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trace4all
- 基于＂trace transform＂的识别２Ｄ图像的Ｃ＋＋源程序， 主文件是tt.cpp， 在ＬＩＮＵＸ下可以用 g++ tt.cpp -o tt -O3进行编绎， 而且最后的结果也可以在ＭＡＴＬＡＢ下显示出来， This package presents C++ tools to the trace transform of a 2D image, and related objects, i.e. circuses and triple features, matlab
genetic_algorithm_code
- 基本遗传学习分类系统 A Simple Classifier System based on Genetic Learning developed from the Pascal SCS code presented by David E.Goldberg -learning basic genetic classification system for A Simple Classifier System bas ed on Genetic Learning developed fro
icaML
- This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixin
Appartenance
- flou ùe,bership function
generateROC
- Generates the values in a ROC curve given a similarity matrix. For use in evaluation of biometric recognition systems (e.g. fingerprint, face, iris, etc.)
Opeorn-presequence
- 提取Operon的前序序列。在生物信息领域，处理微生物信息时，经常会要提取其操纵子的前序序列。由于操纵子的命名诡异，所以提取时经常较为困难。本程序以大肠杆菌为模式生物完成了此操作-Extract the pre-sequence of operons. In the field of bioinformatics, when processing with microbes, we often need to draw the pre-sequence of their operons. Due
mobilty_cells_within_cells
- cells within cell,i.e. depiction of cell zoomin technique
match
- perl编写。从NCBI中下载的编码区序列，比如整个大肠杆菌编码序列，下载下来是fasta格式的一个文档，这个程序可以让你从中提取想要的gene name。把想提取的gene name放到一个文本中，比如基因序列.txt-written in perl. Downloaded from NCBI coding region sequence, for example, the entire coding sequence of E. coli, downloaded the fasta form
script1.tar
- 为了加入这个网站，我把心血分享给大家，绝对都是原创！ A：mkdatabas0.cpp 做blast前对大的非冗余NR或者是uniref数据库的预处理。为每条序列计算出等长的（长度为20*19/2=210）的数值数组。用来后期比较各个序列间的距离做准备。 B：mkdatabas.cpp 是通过比较要blast对象的那条序列和reference序列的距离，提出距离过远序列。用得到的新数据库做blast。 C：dl_fa.pl程序比较简单，但很实用，可以批量的从网站下载想要的fasta序
geneAttribution_1.0.0.tar
- Identification of the most likely gene or genes through which variation at a given genomic locus in the human genome acts. The most basic functionality assumes that the closer gene is to the input locus, the more likely the gene is to be causative. A