R语言 CellNOptR包 gaBinaryT1()函数中文帮助文档(中英文对照)

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gaBinaryT1(CellNOptR)
gaBinaryT1()所属R语言包：CellNOptR

                                         Genetic algorithm used to optimise a model
                                         遗传算法用于优化模型

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

This function is the genetic algorithm to be used to optimise a model by fitting to data containing one time point.
此功能被用来包含一个时间点的数据拟合优化模型的遗传算法。


用法----------Usage----------


gaBinaryT1(CNOlist, Model, SimList, indexList, sizeFac = 1e-04, NAFac = 1, initBstring, PopSize = 50, Pmutation = 0.5, MaxTime = 60, maxGens = 500, StallGenMax = 100, SelPress = 1.2, elitism = 5, RelTol = 0.1, verbose=TRUE)



参数----------Arguments----------

参数：CNOlist
a CNOlist on which the score is based (based on valueSignals[[2]], i.e. data at t1)  
其中得分是基于CNOlist（上valueSignals的基础[2]，即在T1数据）


参数：Model
a Model list  
型号列表


参数：SimList
a list that contains additional fields for the simulator, as created by prep4Sim applied to the model above  
其他领域的模拟器，作为由prep4Sim创建一个列表，其中包含应用上述模型


参数：indexList
a list of indexes of species stimulated/inhibited/signals, as produced by indexfinder applied on the model and CNOlist above  
一个物种的索引列表刺激/抑制/信号，由indexfinder生产应用模型和CNOlist以上


参数：sizeFac
the scaling factor for the size term in the objective function, default to 0.0001  
为目标函数，默认的大小任期至0.0001的比例因子


参数：NAFac
the scaling factor for the NA term in the objective function, default to 1  
为NA术语目标函数，默认为1的比例因子


参数：initBstring
an initial bitsring to be tested, should be of the same size as the number of reactions in the model above  
初始bitsring进行测试，应该是同样大小的反应，在上述模型


参数：PopSize
the population size for the genetic algorithm, default set to 50  
遗传算法的人口规模，默认设置为50


参数：Pmutation
the mutation probability for the genetic algorithm, default set to 0.5  
遗传算法的变异概率，默认设置为0.5


参数：MaxTime
the maximum optimisation time in seconds, default set to 60  
在几秒钟内最大的优化时间，默认设置为60


参数：maxGens
the maximum number of generations in the genetic algorithm, default set to 500  
几代遗传算法的最大数量，默认设置为500


参数：StallGenMax
the maximum number of stall generations in the genetic algorithm, default to 100  
失速几代人的最大数量遗传算法，默认为100


参数：SelPress
the selective pressure in the genetic algorithm, default set to 1.2  
遗传算法的选择性压力，默认设置为1.2


参数：elitism
the number of best individuals that are propagated to the next generation in the genetic algorithm, default set to 5  
传播到下一代的遗传算法在最佳个人的数量，默认设置为5


参数：RelTol
the relative tolerance for the best bitstring reported by the genetic algorithm, i.e.how different from the best solution can solutions be to be reported as well, default set to 0.1  
报告由遗传算法的最佳比特串的相对宽容，iehow最佳的解决方案不同的解决方案是可以被视为良好，默认设置报0.1


参数：verbose
logical (default to TRUE) do you want the statistics of each generation to be printed on the screen?  
逻辑（默认为true）你想印在屏幕上的每一代人的统计数字？


Details

详情----------Details----------

The whole procedure is described in details in Saez-Rodriguez et al. (2009). The basic principle is that at each generation, the algorithm evaluates a population of models based on excluding or including some gates in the initial pre-processed model (this is encoded in a bitstring with contains 0/1 entries for each gate).  The population is then evolved based on the results of the evaluation of these networks, where the evaluation is obtained by simulating the model (to steady state) under the various conditions present in the data, and then computing the squared deviation from the data, to which a penalty is added for size of the model and for species in the model that do not reach steady state.
整个过程被描述在赛斯Rodriguez等人的详细信息。 （2009年）。其基本原理是在每一代中，该算法计算人口排除或包括一些在最初的预加工模型的大门（这是在一个比特串编码与包含0/1项，每个门）模型。人口演变基于这些网络的评估，评估是通过模拟各种条件下的数据模型（稳态），然后从数据计算平方差获得的结果，其中一个点球被添加大小的模型和模型中的物种，没有达到稳定状态。


值----------Value----------

This function returns a list with elements:
这个函数返回一个元素列表：


参数：bString
the best bitstring
最好的比特串


参数：Results
a matrix with columns "Generation","Best_score","Best_bitString","Stall_Generation","Avg_Score_Gen","Best_score_Gen","Best_bit_Gen","Iter_time"
与列矩阵


参数：StringsTol
the bitstrings whose scores are within the tolerance
位串的分数是在公差


参数：StringsTolScores
the scores of the above-mentioned strings
上述字符串的分数


作者（S）----------Author(s)----------



C. Terfve




参考文献----------References----------

mammalian signal transduction, Molecular Systems Biology, 5:331, 2009.

参见----------See Also----------

GetFit, prep4Sim, indexFinder, simulatorT1
GetFit，prep4Sim，indexFinder，simulatorT1


举例----------Examples----------


data(CNOlistToy,package="CellNOptR")
data(ToyModel,package="CellNOptR")

#pre-process model[预过程模型]

indicesToy<-indexFinder(CNOlistToy,ToyModel,verbose=FALSE)
ToyNCNOindices<-findNONC(ToyModel,indicesToy,verbose=FALSE)
ToyNCNOcut<-cutNONC(ToyModel,ToyNCNOindices)
indicesToyNCNOcut<-indexFinder(CNOlistToy,ToyNCNOcut)
ToyNCNOcutComp<-compressModel(ToyNCNOcut,indicesToyNCNOcut)
indicesToyNCNOcutComp<-indexFinder(CNOlistToy,ToyNCNOcutComp)
ToyNCNOcutCompExp<-expandGates(ToyNCNOcutComp)

#optimise[优化]

ToyFields4Sim<-prep4Sim(ToyNCNOcutCompExp)
initBstring<-rep(1,length(ToyNCNOcutCompExp$reacID))
ToyT1opt<-gaBinaryT1(
        CNOlist=CNOlistToy,
        Model=ToyNCNOcutCompExp,
        SimList=ToyFields4Sim,
        indexList=indicesToyNCNOcutComp,
        initBstring=initBstring,
        maxGens=2,
        PopSize=5,
        verbose=FALSE)

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


注：
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