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BMCBI
2004
79views more  BMCBI 2004»
13 years 8 months ago
A new mixture model approach to analyzing allelic-loss data using Bayes factors
Background: Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor...
Manisha Desai, Mary J. Emond
SMA
2005
ACM
125views Solid Modeling» more  SMA 2005»
14 years 2 months ago
One-dimensional selections for feature-based data exchange
In the parametric feature based design paradigm, most features possess arguments that are subsets of the boundary of the current model, subsets defined interactively by user sele...
Ari Rappoport, Steven N. Spitz, Michal Etzion
CBMS
2006
IEEE
14 years 2 months ago
Class Noise and Supervised Learning in Medical Domains: The Effect of Feature Extraction
Inductive learning systems have been successfully applied in a number of medical domains. It is generally accepted that the highest accuracy results that an inductive learning sys...
Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen...
BMCBI
2008
171views more  BMCBI 2008»
13 years 8 months ago
A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more
Background: With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables ...
Harri T. Kiiveri
IROS
2006
IEEE
142views Robotics» more  IROS 2006»
14 years 2 months ago
Using Hidden Markov Models to Generate Natural Humanoid Movement
— This paper proposes a Hidden Markov Model (HMM) based approach to generate human-like movements for humanoid robots. Given human motion capture data for a class of movements, p...
Junghyun Kwon, Frank C. Park