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» Constructing explanatory process models from biological data...
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RECOMB
2004
Springer
14 years 8 months ago
Modeling and Analysis of Heterogeneous Regulation in Biological Networks
Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Irit Gat-Viks, Amos Tanay, Ron Shamir
BMCBI
2007
157views more  BMCBI 2007»
13 years 7 months ago
Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory
Background: Large-scale sequencing of entire genomes has ushered in a new age in biology. One of the next grand challenges is to dissect the cellular networks consisting of many i...
Feng Luo, Yunfeng Yang, Jianxin Zhong, Haichun Gao...
NIPS
2003
13 years 9 months ago
ICA-based Clustering of Genes from Microarray Expression Data
We propose an unsupervised methodology using independent component analysis (ICA) to cluster genes from DNA microarray data. Based on an ICA mixture model of genomic expression pa...
Su-In Lee, Serafim Batzoglou
IJCNN
2006
IEEE
14 years 1 months ago
Reconstruction of Gene Regulatory Networks from Temporal Microarray Data Using Pattern Recognition Techniques
- Gene regulatory networks allow us to study and understand genes’ roles in biological processes. Among others, regulatory networks help to identify pathway initiator genes and t...
Azhar Salim, Faramarz Valafar
JMLR
2002
117views more  JMLR 2002»
13 years 7 months ago
Learning to Construct Fast Signal Processing Implementations
A single signal processing algorithm can be represented by many mathematically equivalent formulas. However, when these formulas are implemented in code and run on real machines, ...
Bryan Singer, Manuela M. Veloso