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» A Bayesian framework for combining gene predictions
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BMCBI
2006
124views more  BMCBI 2006»
13 years 7 months ago
Network-based de-noising improves prediction from microarray data
Background: Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to the noise properties of microarrays as well as...
Tsuyoshi Kato, Yukio Murata, Koh Miura, Kiyoshi As...
JCB
2007
146views more  JCB 2007»
13 years 7 months ago
MSOAR: A High-Throughput Ortholog Assignment System Based on Genome Rearrangement
The assignment of orthologous genes between a pair of genomes is a fundamental and challenging problem in comparative genomics, since many computational methods for solving variou...
Zheng Fu, Xin Chen, Vladimir Vacic, Peng Nan, Yang...
RECOMB
2010
Springer
13 years 11 months ago
MoGUL: Detecting Common Insertions and Deletions in a Population
Abstract. While the discovery of structural variants in the human population is ongoing, most methods for this task assume that the genome is sequenced to high coverage (e.g. 40x),...
Seunghak Lee, Eric Xing, Michael Brudno
BMCBI
2006
87views more  BMCBI 2006»
13 years 7 months ago
Phylogeny based discovery of regulatory elements
Background: Algorithms that locate evolutionarily conserved sequences have become powerful tools for finding functional DNA elements, including transcription factor binding sites;...
Jason Gertz, Justin C. Fay, Barak A. Cohen
CVPR
2010
IEEE
12 years 4 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu