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meme_3.5.4
- EM算法的改进，在此基础上生物信息学的常用工具-EM algorithm, on the basis of commonly used bioinformatics tools
Bioinformatics
- this a theory regarding the bioinformatics software tools-this is a theory regarding the bioinformatics software tools
yichuansuanfa
- 遗传算法在生物信息学中应用甚广，但是好的遗传算法不多。-Genetic algorithms in bioinformatics applications is very extensive, but not much good genetic algorithm.
zincidentifier
- 蛋白质锌结合位点预测的源代码，适合生物信息学初学者。-Zinc binding site prediction of protein source code, suitable for beginners bioinformatics.
CarboxySVM(Beta)
- 蛋白质位点预测的源代码，适合生物信息学初学者。-Protein gamma-carboxylation sites prediction of the source code, suitable for beginners bioinformatics.
An-Introduction-to-SVM
- 支持向量机（SVM）是在统计学习理论的基础上发展起来的新一代学习算法，该算法在文本分类、手写识别、图像分类、生物信息学等领域中获得了较好的应用。本书是SVM的权威参考书。-Support Vector Machine (SVM) is a new learning algorithm developed on the basis of statistical learning theory, the algorithm to obtain a better application in the
SVM-RFE-CBR-v1.3
- 在生物信息学中，SVM-RFE是一个强大的特征选择算法。这是一个不错的选择以避免过度拟合特性高的数量。-SVM-RFE is a powerful feature selection algorithm in bioinformatics. It is a good choice to avoid overfitting when the number of features is high.
biopython中文指南_生物信息学_超强烈推荐
- biopython中文指南_生物信息学_超强烈推荐,对于学习生物信息学，处理大数据非常的有用(For learing Bioinformatics.Biopython is much important.)
2The Elements of Statistical Learning
- This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a va
Intro to Bioinformatics Algorithms
- Intro to Bioinformatics Algorithms