AAindex: amino acid index database. AAindex is a database of numerical indices representing various physicochemical and biochemical properties of amino acids and pairs of amino acids. It consists of two sections: AAindex1 for the amino acid index of 20 numerical values and AAindex2 for the amino acid mutation matrix of 210 numerical values. Each entry of either AAindex1 or AAindex2 consists of the definition, the reference information, a list of related entries in terms of the correlation coefficient, and the actual data. The database may be accessed through the DBGET/LinkDB system at GenomeNet (http://www.genome.ad. jp/dbget/) or may be downloaded by anonymous FTP (ftp://ftp.genome. ad.jp/db/genomenet/aaindex/)

References in zbMATH (referenced in 47 articles )

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  1. Khorsand, Babak; Savadi, Abdorreza; Zahiri, Javad; Naghibzadeh, Mahmoud: Alpha influenza virus infiltration prediction using virus-human protein-protein interaction network (2020)
  2. Ning, Qiao; Ma, Zhiqiang; Zhao, Xiaowei: Dforml(KNN)-PseAAC: detecting formylation sites from protein sequences using K-nearest neighbor algorithm via Chou’s 5-step rule and pseudo components (2019)
  3. Zhao, Wei; Li, Guang-Ping; Wang, Jun; Zhou, Yuan-Ke; Gao, Yang; Du, Pu-Feng: Predicting protein sub-Golgi locations by combining functional domain enrichment scores with pseudo-amino acid compositions (2019)
  4. Henriques, Rui; Francisco, Alexandre P.; Russo, Luís M. S.; Bannai, Hideo: Order-preserving pattern matching indeterminate strings (2018)
  5. Ju, Zhe; Wang, Shi-Yun: Prediction of S-sulfenylation sites using mRMR feature selection and fuzzy support vector machine algorithm (2018)
  6. Liang, Yunyun; Zhang, Shengli: Identify Gram-negative bacterial secreted protein types by incorporating different modes of PSSM into Chou’s general PseAAC via Kullback-Leibler divergence (2018)
  7. Jiao, Ya-Sen; Du, Pu-Feng: Predicting Golgi-resident protein types using pseudo amino acid compositions: approaches with positional specific physicochemical properties (2016)
  8. Jiao, Ya-Sen; Du, Pu-Feng: Prediction of Golgi-resident protein types using general form of Chou’s pseudo-amino acid compositions: approaches with minimal redundancy maximal relevance feature selection (2016)
  9. Arango-Argoty, G. A.; Jaramillo-Garzón, J. A.; Castellanos-Domínguez, G.: Feature extraction by statistical contact potentials and wavelet transform for predicting subcellular localizations in gram negative bacterial proteins (2015)
  10. Li, Limin; Aoki-Kinoshita, Kiyoko F.; Ching, Wai-Ki; Jiang, Hao: On using physico-chemical properties of amino acids in string kernels for protein classification via support vector machines (2015)
  11. Han, Guo-Sheng; Yu, Zu-Guo; Anh, Vo: A two-stage SVM method to predict membrane protein types by incorporating amino acid classifications and physicochemical properties into a general form of Chou’s PseAAC (2014)
  12. Marquez-Chamorro, Alfonso Eduardo; Asencio-Cortes, Gualberto; Divina, Federico; Aguilar-Ruiz, Jesus Salvador: Evolutionary decision rules for predicting protein contact maps (2014)
  13. Ma, Xin; Sun, Xiao: Sequence-based predictor of ATP-binding residues using random forest and mrmr-IFS feature selection (2014)
  14. Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra: Prediction of protein structure classes by incorporating different protein descriptors into general Chou’s pseudo amino acid composition (2014)
  15. Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra; Barrier, Tonya: Ensemble of local phase quantization variants with ternary encoding (2014) ioport
  16. Nanni, Loris; Lumini, Alessandra; Brahnam, Sheryl: A set of descriptors for identifying the protein-drug interaction in cellular networking (2014)
  17. Pavesi, Angelo: Prediction of the determinants of thermal stability by linear discriminant analysis: the case of the glutamate dehydrogenase protein family (2014)
  18. Yang, Lei; Lv, Yingli; Li, Tao; Zuo, Yongchun; Jiang, Wei: Human proteins characterization with subcellular localizations (2014)
  19. Chen, Yen-Kuang; Li, Kuo-Bin: Predicting membrane protein types by incorporating protein topology, domains, signal peptides, and physicochemical properties into the general form of Chou’s pseudo amino acid composition (2013)
  20. Zhang, Wenyi; Xu, Xin; Jia, Longjia; Ma, Zhiqiang; Luo, Na; Wang, Jianan: The prediction of calpain cleavage sites with the mrmr and IFS approaches (2013) ioport

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