title: A novel method to analyze the similarity of biological sequences.
abstract: In this paper, we propose a new method based on the 2-D graphical representation to analyze the similarity of biological sequences and classify the protein secondary structure sequences. Instead of computing some characteristics from the distance matrix, the average area surrounded by the curve and X axis is computed as a new invariant. The new method is tested on two sets: the coding sequences of 30 mitochondrial genes from NCBI and 12 protein secondary structure sequences. The similarity/disimilarity and phylogenetic tree (dendrogram) of these sequences verify the validity of our method.
authors.affiliation: Sichuan University, Chengdu, P. R. China.
authors.forename: Wei
authors.initials: W
authors.lastname: Huang
authors.forename: Ying
authors.initials: Y
authors.lastname: Guo
authors.forename: Jianmin
authors.initials: J
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D050259:Genes, Mitochondrial / Q000235:genetics*; D006801:Humans; D010802:Phylogeny; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry / Q000145:classification / Q000235:genetics*; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
chemical_list: D011506:Proteins