Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. Hover, resolving the GP problem is a fundamental requirement if  are to understand and predict phenotypes given knowledge of the genome and model dynamic proper- ties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses  observe.  discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organiza- tion.  apply this quantitative framework to an investigation of the processes involved in genetic im- provement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of envi- ronments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model.  use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to- phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improve- ment by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes. Links: http://pig.ag.uq.edu.au/qu-gene/
['M. Cooper', 'Scott C. Chapman', 'Dean W. Podlich', 'G. L. Hammer']
I am writing a research paper on a idea The GP Problem: Quantifying Gene-to-Phenotype Relationships
[{"from": "human", "value": "I am writing a research paper on a idea The GP Problem: Quantifying Gene-to-Phenotype Relationships"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. Hover, resolving the GP problem is a fundamental requirement if  are to understand and predict phenotypes given knowledge of the genome and model dynamic proper- ties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses  observe.  discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organiza- tion.  apply this quantitative framework to an investigation of the processes involved in genetic im- provement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of envi- ronments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model.  use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to- phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improve- ment by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes. Links: http://pig.ag.uq.edu.au/qu-gene/"}]