BLAST

Basic Local Alignment Search Tool. BLAST finds regions of similarity between biological sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance.

Keywords for this software

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References in zbMATH (referenced in 248 articles )

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  1. Berenice Talamantes-Becerra, Jason Carling, Arthur Georges: omicR: A tool to facilitate BLASTn alignments for sequence data (2021) not zbMATH
  2. Gullotto, Danilo: Fine tuned exploration of evolutionary relationships within the protein universe (2021)
  3. Ahmad, Jamal; Hayat, Maqsood: MFSC: multi-voting based feature selection for classification of Golgi proteins by adopting the general form of Chou’s PseAAC components (2019)
  4. Randić, Milan: Mathematical chemistry illustrations: a personal view of less known results (2019)
  5. Rout, Subhashree; Mahapatra, Rajani Kanta: \textitInsilico analysis of \textitplasmodiumfalciparum CDPK5 protein through molecular modeling, docking and dynamics (2019)
  6. Tao, Jin; Liu, Xiaoqing; Yang, Siqian; Bao, Chaohui; He, Pingan; Dai, Qi: An efficient genomic signature ranking method for genomic island prediction from a single genome (2019)
  7. Wang, Lei; Yan, Xin; Liu, Meng-Lin; Song, Ke-Jian; Sun, Xiao-Fei; Pan, Wen-Wen: Prediction of RNA-protein interactions by combining deep convolutional neural network with feature selection ensemble method (2019)
  8. Abboud, Amir; Bringmann, Karl: Tighter connections between formula-SAT and shaving logs (2018)
  9. Abboud, Amir; Rubinstein, Aviad: Fast and deterministic constant factor approximation algorithms for LCS imply new circuit lower bounds (2018)
  10. Charikar, Moses; Geri, Ofir; Kim, Michael P.; Kuszmaul, William: On estimating edit distance: alignment, dimension reduction, and embeddings (2018)
  11. Kinjo, Akira R.: Cooperative “folding transition” in the sequence space facilitates function-driven evolution of protein families (2018)
  12. 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)
  13. Tian, Kun; Zhao, Xin; Yau, Stephen S.-T.: Convex hull analysis of evolutionary and phylogenetic relationships between biological groups (2018)
  14. Zhang, Shengli; Liang, Yunyun: Predicting apoptosis protein subcellular localization by integrating auto-cross correlation and PSSM into Chou’s PseAAC (2018)
  15. Abboud, Amir; Backurs, Arturs: Towards hardness of approximation for polynomial time problems (2017)
  16. Dehzangi, Abdollah; López, Yosvany; Lal, Sunil Pranit; Taherzadeh, Ghazaleh; Michaelson, Jacob; Sattar, Abdul; Tsunoda, Tatsuhiko; Sharma, Alok: PSSM-Suc: accurately predicting succinylation using position specific scoring matrix into bigram for feature extraction (2017)
  17. Pai, Priyadarshini P.; Dash, Tirtharaj; Mondal, Sukanta: Sequence-based discrimination of protein-RNA interacting residues using a probabilistic approach (2017)
  18. Shatabda, Swakkhar; Saha, Sanjay; Sharma, Alok; Dehzangi, Abdollah: iPHLoc-ES: identification of bacteriophage protein locations using evolutionary and structural features (2017)
  19. Beg, Ismat; Rashid, Tabasam: Intuitionistic fuzzy similarity measure: theory and applications (2016)
  20. Jiao, Ya-Sen; Du, Pu-Feng: Predicting Golgi-resident protein types using pseudo amino acid compositions: approaches with positional specific physicochemical properties (2016)

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