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Significance Pruning in ARM
- Shinichi Morishita
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On Learning Gene Regulatory Networks Under the Boolean Network Model
Harri Lähdesmäki, Ilya Shmulevich and Olli Yli-Harja
Machine Learning 52 (1-2): 147-167, July - August, 2003 -
From Boolean to Probabilistic Boolean Networks as Models of Genetic Regulatory Networks
ILYA SHMULEVICH, EDWARD R. DOUGHERTY, AND WEI ZHANG
PROCEEDINGS OF THE IEEE, VOL. 90, NO. 11, NOVEMBER 2002- Boolean networks and Gene Expression References
- [60] REVEAL, a general reverse engineering algorithm for inference of genetic network architectures [Proc. Pacific Symp. Biocomputing]
- [61] Identification of gene regulatory networks by strategic gene disruptions and gene overexpressions
- [62] Identification of genetic networks from a small number of gene expression patterns under the Boolean network model [Proc. Pacific Symp. Biocomputing]
- [63] Inferring qualitative relations in genetic networks and metabolic pathways
- [64] Discovery of regulatory interactions through perturbation: Inference and experimental design
- [65] Algorithms for choosing differential gene expression experiments
- [66] Development of a system for the inference of large scale genetic networks
- [67] Finding Genetic Network from Experiments by Weighted Network Model
- [68] INFERENCE OF GENETIC REGULATORY NETWORKS UNDER THE BESTFIT EXTENSION PARADIGM
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Discovering molecular pathways from protein interaction and gene expression data.
Segal E, Wang H, Koller D.
Bioinformatics. 2003;19 Suppl 1:i264-71. -
Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data.
Segal E, Shapira M, Regev A, Pe'er D, Botstein D, Koller D, Friedman N.
Nat Genet. 2003 Jun;34(2):166-76. -
Publications Page
Modelling Gene Expression Data using Dynamic Bayesian Networks.
Kevin Murphy, Saira Mian.
1999 -
Publications Page
Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data.
Spirtes, P., Glymour, G., Kauffman, S., Scheines, R., Aimalie, V., and Wimberly, F.
To appear 2000 -
A Bayesian Network Classification Methodology for Gene Expression Data
Paul Helman, Robert Veroff, Susan R. Atlas, and Cheryl Willman
Technical Report
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