Eytan Domany

Or Zuk, Liat Ein-Dor, Eytan Domany: Ranking Under Uncertainty. CoRR abs/1206.5280 (2012)

Amit Zeisel, Amnon Amir, Wolfgang J. Köstler, Eytan Domany: Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes. BMC Bioinformatics 11: 400 (2010)

Libi Hertzberg, Shai Izraeli, Eytan Domany: STOP: searching for transcription factor motifs using gene expression. Bioinformatics 23(14): 1737-1743 (2007)

Or Zuk, Liat Ein-Dor, Eytan Domany: Ranking Under Uncertainty. UAI 2007: 466-473

Or Zuk, Eytan Domany, Ido Kanter, Michael Aizenman: Taylor series expansions for the entropy rate of Hidden Markov Processes. ICC 2006: 1598-1604

Or Zuk, Shiri Margel, Eytan Domany: On the Number of Samples Needed to Learn the Correct Structure of a Bayesian Network. UAI 2006

Gad Getz, Noam Shental, Eytan Domany: Semi-Supervised Learning -- A Statistical Physics Approach. CoRR abs/cs/0604011 (2006)

Liat Ein-Dor, Itai Kela, Gad Getz, David Givol, Eytan Domany: Outcome signature genes in breast cancer: is there a unique set?. Bioinformatics 21(2): 171-178 (2005)

Itai Yanai, Hila Benjamin-Rodrig, Michael Shmoish, Vered Chalifa-Caspi, Maxim Shklar, Ron Ophir, Arren Bar-Even, Shirley Horn-Saban, Marilyn Safran, Eytan Domany, Doron Lancet, Orit Shmueli: Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification. Bioinformatics 21(5): 650-659 (2005)

Dan Tsafrir, Ilan Tsafrir, Liat Ein-Dor, Or Zuk, Daniel A. Notterman, Eytan Domany: Sorting points into neighborhoods (SPIN): data analysis and visualization by ordering distance matrices. Bioinformatics 21(10): 2301-2308 (2005)

Eytan Domany: Analysis of DNA-chip and antigen-chip data: studies of cancer, stem cells and autoimmune diseases. Computer Physics Communications 169(1-3): 183-187 (2005)

Libi Hertzberg, Or Zuk, Gad Getz, Eytan Domany: Finding Motifs in Promoter Regions. Journal of Computational Biology 12(3): 314-330 (2005)

Or Zuk, Ido Kanter, Eytan Domany: Asymptotics of the Entropy Rate for a Hidden Markov Process. DCC 2005: 173-182

Or Zuk, Ido Kanter, Eytan Domany: The Entropy of a Binary Hidden Markov Process. CoRR abs/cs/0507060 (2005)

Or Zuk, Eytan Domany, Ido Kanter, Michael Aizenman: Taylor series expansions for the entropy rate of Hidden Markov Processes. CoRR abs/cs/0510005 (2005)

Or Zuk, Eytan Domany, Ido Kanter, Michael Aizenman: From finite-system entropy to entropy rate for a Hidden Markov Process. CoRR abs/cs/0510016 (2005)

Gad Getz, Alina Starovolsky, Eytan Domany: F2CS: FSSP to CATH and SCOP prediction server. Bioinformatics 20(13): 2150-2152 (2004)

Gad Getz, Hilah Gal, Itai Kela, Daniel A. Notterman, Eytan Domany: Coupled Two-way Clustering Analysis of Breast Cancer and Colon Cancer Gene Expression Data. Bioinformatics 19(9): 1079-1089 (2003)

Gad Getz, Eytan Domany: Coupled Two-way Clustering Server. Bioinformatics 19(9): 1153-1154 (2003)

Nestor Caticha, J. E. Palo Tejada, Doron Lancet, Eytan Domany: Computational Capacity of an Odorant Discriminator: The Linear Separability of Curves. Neural Computation 14(9): 2201-2220 (2002)

Erel Levine, Eytan Domany: Resampling Method for Unsupervised Estimation of Cluster Validity. Neural Computation 13(11): 2573-2593 (2001)

Marcelo Blatt, Shai Wiseman, Eytan Domany: Data Clustering Using a Model Granular Magnet. Neural Computation 9(8): 1805-1842 (1997)

Marcelo Blatt, Eytan Domany, Ido Kanter: On the equivalence of two-layered perceptrons with binary neurons. Int. J. Neural Syst. 6(3): 225-231 (1995)

Marcelo Blatt, Shai Wiseman, Eytan Domany: Clustering data through an analogy to the Potts model. NIPS 1995: 416-422

Amir A. Handzel, Tal Grossman, Eytan Domany, Shlomit Tarem, Ehud Duchovni: A Neural Network Classifier In Experimental Particle Physics. Int. J. Neural Syst. 4(2): 95-108 (1993)

Harel Z. Shouval, Isaac Shariv, Tal Grossman, Asher A. Friesem, Eytan Domany: An All-Optical Hopfield Network: Theory and Experiment. Int. J. Neural Syst. 1(4): 355-360 (1991)

Tal Grossman, Ronny Meir, Eytan Domany: Learning by Choice of Internal Representations. NIPS 1988: 73-80