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Publications of Author

1. Benjamin Taskar, Eran Segal, Daphne Koller
   Probabilistic Classification and Clustering in Relational Data. [Citation Graph (0, 0)][DBLP]
   IJCAI, 2001, pp:870-878 [Conf]
   
2. Eran Segal, Benjamin Taskar, Audrey Gasch, Nir Friedman, Daphne Koller
   Rich probabilistic models for gene expression. [Citation Graph (0, 0)][DBLP]
   ISMB (Supplement of Bioinformatics), 2001, pp:243-252 [Conf]
   
3. Eran Segal, Haidong Wang, Daphne Koller
   Discovering molecular pathways from protein interaction and gene expression data. [Citation Graph (0, 0)][DBLP]
   ISMB (Supplement of Bioinformatics), 2003, pp:264-272 [Conf]
   
4. Eran Segal, R. Yelensky, Daphne Koller
   Genome-wide discovery of transcriptional modules from DNA sequence and gene expression. [Citation Graph (0, 0)][DBLP]
   ISMB (Supplement of Bioinformatics), 2003, pp:273-282 [Conf]
   
5. Saharon Rosset, Eran Segal
   Boosting Density Estimation. [Citation Graph (0, 0)][DBLP]
   NIPS, 2002, pp:641-648 [Conf]
   
6. Eran Segal, Daphne Koller, Dirk Ormoneit
   Probabilistic Abstraction Hierarchies. [Citation Graph (0, 0)][DBLP]
   NIPS, 2001, pp:913-920 [Conf]
   
7. Haidong Wang, Eran Segal, Asa Ben-Hur, Daphne Koller, Douglas L. Brutlag
   Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale. [Citation Graph (0, 0)][DBLP]
   NIPS, 2004, pp:- [Conf]
   
8. Alexander J. Hartemink, Eran Segal
   Session Introduction: Joint Learning from Multiple Types of Genomic Data. [Citation Graph (0, 0)][DBLP]
   Pacific Symposium on Biocomputing, 2005, pp:- [Conf]
   
9. Alexander J. Hartemink, Eran Segal
   Session Introduction. [Citation Graph (0, 0)][DBLP]
   Pacific Symposium on Biocomputing, 2004, pp:262-263 [Conf]
   
10. Eran Segal, Alexis Battle, Daphne Koller
    Decomposing Gene Expression into Cellular Processes. [Citation Graph (0, 0)][DBLP]
    Pacific Symposium on Biocomputing, 2003, pp:89-100 [Conf]
    
11. Alexis Battle, Eran Segal, Daphne Koller
    Probabilistic discovery of overlapping cellular processes and their regulation. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2004, pp:167-176 [Conf]
    
12. Eran Segal, Yoseph Barash, Itamar Simon, Nir Friedman, Daphne Koller
    From promoter sequence to expression: a probabilistic framework. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2002, pp:263-272 [Conf]
    
13. Eran Segal, Daphne Koller
    Probabilistic hierarchical clustering for biological data. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2002, pp:273-280 [Conf]
    
14. Eran Segal, Roded Sharan
    A discriminative model for identifying spatial cis-regulatory modules. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2004, pp:141-149 [Conf]
    
15. Eilon Sharon, Eran Segal
    A Feature-Based Approach to Modeling Protein-DNA Interactions. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2007, pp:77-91 [Conf]
    
16. Yossi Matias, Eran Segal, Jeffrey Scott Vitter
    Efficient bundle sorting. [Citation Graph (0, 0)][DBLP]
    SODA, 2000, pp:839-848 [Conf]
    
17. Uri Lerner, Eran Segal, Daphne Koller
    Exact Inference in Networks with Discrete Children of Continuous Parents. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:319-328 [Conf]
    
18. Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
    Learning Module Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:525-534 [Conf]
    
19. Eran Segal, Roded Sharan
    A Discriminative Model for Identifying Spatial cis-Regulatory Modules. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2005, v:12, n:6, pp:822-834 [Journal]
    
20. Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
    Learning Module Networks. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:557-588 [Journal]
    
21. Yossi Matias, Eran Segal, Jeffrey Scott Vitter
    Efficient Bundle Sorting. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 2006, v:36, n:2, pp:394-410 [Journal]
    
22. 
    Incorporating Nucleosomes into Thermodynamic Models of Transcription Regulation. [Citation Graph (, )][DBLP]
    
    
23. 
    Modeling interactions between adjacent nucleosomes improves genome-wide predictions of nucleosome occupancy. [Citation Graph (, )][DBLP]