featureSSC(BioSeqClass)
featureSSC()所属R语言包：BioSeqClass
Feature Coding by secondary structure
二级结构的特征编码
译者：生物统计家园网 机器人LoveR
描述----------Description----------
It is suitable for peptides with odd residues and the central residue has important role.
这是适合肽奇怪的残留物和中央的残留物，具有重要的作用。
用法----------Usage----------
featureSSC(secondaryStructure, confidenceScore)
# secondary structure from DSSP database
getDSSP(pdb)
# Protein secondary structure prediction
predictPROTEUS(seq,proteus2.organism="euk")
参数----------Arguments----------
参数：secondaryStructure
a string vector for the protein secondary structure. It is consisted of three kinds of secondary structures: H = Helix, E = Beta Strand, C = Coil.
对蛋白质二级结构的字符串向量。它包括3种二级结构：高=螺旋，电子=β倍数束C =线圈。
参数：confidenceScore
a string vector for the confidence score of secondary structure prediction (0-9, 0 = low, 9 = high).
一个字符串矢量二级结构预测的信心得分（0-9，0 =低，9 =高）。
参数：pdb
a string vector for the name of pdb structure. (e.g. "43ca")
为PDB结构的名称的字符串向量。 （例如43ca“）
参数：seq
a string vector for the protein, DNA, or RNA sequences.
为蛋白质，DNA或RNA序列的字符串向量。
参数：proteus2.organism
a string for the organism of proteus2 program. This must be one of the strings "gram-", "gram+", "euk".
proteus2方案的有机体的字符串。这必须是一个字符串“克”，“克”，“EUK”。
Details
详情----------Details----------
featureSSC codes for the secondary structure of the central residue of peptides. It is suitable for peptides with odd residues and the central residue has important role.
featureSSC代码为中央残留的多肽的二级结构。这是适合肽奇怪的残留物和中央的残留物，具有重要的作用。
getDSSP returns a vector of secondary structure extracted from DSSP database (http://swift.cmbi.ru.nl/gv/dssp/).
getDSSP返回一个从DSSP的数据库（http://swift.cmbi.ru.nl/gv/dssp/）中提取的二级结构的向量。
predictPROTEUS predicts secondary structure based on protein sequence using following methods : "PROTEUS2", "PSIPRED", "JNET", "TRANSSEC", "JURY-OF-EXPERTS PREDICTION". Parameter "proteus2.organism" can be "gram-" for "Gram negative prokaryote", "gram+" for "Gram positive prokaryote", "euk" for "Eukaryote". It returns.....
predictPROTEUS预测基于蛋白质序列的二级结构用下面的方法：“PROTEUS2”，“PSIPRED”，“JNET”的，“TRANSSEC”，“陪审团专家预测”。可以参数“proteus2.organism”是“克”为“革兰氏阴性的原核生物”，“克+”，“革兰氏阳性原核生物”，“EUK”的为“真核”。它返回......
作者（S）----------Author(s)----------
Hong Li
举例----------Examples----------
if(interactive()){
file = file.path(.path.package("BioSeqClass"), "example", "acetylation_K.fasta")
tmp = readFASTA(file)
proteinSeq = sapply(tmp,function(x){x[["seq"]]})
names(proteinSeq) = sapply(tmp,function(x){x[["desc"]]})
DSSP1 = getDSSP(c("108l","43ca"))
DSSP2 = getDSSP(c("108l","43ca","aaaa"))
## Predict protein secordary strucutre [＃预测蛋白质secordary结构发生]
PROTEUS = predictPROTEUS(proteinSeq[1:2],proteus2.organism="euk")
## Use general feature conding functions to codes protein secordary strucutre [＃编码蛋白质secordary结构发生conding功能使用一般功能]
secondaryStructure = sapply(PROTEUS,function(x){paste(x[["PROTEUS2"]]$SecondaryStructure,collapse="")})
confidenceScore = sapply(PROTEUS,function(x){paste(x[["PROTEUS2"]]$ConfidenceScore,collapse="")})
SSCTD = featureCTD(secondaryStructure, class=list("H"="H","E"="E","C"="C"))
# Codes for peptides which have equal length and their central residues are important[为肽具有同等长度和中央残留的代码是很重要的]
secondaryStructure = sapply(PROTEUS,function(x){sub.seq(paste(x[["PROTEUS2"]]$SecondaryStructure,collapse=""), 1, 11)})
confidenceScore = sapply(PROTEUS,function(x){sub.seq(paste(x[["PROTEUS2"]]$ConfidenceScore,collapse=""), 1, 11)})
SS1 = featureSSC(secondaryStructure, confidenceScore)
}
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-25 13:42:34
