matlab精度检验代码-DeepAcet:预测蛋白质中赖氨酸乙酰化位点的深度学习框架
matlab精度检验代码深醋酸
预测蛋白质中赖氨酸乙酰化位点的深度学习框架
要求
Python>
=
3.6
Matlab2016a
Tensorflow
=
1.6.0
文件描述
“深度学习”文件夹中有七个子文件夹。
由这六个编码方案命名的文件夹是python代码，并且通过对通过不同编码方法获得的特征向量执行4倍交叉验证来获得预测变量。
在名为“编码方案”的文件夹中，MATLAB代码有六种不同的编码方案，分别为Aaindex，BLOSUM62，CKSAAP（K空间氨基酸对的组成），IG（信息增益）One-hot和PSSM（位置特定计分）矩阵）。
这些程序可以将蛋白质片段编码为不同尺寸的特征向量。
名为“蛋白质捕获”的文件夹是一种蛋白质拦截程序，能够将蛋白质解释为长度相等的以赖氨酸为中心的片段。
（注意：运行该程序时，将FASTA文件和蛋白质ID文件放在此文件夹中）
名为“功能组合”的文件夹包含通过将六种编码方法与F分数组合而获得的最佳模型。
（注意：在运行该程序时，将编码测试集放入文件夹中，并且该文件夹中的所有文件应位于同一路径中）
六种编码方式介绍
一键编码
在乙酰化位点附近的小范
文件下载
资源详情
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