G
Gene Myers
Researcher at Howard Hughes Medical Institute
Publications - 7
Citations - 1082
Gene Myers is an academic researcher from Howard Hughes Medical Institute. The author has contributed to research in topics: Tracing & String (computer science). The author has an hindex of 6, co-authored 6 publications receiving 1022 citations.
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Book
Algorithms in Bioinformatics: 5th International Workshop, WABI 2005, Mallorca, Spain, October 3-6, 2005, Proceedings (Lecture Notes in Computer Science / Lecture Notes in Bioinformatics)
Rita Casadio,Gene Myers +1 more
TL;DR: In this article, the authors present an efficient reduction from constrained to unconstrained maximum agreement subtree for the maximum quartet consistency problem, which can be solved by using semi-definite programming.
Book ChapterDOI
Computability of models for sequence assembly
TL;DR: This work shows sequence assembly to be NP-hard under two different models: string graphs and de Bruijn graphs, and gives the first, to the knowledge, optimal polynomial time algorithm for genome assembly that explicitly models the double-strandedness of DNA.
Journal ArticleDOI
Clonal Development and Organization of the Adult Drosophila Central Brain
Hung-Hsiang Yu,Takeshi Awasaki,Mark David Schroeder,Fuhui Long,Jacob S. Yang,Yisheng He,Peng Ding,Jui-Chun Kao,Gloria Yueh-Yi Wu,Hanchuan Peng,Gene Myers,Tzumin Lee,Tzumin Lee +12 more
TL;DR: By determining individual NB clones and pursuing their projections into specific neuropils, this work unravels the regional development of the brain neural network in Drosophila central brain.
Journal ArticleDOI
Automatic 3D neuron tracing using all-path pruning
TL;DR: An automatic graph algorithm, called the all-path pruning (APP), to trace the 3D structure of a neuron, and it is shown that MCMR has a linear computational complexity and will converge.
Journal ArticleDOI
A system for pattern matching applications on biosequences.
Gerhard Mehldau,Gene Myers +1 more
TL;DR: ANREP provides a unified framework for almost all previously proposed biosequence patterns and extends them by providing approximate matching, a feature heretofore unavailable except for the limited case of individual sequences.