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VLSISP
1998
111views more  VLSISP 1998»
15 years 1 months ago
Quantitative Analysis of MR Brain Image Sequences by Adaptive Self-Organizing Finite Mixtures
This paper presents an adaptive structure self-organizing finite mixture network for quantification of magnetic resonance (MR) brain image sequences. We present justification fo...
Yue Wang, Tülay Adali, Chi-Ming Lau, Sun-Yuan...
ISMB
2000
15 years 3 months ago
Analysis of Gene Expression Microarrays for Phenotype Classification
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
Andrea Califano, Gustavo Stolovitzky, Yuhai Tu
WABI
2009
Springer
155views Bioinformatics» more  WABI 2009»
15 years 8 months ago
A Markov Classification Model for Metabolic Pathways
Background: This paper considers the problem of identifying pathways through metabolic networks that relate to a specific biological response. Our proposed model, HME3M, first ide...
Timothy Hancock, Hiroshi Mamitsuka
154
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BMCBI
2010
171views more  BMCBI 2010»
15 years 2 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...
143
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CIKM
2010
Springer
14 years 11 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan