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BMCBI
2006
137views more  BMCBI 2006»
13 years 7 months ago
A maximum likelihood framework for protein design
Background: The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, thi...
Claudia L. Kleinman, Nicolas Rodrigue, Céci...
BMCBI
2007
145views more  BMCBI 2007»
13 years 7 months ago
Improved benchmarks for computational motif discovery
Background: An important step in annotation of sequenced genomes is the identification of transcription factor binding sites. More than a hundred different computational methods h...
Geir Kjetil Sandve, Osman Abul, Vegard Walseng, Fi...
CN
2007
167views more  CN 2007»
13 years 7 months ago
Association management for data dissemination over wireless mesh networks
To enable multimedia broadcasting services in mesh networks, it is critical to optimize the broadcast traffic load. Traditionally, users associate with access points (APs) with th...
Dongwook Lee, Gayathri Chandrasekaran, Mukundan Sr...
JACM
2006
99views more  JACM 2006»
13 years 7 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller
JCB
2006
107views more  JCB 2006»
13 years 7 months ago
Maximum Likelihood Molecular Clock Comb: Analytic Solutions
Maximum likelihood (ML) is increasingly used as an optimality criterion for selecting evolutionary trees, but finding the global optimum is a hard computational task. Because no g...
Benny Chor, Amit Khetan, Sagi Snir