Unlock the power of vector algorithms for fast string matching! This research explores the existence and construction of vector algorithms, focusing on applications in computational biology. It demonstrates how these algorithms can efficiently solve the problem of approximate string matching with arbitrary weighted distances. Efficient vector algorithms exist for the problem of approximate string matching with arbitrary weighted distances, generalizing a previous result by G. Myers. The paper characterizes a class of automata for which vector algorithms can be automatically derived from the transition table of the automata. This study provides valuable tools for developing extremely fast implementations in various fields, including bioinformatics and text processing.
Published in International Journal of Foundations of Computer Science, this research aligns with the journal's focus on theoretical computer science and algorithms. By presenting general results on the existence and construction of vector algorithms, this paper contributes to the journal's coverage of foundational topics in computer science.