From promoter sequence to expression: A probabilistic framework

Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB

Volumn , Issue , 2002, Pages 263-272

  Segal, Eran ^a   Barash, Yoseph ^a   Simon, Itamar ^a   Friedman, Nir ^a   Koller, Daphne ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BIOASSAY; DNA SEQUENCES; GENES; KNOWLEDGE BASED SYSTEMS; MOLECULAR BIOLOGY; RNA;

PROMOTER SEQUENCE; TRANSCRIPTION FACTORS;

PROBABILITY;

EID: 0036376097     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (34)

1. Fitting a mixture model by expectation maximization to discover motifs in biopolymers
2. A simple hyper-geometric approach for discovering putative transcription factor binding sites
3. Context-specific Bayesian clustering for gene expression data
4. Context-specific independence in Bayesian networks
5. Predicting gene regulatory elements in silico on a genomic scale
6. Finding motifs using random projections
7. Regulatory element detection using correlation with expression
8. Saccharomyces genome database
9. A Bayesian approach to learning Bayesian networks with local structure
10. Ypd, pombepd, and wormpd: Model organism volumes of the bioknowledge library, an integrated resource for protein information
11. Learning probabilistic relational models
12. Learning Bayesian networks with local structure
13. Using Bayesian networks to analyze expression data
14. Combining location and expression data for principled discovery of genetic regulatory network models
15. A tutorial on learning with Bayesian networks
16. Learning Bayesian networks: A unification for discrete and Gaussian domains
17. Mechanisms controlling differential promoter-occupancy by the yeast forkhead proteins fkh1p and fkh2p: Implications for regulating the cell cycle and differentiation
18. Finding regulatory elements using joint likelihoods for sequence and expression profile data
19. Probabilistic frame-based systems
20. Bioprospector: Discovering conserved dna motifs in upstream regulatory regions of co-expressed genes
21. Inferring subnetworks from perturbed expression profiles
22. Identifying regulatory networks by combinatorial analysis of promoter elements
23. Genome-wide location and function of dna binding proteins
24. Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation
25. Rich probabilistic models for gene expression
26. Serial regulation of transcriptional regulators in the yeast cell cycle
27. A statistical method for finding transcription factor binding sites
28. Comprehensive identification of cell cycle-regulated genes of the yeast saccharomyces cerevisiae by microarray hybridization
29. Systematic determination of genetic network architecture
30. The TRANSFAC system on gene expression regulation
31. Two yeast forkhead genes regulate the cell cycle and pseudohyphal growth