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wnpx's Friedman [28 articles]

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  • From promoter sequence to expression: a probabilistic framework
    (2002), pp. 263-272.
    by Eran Segal, Yoseph Barash, Itamar Simon, Nir Friedman, Daphne Koller
    posted to dt probabilistic by wnpx on 2007-10-18 04:49:45 as **
  • Module Networks: Discovering Regulatory Modules and their Condition Specific Regulators from Gene Expression Data
    by Eran Segal, Michael Shapira, Aviv Regev, Dana Pe'er, David Botstein, Daphne Koller, Nir Friedman
    posted to bayesian gene modeule network regulation by wnpx on 2007-06-11 07:20:10 as ** along with 2 people dimatura lp2
  • Bayesian Q-learning
    (1998), pp. 761-768.
    by Richard Dearden, Nir Friedman, Stuart Russell
    posted to bayesian by wnpx on 2007-04-15 20:36:17 as ** along with 2 people mistersheik AlainDutech
  • GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data.
    J Biomed Inform, Vol. 37, No. 1. (February 2004), pp. 43-53.
    by A Rzhetsky, I Iossifov, T Koike, M Krauthammer, P Kra, M Morris, H Yu, PA Duboué, W Weng, WJ Wilbur, V Hatzivassiloglou, C Friedman
    posted to software visualization by wnpx on 2007-03-22 21:53:24 as ** along with 4 people and 2 groups yas zlu bundschu bhaddow T_lab generif_paper
  • Learning Bayesian Networks with Local Structure
    pp. 252-262.
    by Nir Friedman, Moises Goldszmidt
    posted to bayesian learning by wnpx on 2007-03-22 21:52:03 as ** along with 1 person hcs
  • Bio-Ontology and text: bridging the modeling gap
    Bioinformatics, Vol. 22, No. 19. (1 October 2006), pp. 2421-2429.
    by Carol Friedman, Tara Borlawsky, Lyudmila Shagina, Rosie H Xing, Yves A Lussier
    posted to bioinformatics nlp ontology text by wnpx on 2007-03-22 21:49:40 as ** along with 5 people and 1 group yas gaudan balex sgoetz dejori T_lab
  • Probabilistic inference of molecular networks from noisy data sources
    Bioinformatics, Vol. 20, No. 8. (22 May 2004), pp. 1205-1213.
    by Ivan Iossifov, Michael Krauthammer, Carol Friedman, Vasileios Hatzivassiloglou, Joel S Bader, Kevin P White, Andrey Rzhetsky
    posted to bayesian dt inference od toread by wnpx on 2007-03-22 21:44:29 as *** along with 1 person iris_2001
  • Stochastic protein expression in individual cells at the single molecule level
    Nature, Vol. 440, No. 7082., pp. 358-362.
    by Long Cai, Nir Friedman, Sunney X Xie
    posted to stochasticity protein by wnpx on 2007-01-10 15:18:02 as ** along with 12 people and 1 group okarsligil ccots bayesian balabu cottrell jiyu mmt jtaylor margaritis cjeans austin jjray Bioinformatics
  • Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks
    Machine Learning, Vol. V50, No. 1. (1 January 2003), pp. 95-125.
    by Nir Friedman, Daphne Koller
    posted to bayesian network structure by wnpx on 2006-11-17 06:16:03 as **** along with 5 people and 1 group garyfeng Borelli chechetka quianominorleo naegele ReadingLab
  • Towards an integrated protein-protein interaction network: a relational markov network approach.
    J Comput Biol, Vol. 13, No. 2. (March 2006), pp. 145-164.
    by A Jaimovich, G Elidan, H Margalit, N Friedman
    posted to markov network prediction probabilistic protein proteininteraction by wnpx on 2006-08-24 18:36:29 as ** along with 5 people and 1 group lfriedl nirfriedman koller rsantana iris_2001 kdl
  • Learning Hidden Variable Networks: The Information Bottleneck Approach
    J. Mach. Learn. Res., Vol. 6 (2005), pp. 81-127.
    by Gal Elidan, Nir Friedman
    posted to bayesian learning network by wnpx on 2006-07-30 16:44:33 as ** along with 1 person anon_pl
  • Learning Probabilistic Relational Models
    (1999), pp. 1300-1309.
    by Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer
    posted to learning models prm probabilistic relational by wnpx on 2006-05-28 15:48:19 as ** along with 7 people weimer tvdbulck Maderlock ichbins81 krokicki roys sboisen
  • Learning Probabilistic Models of Relational Structure
    (2001), pp. 170-177.
    by Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar
    posted to learning prm probabilistic relational structure by wnpx on 2006-05-28 15:47:57 as ** along with 3 people ldietz student_t tvdbulck
  • Learning probabilistic models of link structure
    J. Mach. Learn. Res., Vol. 3 (2003), pp. 679-707.
    by Lisa Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar
    posted to learning structure by wnpx on 2006-05-28 15:47:04 as ** along with 3 people lyongu student_t iris_2001
  • Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data.
    Nat Genet, Vol. 34, No. 2. (June 2003), pp. 166-176.
    by E Segal, M Shapira, A Regev, D Pe'er, D Botstein, D Koller, N Friedman
    posted to data expression gene module networks by wnpx on 2006-04-18 14:38:44 as ** along with 18 people and 1 group cswinburne ggallone ealloza orzenil tuck bayesian tabu koller olympos fishtank dimatura karfunkel roys pkm dragonrez tvdbulck chrisamiller aviad_work Jarman Lab
  • On the Sample Complexity of Learning Bayesian Networks
    (1996)
    by Friedman
    posted to bayesnets learning by wnpx on 2006-02-24 15:47:52 as ** along with 1 person yaroslavvb
  • Learning the Structure of Dynamic Probabilistic Networks
    (1999), pp. 139-147.
    by Nir Friedman, Kevin Murphy, Stuart Russell
    posted to bayesian bayesnets inference learning structure by wnpx on 2006-01-30 16:35:12 as ** along with 3 people ryang ddahlem sj777
  • From signatures to models: understanding cancer using microarrays.
    Nat Genet, Vol. 37 Suppl (June 2005)
    by E Segal, N Friedman, N Kaminski, A Regev, D Koller
    posted to cancer expressiondata modeling by wnpx on 2006-01-05 22:23:17 as ***** along with 9 people and 1 group cswinburne aalibes textoris troels_marstrand nirfriedman rdiaz sampath shikin srp33 GeneGo
  • Rich probabilistic models for gene expression.
    Bioinformatics, Vol. 17 Suppl 1 (2001)
    by E Segal, B Taskar, A Gasch, N Friedman, D Koller
    posted to clustering expression gene probabilistic by wnpx on 2006-01-03 18:44:03 as ** along with 3 people and 1 group lfriedl balicea frohike kdl
  • Using Bayesian networks to analyze expression data
    (2000), pp. 127-135.
    by Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er
    posted to expressiondata dt bayesnet bayesian by wnpx on 2006-01-03 06:14:49 as *** along with 2 people ujh abhik
  • Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks
    (January 2003)
    by N Friedman, D Koller
    posted to bayesian bayesnets learning structure by wnpx on 2006-01-03 06:11:20 as **** along with 6 people markusd zeppe abhik eustatic yoh dimatura
  • Learning Bayesian networks with local structure
    (1999), pp. 421-459.
    by Nir Friedman, Moises Goldszmidt
    posted to bayesian bayesnet learning structure by wnpx on 2006-01-03 06:08:50 as ** along with 2 people yaroslavvb eustatic
  • Learning Probabilistic Relational Models
    (1999), pp. 1300-1309.
    by Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer
    posted to prm by wnpx on 2005-12-30 17:16:54 as ** along with 1 person 1like
  • Learning Bayesian Network Structure from Massive Datasets: The ”Sparse Candidate” Algorithm
    pp. 206-215.
    by Nir Friedman, Iftach Nachman, Dana Pe'er
    posted to algorithm bayesian network structure by wnpx on 2005-12-29 17:25:46 as *** along with 4 people ldfu famoreira dimatura roys
  • Inferring subnetworks from perturbed expression profiles.
    Bioinformatics, Vol. 17 Suppl 1 (2001)
    by Dana Pe’er, Aviv Regev, Gal Elidan, Nir Friedman
    posted to timeseries perturbation network inference expressiondata dt by wnpx on 2005-12-29 17:13:55 as *** along with 2 people cswinburne frohike
  • Inferring quantitative models of regulatory networks from expression data.
    Bioinformatics, Vol. 20 Suppl 1 (4 August 2004)
    by I Nachman, A Regev, N Friedman
    posted to ml kineticparameters dt dbn bayesian by wnpx on 2005-12-29 17:02:44 as read along with 4 people brl koller apleite frohike
  • Using Bayesian networks to analyze expression data.
    J Comput Biol, Vol. 7, No. 3-4. (2000), pp. 601-620.
    by N Friedman, M Linial, I Nachman, D Pe'er
    posted to expressiondata dt bayesian by wnpx on 2005-12-29 17:00:41 as read along with 9 people cswinburne siebert brl ldfu dragonrez Schmidtc helsley heliopais srp33
  • Inferring cellular networks using probabilistic graphical models.
    Science, Vol. 303, No. 5659. (6 February 2004), pp. 799-805.
    by Nir Friedman
    posted to review inference dt bayes by wnpx on 2005-12-29 16:57:37 as read along with 17 people and 1 group bertelsen ldfu ujh lfriedl opheliav ryang nirfriedman neveaire koller helsley dimatura edwardmorrissey vietanh0 Yumyai srp33 saman_vp jo_davies kdl
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