matrix is defined, which is used to simplify validation matrix to decrease computational complexity. Then, target class information is integrated into the data association process. Performance comparisons with and without the use of class information in JPDA are presented on multiple closely spaced maneuvering targets tracking problem. Simulation results quantify the benefits of classification-aided JPDA for improved multiple targets tracking, especially in the presence of association uncertainty in the kinematic measurement and target maneuvering. Simulation results indicate that the algorithm is valid.
文摘In order to deal with the complex association relationships between classes in an object-oriented software system,a novel approach for identifying refactoring opportunities is proposed.The approach can be used to detect complex and duplicated many-to-many association relationships in source code,and to provide guidance for further refactoring.In the approach,source code is first transformed to an abstract syntax tree from which all data members of each class are extracted,then each class is characterized in connection with a set of association classes saving its data members.Next,classes in common associations are obtained by comparing different association classes sets in integrated analysis.Finally,on condition of pre-defined thresholds,all class sets in candidate for refactoring and their common association classes are saved and exported.This approach is tested on 4 projects.The results show that the precision is over 96%when the threshold is 3,and 100%when the threshold is 4.Meanwhile,this approach has good execution efficiency as the execution time taken for a project with more than 500 classes is less than 4 s,which also indicates that it can be applied to projects of different scales to identify their refactoring opportunities effectively.
基金This project was supported by the National Natural Science Foundation of China (60272024).
文摘A specialized Hungarian algorithm was developed here for the maximum likelihood data association problem with two implementation versions due to presence of false alarms and missed detections. The maximum likelihood data association problem is formulated as a bipartite weighted matching problem. Its duality and the optimality conditions are given. The Hungarian algorithm with its computational steps, data structure and computational complexity is presented. The two implementation versions, Hungarian forest （HF） algorithm and Hungarian tree （HT） algorithm, and their combination with the naYve auction initialization are discussed. The computational results show that HT algorithm is slightly faster than HF algorithm and they are both superior to the classic Munkres algorithm.
基金This project was supported by the National Natural Science Foundation of China (60172033) the Excellent Ph.D.PaperAuthor Foundation of China (200036 ,200237) .
文摘Aiming at three-passive-sensor location system, a generalized 3-dimension （3-D） assignment model is constructed based on property information, and a multi-target programming model is proposed based on direction-finding and property fusion information. The multi-target programming model is transformed into a single target programming problem to resolve, and its data association result is compared with the results which are solved by using one kind of information only. Simulation experiments show the effectiveness of the multi-target programming algorithm with higher data association accuracy and less calculation.
基金the Youth Science and Technology Foundection of University of Electronic Science andTechnology of China (JX0622).
文摘In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too close to each other. To enhance the tracking accuracy, the target signal classification information （TSCI） should be used to improve the data association. The TSCI is integrated in the data association process using the JPDA （joint probabilistic data association）. The use of the TSCI in the data association can improve discrimination by yielding a purer track and preserving continuity. To verify the validity of the application of TSCI, two simulation experiments are done on an air target-tracing problem, that is, one using the TSCI and the other not using the TSCI. The final comparison shows that the use of the TSCI can effectively improve tracking accuracy.
文摘The conventional complete association rule set was replaced by the least association rule set in data warehouse association rule mining process. The least association rule set should comply with two requirements: 1) it should be the minimal and the simplest association rule set; 2) its predictive power should in no way be weaker than that of the complete association rule set so that the precision of the association rule set analysis can be guaranteed. By adopting the least association rule set, the pruning of weak rules can be effectively carried out so as to greatly reduce the number of frequent itemset, and therefore improve the mining efficiency. Finally, based on the classical Apriori algorithm, the upward closure property of weak rules is utilized to develop a corresponding efficient algorithm.
基金Projects(10871031, 60474070) supported by the National Natural Science Foundation of ChinaProject(07A001) supported by the Scientific Research Fund of Hunan Provincial Education Department, China
文摘Based on the rough set theory which is a powerful tool in dealing with vagueness and uncertainty, an algorithm to mine association rules in incomplete information systems was presented and the support and confidence were redefined. The algorithm can mine the association rules with decision attributes directly without processing missing values. Using the incomplete dataset Mushroom from UCI machine learning repository, the new algorithm was compared with the classical association rules mining algorithm based on Apriori from the number of rules extracted, testing accuracy and execution time. The experiment results show that the new algorithm has advantages of short execution time and high accuracy.
基金The project supported by the Bio-Synergy Research Project(NRF-2012M3A9C4048758)of the Ministry of Science,ICT and Future Planning through the National Research Foundation
文摘OBJECTIVE To identify compound combinations as candidate multi-component drugs for the type 2 diabetes from natural product information.METHODS Chemical composition information of herbs in natural medicine was acquired by integrating conventional databases;Traditional Chinese Medicine Information Database(TCM-ID)and Traditional Chinese Medicine Integrated Database(TCMID).Therapeutic effect of each herb on the type 2 diabetes was examined by analyzing annotated function information with a text-mining method.The Apriori algorithm,which is a classical method for extracting associations between object in large-scale databases,was employed to infer association rules between compound combinations and therapeutic effect on the target disease.The chemical composition and therapeutic information of each herb was used as a transaction,which consists of the chemical compound combination as an antecedent item set and the therapeutic effect as a consequent item.The association rules with high support and confidence value were suggested as candidate multi-component drugs for the type 2 diabetes.RESULTS Totally 40 941 association rules were inferred with support lower bound 0.05% and maximum rule length 4.With respect to support and confidence,the top-ranked compound combination was puerarin and daidzin(support=0.15%,confidence=100%).In addition,the top 16 compound combinations were composed of 11 individual chemical compounds;puerarin,daidzin,abscisic acid,batatisine,dopamine,cholesterol,daidzein,gamma-aminobutyric acid,stigmasterol,campesteryl ferulate,and campesterol.To validate therapeutic effect of the proposed compound combinations,literature evidences of each individual compound were investigated.Among the 11 individual compounds,six compounds were reported to be effective for the treatment of the diabetes mellitus.CONCLUSION By analyzing natural product in formation with association rule mining,16 compound combinations are suggested as candidate multi-component drugs for the type 2 diabetes.These compound combinations are recommended for further investigation in the context of drug development.
文摘Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space, through constructing its state （abnormality） relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validiw is proved through case.
基金This work was supported by the National Natural Science Foundation of China(31760402)Young and Middle-aged Science and Technology Leading Talents of Xinjiang Production and Construction Corps(2019CB027).
文摘Background: Cotton fiber yield is a complex trait,which can be influenced by multiple agronomic traits.Unravelling the genetic basis of cotton fiber yield-related traits contributes to genetic improvement of cotton.Results: In this study,503 upland cotton varieties covering the four breeding stages(BS1–BS4,1911–2011)in China were used for association mapping and domestication analysis.One hundred and forty SSR markers significantly associated with ten fiber yield-related traits were identified,among which,29 markers showed an increasing trend contribution to cotton yield-related traits from BS1 to BS4,and 26 markers showed decreased trend effect.Four favorable alleles of 9 major loci(R^(2)≥3)were strongly selected during the breeding stages,and the candidate genes of the four strongly selected alleles were predicated according to the gene function annotation and tissue expression data.Conclusions :The study not only uncovers the genetic basis of 10 cotton yield-related traits but also provides genetic evidence for cotton improvement during the cotton breeding process in China.
文摘Jinshajiang melange belt locates between Jianda\|Weixi island arc and Zhongzha massif. The melange belt and island arc makes up Jinshajiang plate junction. Although subsequent tectonic movements had complexed the structural form of Jinshajiang melange belt, there are still a lots of structural block remained which carried amount of information about the tectonic evolution of the belt. Recent researches have identified several kinds of rock association in the structural blocks.(1) Ophiolite:The ophiolite consists of serpentinization ultramafite, ultramafic cumulus crystal rock (pyroxenite, dunite), gabbro, diabase cluster, ocean\|ridge type basalt, plagiogranite and radiolarian silicalite. The isotopic age shows that the ultramafite and basalt formed during Upper Carboniferous and Lower Permian. The silicalite is high in radiolaria of Lower Permian.(2) Rock association of oceanic island\|arc:The liptocoenosis of oceanic island\|arc scatter in melange belt, it mainly consists of sandy slate, pyroclastic rock, silicalite, basalt and andesite. A part of volcanic rock belongs to calc\|alkaline volcanic suite and the other is tholeiite. The petrochemistry, REE and microelement of volcanic rock have the feature of the rock in ocean\|island arc. The isotopic age of basalt shows that the ocean\|island arc formed in Lower Permian.
文摘Aim Clopidogrel therapy is associated with a substantial variability in pharmacokinetics （PK） and pharmacodynamics （PD） responses. To date, known gene variants explain only a small proportion of the variabili- ty. A genome-wide association study （GWAS） was conducted to identify new genetic loci modifying PD responses to clopidogrel in Chinese patients with coronary heart disease （CHD）. The initial GWAS by combination analysis of PIL/PD included 115 patients with CHD. The PK validation included 31 patients with CHD and the metabolizing functional validation included 32 human liver tissues. We identified novel variants in two transporter genes （ rs12456693 in SLC14A2 and kgpl 1138762 in ABCA1 ） and in N6AMT1 （rs2254638） associated with not only clo- pidogrel on-treated P2Y12 reaction unit （PRU） （P 〈 1 × 10^-4） , but also plasma clopidogrel active metabolite H4 concentration （P 〈 1 × 10^-2）. The significant association between rs12456693, kgpl 1138762, or rs2254638 and PK parameters of clopidogrel （P 〈 1 × 10^-2） was observed in additional CHD patients. Further, the N6AMT1 rs2254638 T variant was found to be associated decreased activation of clopidogrel （P -3.86 × 10^-2）. The new variants in N6AMT1 and ABCA1, together with CYP2C19 ＊ 2, dramatically improve the predictability of PRU varia- bility to 37.7% compared with the published value of approximately 20%. The present study identifies novel genet- ic loci modifying PIL/PD responses to clopidogrel, which contributes to a better understanding of the absorption and metabolic mechanisms that influence PD responses to clopidogrel treatment.
基金The project supported by National Natural Science Foundation of China(81373486)Science and Technology Development Projects of Guangdong Province,China(2016B090918114,2013B021800157)Science and Technology Development Projects of Guangzhou,Guangdong,China(201510010236,201604020096)
文摘OBJECTIVE Genetic variants in the pharmacokinetic(PK)mechanism are the main underlying factors that modify the antiplatelet efficacy of clopidogrel.Hence,joint analysis of genetic variants that modify pharmacodynamic(PD)and PK responses to clopidogrel should be effective for identifying the genetic variants affecting the antiplatelet response to the drug.METHODS A genome-wide association study was conducted to identify new genetic loci that modify PD responses to clopidogrel and its active metabolite H4 in 115 Chinese patients with coronary heart disease(CHD).RESULTS We identified novel variants in two transporter genes(rs12456693 in SLC14A2 and rs2487032 in ABCA1)and in N6AMT1(rs2254638)associated with clopidogrel-treated P2Y12reaction unit(PRU)and plasma H4 concentration.The associations between these single nucleotide polymorphisms(SNPs)and PK parameters of clopidogrel and H4 were observed in 31 additional CHD patients(P<0.05).The new variants,together with CYP2C19*2 and clinical factors,dramatically improved the predictability of PRU variability to 37.7%compared with the published value of approximately 20%.The function of these SNPs on the activation of clopidogrel was validated in 32 liver S9 fractions,and the N6AMT1 rs2254638 T variant was found to be associated with decreased formation of H4(P=0.0386).Meanwhile,N6AMT1 rs2254638 was further identified to exert a marginal risk effect for MACE in an independent CHD patient cohort(OR:1.428,95%CI:0.978-2.086,P=0.0653,FDR=0.4726).In conclusion,we systematically identified new genetic variants as risk factors for the reduced efficacy of clopidogrel.CONCLUSION Our study findings enhanced the understanding of the absorption and metabolic mechanisms that influence PD responses to clopidogrel treatment.
文摘Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association （DA） algorithm not combined with directional information.
文摘Time:October 15-17,2017Venue:San Diego,California,USA Website:2017.myana.org Abstract deadline:September 11,2017The 142nd Annual Meeting of American Neurological Association(ANA2017)will be held on October 15-17,2017 in
文摘A new algorithm for mining quantitative association rules with standard SQL is presented. The association rules are evaluated with the sufficiency gene LS of subjectivity Bayes reasoning. This algorithm is proved to be quick and effective with its application in Lujiang insects and pests database.
基金supported by funding from the fund for National Key Research and Development Program of China(2023YFD2301203-05)National Natural Science Foundation of China(32260510)+3 种基金Special Financial Project for Seed Industry Development in the Autonomous Region(BNZJ2024-10,BNZJ2024-30)Key Project for Science and Technology Development of Shihezi city,Xinjiang Production and Construction Crops(2022NY01)Shihezi University high-level talent research project(RCZK202337)Science and Technol-ogy Planning of Shuanghe city,Xinjiang Production and Construction Crops(2021NY02).
文摘Background Cotton is an important cash crop in China and a key component of the global textile market.Verticil-lium wilt is a major factor affecting cotton yield.Single nucleotide polymorphism(SNP)markers and phenotypic data can be used to identify genetic markers and loci associated with cotton resistance to Verticillium wilt.We used eight upland cotton parent materials in this study to construct a multiparent advanced generation inter-cross(MAGIC)population comprising 320 lines.The Verticillium wilt resistance of the MAGIC population was identified in the green-house in 2019,and the average relative disease index(ARDI)was calculated.A genome-wide association study(GWAS)was performed to discover SNP markers/genes associated with Verticillium wilt resistance.Results ARDI of the MAGIC population showed wide variation,ranging from 16.7 to 79.4 across three replicates.This variation reflected a diverse range of resistance to Verticillium wilt within the population.Analysis of distribution pat-terns across the environments revealed consistent trends,with coefficients of variation between 12.25%and 21.96%.Families with higher ARDI values,indicating stronger resistance,were more common,likely due to genetic diver-sity and environmental factors.Population structure analysis divided the MAGIC population into three subgroups,with Group I showing higher genetic variation and Groups II and III displaying more uniform resistance performance.Principal component analysis(PCA)confirmed these divisions,highlighting the genetic diversity underlying Verticil-lium wilt resistance.Through GWAS,we identified 19 SNPs significantly associated with Verticillium wilt resistance,distributed across three chromosomes.The screening of candidate genes was performed on the transcriptome derived from resistant and susceptible cultivars,combined with gene annotation and tissue expression patterns,and two key candidate genes,Ghir_A01G006660 and Ghir_A02G008980,were found to be potentially associated with Verticillium wilt resistance.This suggests that these two candidate genes may play an important role in responding to Verticillium wilt.Conclusion This study aims to dissect the genetic basis of Verticillium wilt resistance in cotton by using a MAGIC population and GWAS.The study seeks to provide valuable genetic resources for marker-assisted breeding and enhance the understanding of resistance mechanisms to improve cotton resilience against Verticillium wilt.
