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Dan Gusfield

Researcher at University of California, Davis

Publications -  152
Citations -  13585

Dan Gusfield is an academic researcher from University of California, Davis. The author has contributed to research in topics: Perfect phylogeny & Time complexity. The author has an hindex of 43, co-authored 152 publications receiving 13255 citations. Previous affiliations of Dan Gusfield include University of California, Irvine & Yale University.

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Book

Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology

TL;DR: In this paper, the authors introduce suffix trees and their use in sequence alignment, core string edits, alignments and dynamic programming, and extend the core problems to extend the main problems.

Algorithms on strings, trees, and sequences

Dan Gusfield
TL;DR: Ukkonen’s method is the method of choice for most problems requiring the construction of a suffix tree, and it will be presented first because it is easier to understand.
Book

The Stable Marriage Problem: Structure and Algorithms

TL;DR: The authors develop the structure of the set of stable matchings in the stable marriage problem in a more general and algebraic context than has been done previously; they discuss the problem's structure in terms of rings of sets, which allows many of the most useful features to be seen as features of a moregeneral set of problems.
Journal ArticleDOI

Efficient algorithms for inferring evolutionary trees

TL;DR: These problems of inferring the evolutionary history of n objects, either from present characters of the objects or from several partial estimates of their evolutionary history, can be solved by graph theoretic methods in linear time, which is time optimal, and which is a significant improvement over existing methods.
Journal ArticleDOI

Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology

TL;DR: The author examines the importance of (sub)sequence comparison in molecular biology, core string edits, alignments and dynamic programming, and a deeper look at classical methods for exact string matching.