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» Predicting protein functions with message passing algorithms
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CVPR
2012
IEEE
13 years 1 months ago
Curvature-based regularization for surface approximation
We propose an energy-based framework for approximating surfaces from a cloud of point measurements corrupted by noise and outliers. Our energy assigns a tangent plane to each (noi...
Carl Olsson, Yuri Boykov
BMCBI
2008
173views more  BMCBI 2008»
14 years 11 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
HPCN
2000
Springer
15 years 2 months ago
An Analytical Model for a Class of Architectures under Master-Slave Paradigm
We build an analytical model for an application utilizing master-slave paradigm. In the model, only three architecture parameters are used: latency, bandwidth and flop rate. Instea...
Yasemin Yalçinkaya, Trond Steihaug
JCB
2007
130views more  JCB 2007»
14 years 11 months ago
Bayesian Inference of MicroRNA Targets from Sequence and Expression Data
MicroRNAs (miRNAs) regulate a large proportion of mammalian genes by hybridizing to targeted messenger RNAs (mRNAs) and down-regulating their translation into protein. Although mu...
Jim C. Huang, Quaid Morris, Brendan J. Frey
BMCBI
2004
196views more  BMCBI 2004»
14 years 11 months ago
MUSCLE: a multiple sequence alignment method with reduced time and space complexity
Background: In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUS...
Robert C. Edgar