Fundamentals
Arvind Kumar Bansal, Javed Iqbal Khan, S. Kaisar Alam in Introduction to Computational Health Informatics, 2019
Dynamic programming is a matrix-based variant of approximate string matching technique for aligning the characters in two similar nucleotide or amino-acid sequences using three operations: insertion, deletion or substitution. The rows represent one sequence, and the columns represent another sequence. The overall matching function is defined as given in Equation 2.9. A mismatch is penalized, and a match is rewarded by adding a positive similarity-score that is looked-up from a standardized biochemical matrix. For matching amino-acid sequences, BLOSUM (BLOcks SUbstitution Matrix) or PAM (Point Accepted Mutation) matrices are used that show similarity-score for different pairs of amino-acids.
Predicting T cell recognition of MHC class I restricted neoepitopes
Published in OncoImmunology, 2018
Zeynep Koşaloğlu-Yalçın, Manasa Lanka, Angela Frentzen, Ashmitaa Logandha Ramamoorthy Premlal, John Sidney, Kerrie Vaughan, Jason Greenbaum, Paul Robbins, Jared Gartner, Alessandro Sette, Bjoern Peters
To assess the similarity of the mutated epitopes and their non-mutated counterparts, we used a BLOSUM matrix, which is based on the frequency of amino acid substitutions observed in evolutionarily related protein sequences.71,72 A BLOSUM matrix contains log-odds scores for each of the possible substitutions of the 20 amino acids, where highly conserved amino acids have the highest scores, while non-conservative substitutions have negative scores. We used the BLOSUM62 matrix, which is generated based on protein sequence alignments of 62% identity or less. For each pair of the mutated epitope and corresponding non-mutant peptide, we calculated the similarity score as previously described. 73 Briefly, for two peptides a and b the similarity score is calculated as the BLOSUM score for a and b divided by the square root of the product of the BLOSUM scores of the two peptides aligned to themselves. This method assigns two identical peptides a similarity score of 1.
Immune-based mutation classification enables neoantigen prioritization and immune feature discovery in cancer immunotherapy
Published in OncoImmunology, 2021
Peng Bai, Yongzheng Li, Qiuping Zhou, Jiaqi Xia, Peng-Cheng Wei, Hexiang Deng, Min Wu, Sanny K. Chan, John W. Kappler, Yu Zhou, Eric Tran, Philippa Marrack, Lei Yin
Amino acid dissimilarity comparison of wild-type and mutant amino acids was taken for peptide pairs between immunogenic and ineffective cohorts based on the BLOSUM50 matrix.30 This matrix provided BLOSUM scores represented the similarity of amino acid pairs (higher score indicates more similar). Tails of the violins to the range of the data were not trimmed. The figure was generated by R. Statistical analyses were calculated by Wilcoxon test.
Comparative genome analysis of Alkhumra hemorrhagic fever virus with Kyasanur forest disease and tick-borne encephalitis viruses by the in silico approach
Published in Pathogens and Global Health, 2018
Navaneethan Palanisamy, Dario Akaberi, Johan Lennerstrand, Åke Lundkvist
Sequence (nucleotide or protein) identity and similarity were studied using the matrix global alignment tool (MatGAT) with default parameters [17]. While studying the similarity of the protein sequences, the BLOSUM62 matrix was used. Additionally, we also used the sequence identity and similarity (SIAS) server (http://imed.med.ucm.es/Tools/sias.html) to verify the MatGAT results.
Related Knowledge Centers
- Bioinformatics
- Cell Division
- Conserved Sequence
- Divergent Evolution
- Protein
- Amino Acid
- Substitution Matrix
- Odds Ratio
- Point Accepted Mutation
- Cell