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JACM
2006
99views more  JACM 2006»
15 years 3 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
BMCBI
2005
122views more  BMCBI 2005»
15 years 3 months ago
Bayesian coestimation of phylogeny and sequence alignment
Background: Two central problems in computational biology are the determination of the alignment and phylogeny of a set of biological sequences. The traditional approach to this p...
Gerton Lunter, István Miklós, Alexei...
BMCBI
2005
198views more  BMCBI 2005»
15 years 3 months ago
Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural
Background: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of t...
Qicheng Ma, Gung-Wei Chirn, Richard Cai, Joseph D....
PAMI
2002
149views more  PAMI 2002»
15 years 3 months ago
Region Tracking via Level Set PDEs without Motion Computation
Tracking regions in an image sequence is a challenging and di cult problem in image processing and computer vision, and at the same time, one that has many important applications:...
Abdol-Reza Mansouri
DAS
2010
Springer
15 years 2 months ago
Automatic unsupervised parameter selection for character segmentation
A major difficulty for designing a document image segmentation methodology is the proper value selection for all involved parameters. This is usually done after experimentations o...
Georgios Vamvakas, Nikolaos Stamatopoulos, Basilio...