PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions. The avalanche of genomic sequences generated in the post-genomic age requires efficient computational methods for rapidly and accurately identifying biological features from sequence information. Towards this goal, we developed a freely available and open-source package, called PseKNC-General (the general form of pseudo k-tuple nucleotide composition), that allows for fast and accurate computation of all the widely used nucleotide structural and physicochemical properties of both DNA and RNA sequences. PseKNC-General can generate several modes of pseudo nucleotide compositions, including conventional k-tuple nucleotide compositions, Moreau–Broto autocorrelation coefficient, Moran autocorrelation coefficient, Geary autocorrelation coefficient, Type I PseKNC and Type II PseKNC. In every mode, >100 physicochemical properties are available for choosing. Moreover, it is flexible enough to allow the users to calculate PseKNC with user-defined properties. The package can be run on Linux, Mac and Windows systems and also provides a graphical user interface.
Keywords for this software
References in zbMATH (referenced in 6 articles )
Showing results 1 to 6 of 6.
- Jia, Jianhua; Liu, Zi; Xiao, Xuan; Liu, Bingxiang; Chou, Kuo-Chen: pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach (2016)
- Jiao, Ya-Sen; Du, Pu-Feng: Predicting Golgi-resident protein types using pseudo amino acid compositions: approaches with positional specific physicochemical properties (2016)
- Yang, Lianping; Zhang, Xiangde; Fu, Haoyue; Yang, Chenhui: An estimator for local analysis of genome based on the minimal absent word (2016)
- Ali, Farman; Hayat, Maqsood: Classification of membrane protein types using voting feature interval in combination with Chou’s pseudo amino acid composition (2015)
- Ju, Zhe; Cao, Jun-Zhe; Gu, Hong: iLM-2L: a two-level predictor for identifying protein lysine methylation sites and their methylation degrees by incorporating K-gap amino acid pairs into Chou’s general PseAAC (2015)
- Liu, Guoqing; Xing, Yongqiang; Cai, Lu: Using weighted features to predict recombination hotspots in \itSaccharomyces cerevisiae (2015)