Title :
De Novo Peptide Sequencing Based on Vertex Contraction Algorithm
Author :
Wei, Zhexue ; Zhu, Daming
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
Abstract :
De novo peptide sequencing is an important method for peptide sequencing and protein identification. It can be transformed into a special case of paths avoiding forbidden pairs problem (PAFP). General PAFP is NP-complete. The definition of PAFP is the following: Given a directed acyclic graph G = (V, E), two distinguished vertices source s, sink t ∈ V , a set of forbidden pairs F ⊂ V × V, and an edge weight function w : E -+ R, asking for a maximum weight path from s to t passing at most one vertex from each forbidden pair. In the process of transformation from de novo peptide sequencing to PAFP, forbidden pairs have nested structure. We give a vertex contraction algorithm which is designed based on nested structure of forbidden pairs to solve paths avoiding forbidden pairs problem. The time complexity of vertex contraction algorithm is O(|V|3).
Keywords :
biology computing; computational complexity; directed graphs; proteins; NP-complete problem; PAFP; de novo peptide sequencing; directed acyclic graph; edge weight function; forbidden pair nested structure; paths avoiding forbidden pairs; protein identification; time complexity; vertex contraction algorithm; Algorithm design and analysis; Amino acids; Complexity theory; Dynamic programming; Educational institutions; Greedy algorithms; Peptides; de novo peptide sequencing; forbidden pairs; nested structure; vertex contraction;
Conference_Titel :
Computational Sciences and Optimization (CSO), 2012 Fifth International Joint Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4673-1365-0
DOI :
10.1109/CSO.2012.19