Objective： The progression of human cancer is characterized by the accumulation of genetic instability. An increasing number of experimental genetic molecular techniques have been used to detect chromosome aberration...Objective： The progression of human cancer is characterized by the accumulation of genetic instability. An increasing number of experimental genetic molecular techniques have been used to detect chromosome aberrations. Previous studies on chromosome abnormalities often focused on identifying the frequent loci of chromosome alterations, but rarely addressed the issue of interrelationship of chromosomal abnormalities. In the last few years, several mathematical models have been employed to construct models of carcinogenesis, in an attempt to identify the time order and cause-and-effect relationship of chromosome aberrations. The principles and applications of these models are reviewed and compared in this paper. Mathematical modeling of carcinogenesis can contribute to our understanding of the molecular genetics of tumor development, and identification of cancer related genes, thus leading to improved clinical practice of cancer.展开更多
Aiming at assembly line balancing problem,a double chromosome genetic algorithm(DCGA)is proposed to avoid trapping in local optimum,which is a disadvantage of standard genetic algorithm(SGA).In this algorithm,there ar...Aiming at assembly line balancing problem,a double chromosome genetic algorithm(DCGA)is proposed to avoid trapping in local optimum,which is a disadvantage of standard genetic algorithm(SGA).In this algorithm,there are two chromosomes of each individual,and the better one,regarded as dominant chromosome,determines the fitness.Dominant chromosome keeps excellent gene segments to speed up the convergence,and recessive chromosome maintains population diversity to get better global search ability to avoid local optimal solution.When the amounts of chromosomes are equal,the population size of DCGA is half that of SGA,which significantly reduces evolutionary time.Finally,the effectiveness is verified by experiments.展开更多
Evaluation of the genetic effect on yield and fiber quality can provide useful information on cotton breeding. Sixteen CSB lines and TM-1 introduced from USDA/ARS were used as male and top-crossed with three elite cul...Evaluation of the genetic effect on yield and fiber quality can provide useful information on cotton breeding. Sixteen CSB lines and TM-1 introduced from USDA/ARS were used as male and top-crossed with three elite cultivars and the 51 F1 hybrids, 16 CSB lines, TM-1, and 3 elite cultivars were planted at the Cotton Research Institute of CAAS, Anyang, Henan Province and Xiajin, Shandong Province, China. The yield traits and fiber quality data were obtained and additive and dominance effect on each trait were measured by AD model. Boll weight takes the largest additive proration, whereas boll number takes the least additive proration. The largest and the least dominant proration for lint yield and boll weight were measured, respectively. Fiber length has the additive and dominance effect, and dominance effect was slightly more than additive effect. Larger additive and no dominance effect on uniformity, micronaire, and fiber strength were measured. Significantly, positive additive effect on boll weight of CSB06 and CSB12Sh was observed. CSB14Sh and CSB01 have significantly positive additive effect on 4 and 3 traits of fiber quality, respectively. CSB01 has the greatest dominant effect on lint yield among CSB lines. The dominant effect on fiber length of CSB lines showed positive. It is beneficial to use CSB06 and CSB12Sh as parents to improve boll size, to use CSB14Sh and CSB01 as parents to improve fiber quality. As for hybrid cotton breeding, it is reasonable using CSB01 to improve lint yield traits, and using CSB01, CSB11Sh, and CSB06 to improve fiber length.展开更多
The organized three-dimensional chromosome architecture in the cell nucleus provides scaffolding for precise regulation of gene expression.When the cell changes its identity in the cell-fate decision-making process,ex...The organized three-dimensional chromosome architecture in the cell nucleus provides scaffolding for precise regulation of gene expression.When the cell changes its identity in the cell-fate decision-making process,extensive rearrangements of chromo-some structures occur accompanied by large-scale adaptations of gene expression,underscoring the importance of chromosome dynamics in shaping genome function.Over the last two decades,rapid development of experimental methods has provided unprecedented data to characterize the hierarchical structures and dynamic properties of chromosomes.In parallel,these enormous data offer valuable opportunities for developing quantitative computational models.Here,we review a variety of large-scale polymer models developed to investigate the structures and dynamics of chromosomes.Different from the underlying modeling strategies,these approaches can be classified into data-driven(‘top-down’)and physics-based(‘bottom-up’)categories.We discuss their contributions to offering valuable insights into the relationships among the structures,dynamics,and functions of chromosomes and propose the perspective of developing data integration approaches from different experimental technologies and multidisciplinary theoretical/simulation methods combined with different modeling strategies.展开更多
基金supported by a grant from the Education Department of Zhejiang Province (No.Y200803235)
文摘Objective： The progression of human cancer is characterized by the accumulation of genetic instability. An increasing number of experimental genetic molecular techniques have been used to detect chromosome aberrations. Previous studies on chromosome abnormalities often focused on identifying the frequent loci of chromosome alterations, but rarely addressed the issue of interrelationship of chromosomal abnormalities. In the last few years, several mathematical models have been employed to construct models of carcinogenesis, in an attempt to identify the time order and cause-and-effect relationship of chromosome aberrations. The principles and applications of these models are reviewed and compared in this paper. Mathematical modeling of carcinogenesis can contribute to our understanding of the molecular genetics of tumor development, and identification of cancer related genes, thus leading to improved clinical practice of cancer.
基金Supported by the 12th Five-Year Plan National Pre-research Program of Chinathe Aerospace Science Foundation of China(20111652016)+1 种基金the China Postdoctoral Science Foundation(2012M511748)the Jiangsu Planned Projects for Postdoctoral Research Funds(1102053C)
文摘Aiming at assembly line balancing problem,a double chromosome genetic algorithm(DCGA)is proposed to avoid trapping in local optimum,which is a disadvantage of standard genetic algorithm(SGA).In this algorithm,there are two chromosomes of each individual,and the better one,regarded as dominant chromosome,determines the fitness.Dominant chromosome keeps excellent gene segments to speed up the convergence,and recessive chromosome maintains population diversity to get better global search ability to avoid local optimal solution.When the amounts of chromosomes are equal,the population size of DCGA is half that of SGA,which significantly reduces evolutionary time.Finally,the effectiveness is verified by experiments.
基金supported by the National Key Tech-nology R&D Program of China (2006BAD01A05)
文摘Evaluation of the genetic effect on yield and fiber quality can provide useful information on cotton breeding. Sixteen CSB lines and TM-1 introduced from USDA/ARS were used as male and top-crossed with three elite cultivars and the 51 F1 hybrids, 16 CSB lines, TM-1, and 3 elite cultivars were planted at the Cotton Research Institute of CAAS, Anyang, Henan Province and Xiajin, Shandong Province, China. The yield traits and fiber quality data were obtained and additive and dominance effect on each trait were measured by AD model. Boll weight takes the largest additive proration, whereas boll number takes the least additive proration. The largest and the least dominant proration for lint yield and boll weight were measured, respectively. Fiber length has the additive and dominance effect, and dominance effect was slightly more than additive effect. Larger additive and no dominance effect on uniformity, micronaire, and fiber strength were measured. Significantly, positive additive effect on boll weight of CSB06 and CSB12Sh was observed. CSB14Sh and CSB01 have significantly positive additive effect on 4 and 3 traits of fiber quality, respectively. CSB01 has the greatest dominant effect on lint yield among CSB lines. The dominant effect on fiber length of CSB lines showed positive. It is beneficial to use CSB06 and CSB12Sh as parents to improve boll size, to use CSB14Sh and CSB01 as parents to improve fiber quality. As for hybrid cotton breeding, it is reasonable using CSB01 to improve lint yield traits, and using CSB01, CSB11Sh, and CSB06 to improve fiber length.
基金supported by the National Natural Science Foundation of China(grant no.32201020)the general program(grant no.2023A04J0083)+1 种基金the Guangzhou–HKUST(GZ)joint funding program(grant no.2023A03J0060)of Guangzhou Municipal Science and Technology Projectfunded by the Municipal Key Laboratory Construction Program of Guangzhou Municipal Science and Technology Project(grant no.2023A03J0003).
文摘The organized three-dimensional chromosome architecture in the cell nucleus provides scaffolding for precise regulation of gene expression.When the cell changes its identity in the cell-fate decision-making process,extensive rearrangements of chromo-some structures occur accompanied by large-scale adaptations of gene expression,underscoring the importance of chromosome dynamics in shaping genome function.Over the last two decades,rapid development of experimental methods has provided unprecedented data to characterize the hierarchical structures and dynamic properties of chromosomes.In parallel,these enormous data offer valuable opportunities for developing quantitative computational models.Here,we review a variety of large-scale polymer models developed to investigate the structures and dynamics of chromosomes.Different from the underlying modeling strategies,these approaches can be classified into data-driven(‘top-down’)and physics-based(‘bottom-up’)categories.We discuss their contributions to offering valuable insights into the relationships among the structures,dynamics,and functions of chromosomes and propose the perspective of developing data integration approaches from different experimental technologies and multidisciplinary theoretical/simulation methods combined with different modeling strategies.
