Flexible sequence similarity searching with the FASTA3 program package. Since the publication of the first rapid method for comparing biological sequences 15 years ago (1), DNA and protein sequence comparisons have become routine steps in biochemical characterization, from newly cloned proteins to entire genomes. As the DNA and protein sequence databases become more complete, a sequence similarity search is more likely to reveal a database sequence with statistically significant similarity, and thus inferred homology, to a query sequence. Indeed, even in the archaebacterium Methanococcus jannaschii, more than 40% of the open reading frames could be assigned a function based on significant sequence similarity to a protein of known function (2).

References in zbMATH (referenced in 7 articles )

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  1. Keith, Jonathan M. (ed.): Bioinformatics. Volume I. Data, sequence analysis, and evolution (2017)
  2. F├╝rstberger, Axel; Maucher, Markus; Kestler, Hans A.: Extended pairwise local alignment of wild card DNA/RNA sequences using dynamic programming (2015)
  3. Uno, Takeaki: Multi-sorting algorithm for finding pairs of similar short substrings from large-scale string data (2010) ioport
  4. Agrawal, Ankit; Huang, Xiaoqiu: Pairwise statistical significance of local sequence alignment using multiple parameter sets and empirical justification of parameter set change penalty (2009) ioport
  5. Wang, Kai; Samudrala, Ram: Automated functional classification of experimental and predicted protein structures (2006) ioport
  6. Wen, Zhining; Wang, Kelong; Li, Menglong; Nie, Fusheng; Yang, Yi: Analyzing functional similarity of protein sequences with discrete wavelet transform (2005)
  7. Wang, Xiangyun; Schroeder, Diane; Dobbs, Drena; Honavar, Vasant: Automated data-driven discovery of motif-based protein function classifiers. (2003) ioport