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The Faculty of Medicine - Immunology and Cancer Research: Friedman Nir

Researchers

Last updated December 2021 -  Immunology and Cancer Research

List of Publications

(1) Chappleboim A, Joseph-Strauss D, Rahat A, Sharkia I, Adam M, Kitsberg D, et al. Early sample tagging and pooling enables simultaneous SARS-CoV-2 detection and variant sequencing. Sci Transl Med 2021;13(618).

(2) Rak R, Polonsky M, Eizenberg-Magar I, Mo Y, Sakaguchi Y, Mizrahi O, et al. Dynamic changes in tRNA modifications and abundance during T cell activation. Proc Natl Acad Sci U S A 2021;118(42).

(3) Moriel N, Senel E, Friedman N, Rajewsky N, Karaiskos N, Nitzan M. NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport. Nat Protoc 2021;16(9):4177-4200.

(4) Bassan D, Gozlan YM, Sharbi-Yunger A, Tzehoval E, Greenstein E, Bitan L, et al. Avidity optimization of a MAGE-A1-specific TCR with somatic hypermutation. Eur J Immunol 2021;51(6):1505-1518.

(5) Sadeh R, Sharkia I, Fialkoff G, Rahat A, Gutin J, Chappleboim A, et al. Author Correction: ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin (Nature Biotechnology, (2021), 39, 5, (586-598), 10.1038/s41587-020-00775-6). Nat Biotechnol 2021;39(5):642.

(6) Sadeh R, Sharkia I, Fialkoff G, Rahat A, Gutin J, Chappleboim A, et al. ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin. Nat Biotechnol 2021;39(5):586-598.

(7) Peri A, Greenstein E, Alon M, Pai JA, Dingjan T, Reich-Zeliger S, et al. Combined presentation and immunogenicity analysis reveals a recurrent RAS.Q61K neoantigen in melanoma. J Clin Invest 2021;131(20).

(8) Haralampiev I, Prisner S, Nitzan M, Schade M, Jolmes F, Schreiber M, et al. Selective flexible packaging pathways of the segmented genome of influenza A virus. Nat Commun 2020;11(1).

(9) de Boer CG, Vaishnav ED, Sadeh R, Abeyta EL, Friedman N, Regev A. Author Correction: Deciphering eukaryotic gene-regulatory logic with 100 million random promoters (Nature Biotechnology, (2020), 38, 1, (56-65), 10.1038/s41587-019-0315-8). Nat Biotechnol 2020;38(10):1211.

(10) Korem Kohanim Y, Tendler A, Mayo A, Friedman N, Alon U. Endocrine Autoimmune Disease as a Fragility of Immune Surveillance against Hypersecreting Mutants. Immunity 2020;52(5):872-884.e5.

(11) de Boer CG, Vaishnav ED, Sadeh R, Abeyta EL, Friedman N, Regev A. Deciphering eukaryotic gene-regulatory logic with 100 million random promoters. Nat Biotechnol 2020;38(1):56-65.

(12) Nitzan M, Karaiskos N, Friedman N, Rajewsky N. Gene expression cartography. Nature 2019;576(7785):132-137.

(13) Lu J, Van Laethem F, Bhattacharya A, Craveiro M, Saba I, Chu J, et al. Molecular constraints on CDR3 for thymic selection of MHC-restricted TCRs from a random pre-selection repertoire. Nat Commun 2019;10(1).

(14) Elyahu Y, Hekselman I, Eizenberg-Magar I, Berner O, Strominger I, Schiller M, et al. Aging promotes reorganization of the CD4 T cell landscape toward extreme regulatory and effector phenotypes. Sci Adv 2019;5(8).

(15) Schneidman-Duhovny D, Khuri N, Dong GQ, Winter MB, Shifrut E, Friedman N, et al. Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition. PLoS ONE 2019;13(11).

(16) De Mattos-Arruda L, Sammut S-, Ross EM, Bashford-Rogers R, Greenstein E, Markus H, et al. The Genomic and Immune Landscapes of Lethal Metastatic Breast Cancer. Cell Rep 2019;27(9):2690-2708.e10.

(17) Klein-Brill A, Joseph-Strauss D, Appleboim A, Friedman N. Dynamics of Chromatin and Transcription during Transient Depletion of the RSC Chromatin Remodeling Complex. Cell Rep 2019;26(1):279-292.e5.

(18) Gutin J, Joseph-Strauss D, Sadeh A, Shalom E, Friedman N. Genetic screen of the yeast environmental stress response dynamics uncovers distinct regulatory phases. Mol Syst Biol 2019;15(8).

(19) Rieckmann M, Delgobo M, Gaal C, Büchner L, Steinau P, Reshef D, et al. Myocardial infarction triggers cardioprotective antigen-specific T helper cell responses. J Clin Invest 2019;129(11):4922-4936.

(20) Kalaora S, Wolf Y, Feferman T, Barnea E, Greenstein E, Reshef D, et al. Combined analysis of antigen presentation and T-cell recognition reveals restricted immune responses in melanoma. Cancer Discov 2018;8(11):1366-1375.

(21) Polonsky M, Rimer J, Kern-Perets A, Zaretsky I, Miller S, Bornstein C, et al. Induction of CD4 T cell memory by local cellular collectivity. Sci 2018;360(6394).

(22) Adutler-Lieber S, Friedman N, Geiger B. Expansion and antitumor cytotoxicity of T-Cells are augmented by substrate-bound CCL21 and intercellular adhesion molecule 1. Front Immunol 2018;9(JUN).

(23) Radzinski M, Fassler R, Yogev O, Breuer W, Shai N, Gutin J, et al. Temporal profiling of redox-dependent heterogeneity in single cells. eLife 2018;7.

(24) Gutin J, Sadeh R, Bodenheimer N, Joseph-Strauss D, Klein-Brill A, Alajem A, et al. Fine-Resolution Mapping of TF Binding and Chromatin Interactions. Cell Rep 2018;22(10):2797-2807.

(25) Tickotsky N, Sagiv T, Prilusky J, Shifrut E, Friedman N. McPAS-TCR: A manually curated catalogue of pathology-associated T cell receptor sequences. Bioinformatics 2017;33(18):2924-2929.

(26) Ichikawa Y, Connelly CF, Appleboim A, Miller TCR, Jacobi H, Abshiru NA, et al. A synthetic biology approach to probing nucleosome symmetry. eLife 2017;6.

(27) Eizenberg-Magar I, Rimer J, Zaretsky I, Lara-Astiaso D, Reich-Zeliger S, Friedman N. Diverse continuum of CD4+ T-cell states is determined by hierarchical additive integration of cytokine signals. Proc Natl Acad Sci U S A 2017;114(31):E6447-E6456.

(28) Madi A, Poran A, Shifrut E, Reich-Zeliger S, Greenstein E, Zaretsky I, et al. T cell receptor repertoires of mice and humans are clustered in similarity networks around conserved public CDR3 sequences. eLife 2017;6.

(29) Adutler-Lieber S, Zaretsky I, Sabany H, Kartvelishvily E, Golani O, Geiger B, et al. Substrate-bound CCL21 and ICAM1 combined with soluble IL-6 collectively augment the expansion of antigen-specific murine CD41 T cells. Blood Adv 2017;1(15):1016-1030.

(30) Sun Y, Best K, Cinelli M, Heather JM, Reich-Zeliger S, Shifrut E, et al. Specificity, privacy, and degeneracy in the CD4 T cell receptor repertoire following immunization. Front Immunol 2017;8(APR).

(31) Wolf Y, Shemer A, Polonsky M, Gross M, Mildner A, Yona S, et al. Autonomous TNF is critical for in vivo monocyte survival in steady state and inflammation. J Exp Med 2017;214(4):905-917.

(32) Cinelli M, Sun Y, Best K, Heather JM, Reich-Zeliger S, Shifrut E, et al. Feature selection using a one dimensional naïve Bayes' classifier increases the accuracy of support vector machine classification of CDR3 repertoires. Bioinformatics 2017;33(7):951-955.

(33) Dixit A, Parnas O, Li B, Chen J, Fulco CP, Jerby-Arnon L, et al. Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens. Cell 2016;167(7):1853-1866.e17.

(34) Levy G, Habib N, Guzzardi MA, Kitsberg D, Bomze D, Ezra E, et al. Nuclear receptors control pro-viral and antiviral metabolic responses to hepatitis C virus infection. Nat Chem Biol 2016;12(12):1037-1045.

(35) Sadeh R, Launer-Wachs R, Wandel H, Rahat A, Friedman N. Elucidating Combinatorial Chromatin States at Single-Nucleosome Resolution. Mol Cell 2016;63(6):1080-1088.

(36) Geffen Y, Appleboim A, Gardner RG, Friedman N, Sadeh R, Ravid T. Mapping the Landscape of a Eukaryotic Degronome. Mol Cell 2016;63(6):1055-1065.

(37) Cohen IR, Friedman N, Quintana FJ. T-Cell Vaccination: An Insight Into T-Cell Regulation. Translational Neuroimmunology in Multiple Sclerosis: From Disease Mechanisms to Clinical Applications; 2016. p. 457-473.

(38) Setty M, Tadmor MD, Reich-Zeliger S, Angel O, Salame TM, Kathail P, et al. Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat Biotechnol 2016;34(6):637-645.

(39) Polonsky M, Chain B, Friedman N. Clonal expansion under the microscope: Studying lymphocyte activation and differentiation using live-cell imaging. Immunol Cell Biol 2016;94(3):242-249.

(40) Heather JM, Best K, Oakes T, Gray ER, Roe JK, Thomas N, et al. Dynamic perturbations of the T-Cell receptor repertoire in chronic HIV infection and following antiretroviral therapy. Front Immunol 2016;6(JAN).

(41) Rege M, Subramanian V, Zhu C, Hsieh THS, Weiner A, Friedman N, et al. Chromatin Dynamics and the RNA Exosome Function in Concert to Regulate Transcriptional Homeostasis. Cell Rep 2015;13(8):1610-1622.

(42) Zlotnikov-Klionsky Y, Nathansohn-Levi B, Shezen E, Rosen C, Kagan S, Bar-On L, et al. Perforin-Positive Dendritic Cells Exhibit an Immuno-regulatory Role in Metabolic Syndrome and Autoimmunity. Immunity 2015;43(4):776-787.

(43) Gutin J, Sadeh A, Rahat A, Aharoni A, Friedman N. Condition-specific genetic interaction maps reveal crosstalk between the cAMP/PKA and the HOG MAPK pathways in the activation of the general stress response. Mol Syst Biol 2015;11(10).

(44) Friedman N, Rando OJ. Epigenomics and the structure of the living genome. Genome Res 2015;25(10):1482-1490.

(45) Hsieh T-S, Weiner A, Lajoie B, Dekker J, Friedman N, Rando OJ. Mapping Nucleosome Resolution Chromosome Folding in Yeast by Micro-C. Cell 2015;162(1):108-119.

(46) Lerner I, Bartok O, Wolfson V, Menet JS, Weissbein U, Afik S, et al. Clk post-transcriptional control denoises circadian transcription both temporally and spatially. Nat Commun 2015;6.

(47) Weiner A, Hsieh T-S, Appleboim A, Chen HV, Rahat A, Amit I, et al. High-resolution chromatin dynamics during a yeast stress response. Mol Cell 2015;58(2):371-386.

(48) Rabani M, Raychowdhury R, Jovanovic M, Rooney M, Stumpo DJ, Pauli A, et al. High-resolution sequencing and modeling identifies distinct dynamic RNA regulatory strategies. Cell 2014;159(7):1698-1710.

(49) Adutler-Lieber S, Zaretsky I, Platzman I, Deeg J, Friedman N, Spatz JP, et al. Engineering of synthetic cellular microenvironments: Implications for immunity. J Autoimmun 2014;54:100-111.

(50) Madi A, Shifrut E, Reich-Zeliger S, Gal H, Best K, Ndifon W, et al. T-cell receptor repertoires share a restricted set of public and abundant CDR3 sequences that are associated with self-related immunity. Genome Res 2014;24(10):1603-1612.

(51) Hart Y, Reich-Zeliger S, Antebi YE, Zaretsky I, Mayo AE, Alon U, et al. Paradoxical signaling by a secreted molecule leads to homeostasis of cell levels. Cell 2014;158(5):1022-1032.

(52) Rimer J, Cohen IR, Friedman N. Do all creatures possess an acquired immune system of some sort? Bioessays 2014;36(3):273-281.

(53) Thomas N, Best K, Cinelli M, Reich-Zeliger S, Gal H, Shifrut E, et al. Tracking global changes induced in the CD4 T-cell receptor repertoire by immunization with a complex antigen using short stretches of CDR3 protein sequence. Bioinformatics 2014;30(22):3181-3188.

(54) Lara-Astiaso D, Weiner A, Lorenzo-Vivas E, Zaretsky I, Jaitin DA, David E, et al. Immunogenetics. Chromatin state dynamics during blood formation. Science 2014;345(6199):943-949.

(55) Shipony Z, Mukamel Z, Cohen NM, Landan G, Chomsky E, Zeliger SR, et al. Dynamic and static maintenance of epigenetic memory in pluripotent and somatic cells. Nature 2014;513(7516):115-119.

(56) Shalek AK, Satija R, Shuga J, Trombetta JJ, Gennert D, Lu D, et al. Single-cell RNA-seq reveals dynamic paracrine control of cellular variation. Nature 2014;510(7505):363-369.

(57) Waysbort N, Russ D, Chain BM, Friedman N. Coupled IL-2-dependent extracellular feedbacks govern two distinct consecutive phases of CD4 T cell activation. J Immunol 2013;191(12):5822-5830.

(58) Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc 2013;8(8):1494-1512.

(59) Polonsky M, Zaretsky I, Friedman N. Dynamic single-cellmeasurements of gene expression in primary lymphocytes: Challenges, tools and prospects. Brief Funct Genomics 2013;12(2):99-108.

(60) Friedman N. Studying gene expression at the level of the single cell. Brief Funct Genomics 2013;12(2):73-74.

(61) Baruch K, Ron-Harel N, Gal H, Deczkowska A, Shifrut E, Ndifon W, et al. CNS-specific immunity at the choroid plexus shifts toward destructive Th2 inflammation in brain aging. Proc Natl Acad Sci U S A 2013;110(6):2264-2269.

(62) Friedman N. Comprehensive Mapping of DNA Damage: From Static Genetic Maps to Condition-Specific Maps. Mol Cell 2013;49(2):234-236.

(63) Yissachar N, Sharar Fischler T, Cohen AA, Reich-Zeliger S, Russ D, Shifrut E, et al. Dynamic Response Diversity of NFAT Isoforms in Individual Living Cells. Mol Cell 2013;49(2):322-330.

(64) Shifrut E, Baruch K, Gal H, Ndifon W, Deczkowska A, Schwartz M, et al. CD4+ T cell-receptor repertoire diversity is compromised in the spleen but not in the bone marrow of aged mice due to private and sporadic clonal expansions. Front Immunol 2013;4(NOV).

(65) Antebi YE, Reich-Zeliger S, Hart Y, Mayo A, Eizenberg I, Rimer J, et al. Mapping differentiation under mixed culture conditions reveals a tunable continuum of T cell fates. PLoS Biol 2013;11(7).

(66) Zaretsky I, Polonsky M, Shifrut E, Reich-Zeliger S, Antebi Y, Aidelberg G, et al. Monitoring the dynamics of primary T cell activation and differentiation using long term live cell imaging in microwell arrays. Lab Chip Miniaturisation Chem Biol 2012;12(23):5007-5015.

(67) Habib N, Wapinski I, Margalit H, Regev A, Friedman N. A functional selection model explains evolutionary robustness despite plasticity in regulatory networks. Mol Syst Biol 2012;8.

(68) Ndifon W, Gal H, Shifrut E, Aharoni R, Yissachar N, Waysbort N, et al. Chromatin conformation governs T-cell receptor Jβgene segment usage. Proc Natl Acad Sci U S A 2012;109(39):15865-15870.

(69) Garber M, Yosef N, Goren A, Raychowdhury R, Thielke A, Guttman M, et al. A High-Throughput Chromatin Immunoprecipitation Approach Reveals Principles of Dynamic Gene Regulation in Mammals. Mol Cell 2012;47(5):810-822.

(70) Savir Y, Waysbort N, Antebi YE, Tlusty T, Friedman N. Balancing speed and accuracy of polyclonal T cell activation: a role for extracellular feedback. BMC Syst Biol 2012;6.

(71) Weiner A, Chen HV, Liu CL, Rahat A, Klien A, Soares L, et al. Systematic dissection of roles for chromatin regulators in a yeast stress response. PloS Biol 2012;10(7):17.

(72) Hart Y, Antebi YE, Mayo AE, Friedman N, Alona U. Design principles of cell circuits with paradoxical components. Proc Natl Acad Sci U S A 2012;109(21):8346-8351.

(73) Kaplan T, Friedman N. Gene expression: Running to stand still. Nature 2012;484(7393):171-172.

(74) Brar GA, Yassour M, Friedman N, Regev A, Ingolia NT, Weissman JS. High-resolution view of the yeast meiotic program revealed by ribosome profiling. Science 2012;335(6068):552-557.

(75) Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol 2011;29(7):644-652.

(76) Novershtern N, Regev A, Friedman N. Physical Module Networks: An integrative approach for reconstructing transcription regulation. Bioinformatics 2011;27(13):i177-i185.

(77) Sivriver J, Habib N, Friedman N. An integrative clustering and modeling algorithm for dynamical gene expression data. Bioinformatics 2011;27(13):i392-i400.

(78) Celona B, Weiner A, Di Felice F, Mancuso FM, Cesarini E, Rossi RL, et al. Substantial Histone reduction modulates Genomewide nucleosomal occupancy and global transcriptional output. PloS Biol 2011;9(6).

(79) Radman-Livaja M, Verzijlbergen KF, Weiner A, van Welsem T, Friedman N, Rando OJ, et al. Patterns and mechanisms of Ancestral Histone protein inheritance in Budding yeast. PloS Biol 2011;9(6).

(80) Zhang Y, Handley D, Kaplan T, Yu H, Bais AS, Richards T, et al. High throughput determination of TGFβ1/SMAD3 targets in A549 lung epithelial cells. PLoS ONE 2011;6(5).

(81) Rhind N, Chen Z, Yassour M, Thompson DA, Haas BJ, Habib N, et al. Comparative functional genomics of the fission yeasts. Science 2011;332(6032):930-936.

(82) Rabani M, Levin JZ, Fan L, Adiconis X, Raychowdhury R, Garber M, et al. Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells. Nat Biotechnol 2011;29(5):436-442.

(83) Rinotta R, Jaimovicha A, Friedman N. Exploring transcription regulation through cell-to-cell variability. Proc Natl Acad Sci U S A 2011;108(15):6329-6334.

(84) Radman-Livaja M, Ruben G, Weiner A, Friedman N, Kamakaka R, Rando OJ. Dynamics of Sir3 spreading in budding yeast: Secondary recruitment sites and euchromatic localization. EMBO J 2011;30(6):1012-1026.

(85) Jaimovich A, Friedman N. From large-scale assays to mechanistic insights: Computational analysis of interactions. Curr Opin Biotechnol 2011;22(1):87-93.

(86) Novershtern N, Subramanian A, Lawton LN, Mak RH, Haining WN, McConkey ME, et al. Densely interconnected transcriptional circuits control cell states in human hematopoiesis. Cell 2011;144(2):296-309.

(87) Carone BR, Fauquier L, Habib N, Shea JM, Hart CE, Li R, et al. Paternally induced transgenerational environmental reprogramming of metabolic gene expression in mammals. Cell 2010;143(7):1084-1096.

(88) Friedman N, Schuldiner M. The DNA damage road map. Science 2010;330(6009):1327-1328.

(89) Cohn I, El-Hay T, Friedman N, Kupferman R. Mean field variational approximation for continuous-time Bayesian networks. J Mach Learn Res 2010;11:2745-2783.

(90) Continuous-time belief propagation. ICML 2010 - Proceedings, 27th International Conference on Machine Learning; 2010.

(91) Levin JZ, Yassour M, Adiconis X, Nusbaum C, Thompson DA, Friedman N, et al. Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nat Methods 2010;7(9):709-715.

(92) Yassour M, Pfiffner J, Levin JZ, Adiconis X, Gnirke A, Nusbaum C, et al. Strand-specific RNA sequencing reveals extensive regulated long antisense transcripts that are conserved across yeast species. Genome Biol 2010;11(8).

(93) Aharoni R, Eilam R, Stock A, Vainshtein A, Shezen E, Gal H, et al. Glatiramer acetate reduces Th-17 inflammation and induces regulatory T-cells in the CNS of mice with relapsing-remitting or chronic EAE. J Neuroimmunol 2010;225(1-2):100-111.

(94) Kim TS, Liu CL, Yassour M, Holik J, Friedman N, Buratowski S, et al. RNA polymerase mapping during stress responses reveals widespread nonproductive transcription in yeast. Genome Biol 2010;11(7).

(95) Jaimovich A, Rinott R, Schuldiner M, Margalit H, Friedman N. Modularity and directionality in genetic interaction maps. Bioinformatics 2010;26(12):i228-i236.

(96) Radman-Livaja M, Liu CL, Friedman N, Schreiber SL, Rando OJ. Replication and active demethylation represent partially overlapping mechanisms for erasure of H3K4me3 in budding yeast. PLoS Genet 2010;6(2).

(97) Weiner A, Hughes A, Yassour M, Rando OJ, Friedman N. High-resolution nucleosome mapping reveals transcription-dependent promoter packaging. Genome Res 2010;20(1):90-100.

(98) Segman RH, Goltser-Dubner T, Weiner I, Canetti L, Galili-Weisstub E, Milwidsky A, et al. Blood mononuclear cell gene expression signature of postpartum depression. Mol Psychiatry 2010;15(1):93-100.

(99) Segman RH, Goltser-Dubner T, Weiner I, Canetti L, Galili-Weisstub E, Milwidsky A, et al. Blood mononuclear cell gene expression patterns denote the onset of persisting post-partum depressive disorder. Mol Psychiatry 2010;15(1):2.

(100) Garber M, Guttman M, Clamp M, Zody MC, Friedman N, Xie X. Identifying novel constrained elements by exploiting biased substitution patterns. Bioinformatics 2009;25(12):i54-i62.

(101) Friedman N, Cai L, Xie XS. Stochasticity in gene expression as observed by single-molecule experiments in live cells. Isr J Chem 2009;49(3-4):333-342.

(102) Yassoura M, Kaplana T, Fraser HB, Levin JZ, Pfiffner J, Adiconis X, et al. Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing. Proc Natl Acad Sci U S A 2009;106(9):3264-3269.

(103) Convexifying the Bethe free energy. Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009; 2009.

(104) Mean field variational approximation for continuous-time Bayesian networks. Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, UAI 2009; 2009.

(105) Gibbs sampling in factorized continuous-time Markov processes. Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence, UAI 2008; 2008.

(106) Eisenberg I, Novershtern N, Itzhaki Z, Becker-Cohen M, Sadeh M, Willems PHGM, et al. Mitochondrial processes are impaired in hereditary inclusion body myopathy. Hum Mol Genet 2008;17(23):3663-3674.

(107) Kaplan T, Liu CL, Erkmann JA, Holik J, Grunstein M, Kaufman PD, et al. Cell cycle- and chaperone-mediated regulation of H3K56ac incorporation in yeast. PLoS Genet 2008;4(11).

(108) Yassour M, Kaplan T, Jaimovich A, Friedman N. Nucleosome positioning from tiling microarray data. Bioinformatics 2008;24(13):i139-i146.

(109) Tetievsky A, Cohen O, Eli-Berchoer L, Gerstenblith G, Stern MD, Wapinski I, et al. Physiological and molecular evidence of heat acclimation memory: A lesson from thermal responses and ischemic cross-tolerance in the heart. Physiol Genomics 2008;34(1):78-87.

(110) Novershtern N, Itzhaki Z, Manor O, Friedman N, Kaminski N. A functional and regulatory map of asthma. Am J Resp Cell Mol Biol 2008;38(3):324-336.

(111) Habib N, Kaplan T, Margalit H, Friedman N. A novel Bayesian DNA motif comparison method for clustering and retrieval. PLoS Comput Biol 2008;4(2).

(112) Capaldi AP, Kaplan T, Liu Y, Habib N, Regev A, Friedman N, et al. Structure and function of a transcriptional network activated by the MAPK Hog1. Nat Genet 2008;40(11):1300-1306.

(113) Template based inference in symmetric relational Markov random fields. Proceedings of the 23rd Conference on Uncertainty in Artificial Intelligence, UAI 2007; 2007.

(114) Wapinski I, Pfeffer A, Friedman N, Regev A. Natural history and evolutionary principles of gene duplication in fungi. Nature 2007;449(7158):54-61.

(115) Elidan G, Nachman I, Friedman N. "Ideal parent" structure learning for continuous variable Bayesian networks. J Mach Learn Res 2007;8:1799-1833.

(116) Wapinski I, Pfeffer A, Friedman N, Regev A. Automatic genome-wide reconstruction of phylogenetic gene trees. Bioinformatics 2007;23(13):i549-i558.

(117) Dion MF, Kaplan T, Kim M, Buratowski S, Friedman N, Rando OJ. Dynamics of replication-independent histone turnover in budding yeast. Science 2007;315(5817):1405-1408.

(118) Ninio M, Privman E, Pupko T, Friedman N. Phylogeny reconstruction: Increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates. Bioinformatics 2007;23(2):e136-e141.

(119) Dimension reduction in singularly perturbed continuous-time Bayesian networks. Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence, UAI 2006; 2006.

(120) Continuous time Markov networks. Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence, UAI 2006; 2006.

(121) Friedman N, Cai L, Xie XS. Linking stochastic dynamics to population distribution: An analytical framework of gene expression. Phys Rev Lett 2006;97(16).

(122) Slonim N, Friedman N, Tishby N. Multivariate information bottleneck. Neural Comp 2006;18(8):1739-1789.

(123) Cai L, Friedman N, Xie XS. Stochastic protein expression in individual cells at the single molecule level. Nature 2006;440(7082):358-362.

(124) Jaimovich A, Elidan G, Margalit H, Friedman N. Towards an integrated protein-protein interaction network: A relational Markov network approach. J Comput Biol 2006;13(2):145-164.

(125) Chih LL, Kaplan T, Kim M, Buratowski S, Schreiber SL, Friedman N, et al. Single-nucleosome mapping of histone modifications in S. cerevisiae. PloS Biol 2005;3(10).

(126) Mayrose I, Friedman N, Pupko T. A gamma mixture model better accounts for among site rate heterogeneity. Bioinformatics 2005;21(SUPPL. 2):ii151-ii158.

(127) Segal E, Pe'er D, Regev A, Koller D, Friedman N. Learning module networks. J Mach Learn Res 2005;6.

(128) Elidan G, Friedman N. Learning hidden variable networks: The information bottleneck approach. J Mach Learn Res 2005;6.

(129) Kobiler O, Rokney A, Friedman N, Court DL, Stavans J, Oppenheim AB. Quantitative kinetic analysis of the bacteriophage λ genetic network. Proc Natl Acad Sci U S A 2005;102(12):4470-4475.

(130) Barash Y, Elidan G, Kaplan T, Friedman N. CIS: Compound importance sampling method for protein-DNA binding site p-value estimation. Bioinformatics 2005;21(5):596-600.

(131) Kaplan T, Friedman N, Margalit H. Ab initio prediction of transcription factor targets using structural knowledge. PLoS Comput Biol 2005;1(1):0005-0013.

(132) Predicting transcription factor binding sites using structural knowledge. Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science); 2005.

(133) Towards an integrated protein-protein interaction network. Lecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science); 2005.

(134) Friedman N, Vardi S, Ronen M, Alon U, Stavans J. Precise temporal modulation in the response of the SOS DNA repair network in individual bacteria. PloS Biol 2005;3(7):1261-1268.

(135) Segal E, Friedman N, Kaminski N, Regev A, Koller D. From signatures to models: Understanding cancer using microarrays. Nat Genet 2005;37(6S):S38-S45.

(136) Segman RH, Shefi N, Goltser-Dubner T, Friedman N, Kaminski N, Shalev AY. Peripheral blood mononuclear cell gene expression profiles identify emergent post-traumatic stress disorder among trauma survivors. Mol Psychiatry 2005;10(5):500-513.

(137) Nachman I, Regev A, Friedman N. Inferring quantitative models of regulatory networks from expression data. Bioinformatics 2004;20(SUPPL. 1):i248-i256.

(138) Marion RM, Regev A, Segal E, Barash Y, Koller D, Friedman N, et al. Sfp1 is a stress- and nutrient-sensitive regulator of ribosomal protein gene expression. Proc Natl Acad Sci U S A 2004;101(40):14315-14322.

(139) Segal E, Friedman N, Koller D, Regev A. A module map showing conditional activity of expression modules in cancer. Nat Genet 2004;36(10):1090-1098.

(140) Horowitz M, Eli-Berchoer L, Wapinski I, Friedman N, Kodesh E. Stress-related genomic responses during the course of heat acclimation and its association with ischemic-reperfusion cross-tolerance. J Appl Physiol 2004;97(4):1496-1507.

(141) Sagi D, Friedman N, Vorgias C, Oppenheim AB, Stavans J. Modulation of DNA conformations through the formation of alternative high-order HU-DNA complexes. J Mol Biol 2004;341(2):419-428.

(142) Barash Y, Dehan E, Krupsky M, Franklin W, Geraci M, Friedman N, et al. Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays. Bioinformatics 2004;20(6):839-846.

(143) Achiron A, Gurevich M, Friedman N, Kaminski N, Mandel M. Blood Transcriptional Signatures of Multiple Sclerosis: Unique Gene Expression of Disease Activity. Ann Neurol 2004;55(3):410-417.

(144) Friedman N. Inferring Cellular Networks Using Probabilistic Graphical Models. Science 2004;303(5659):799-805.

(145) Bejerano G, Friedman N, Tishby N. Efficient exact p-value computation for small sample, sparse, and surprising categorical data. J Comput Biol 2004;11(5):867-886.

(146) Kaplan A, Friedman N, Andersen M, Davidson N. Stable regions and singular trajectories in chaotic soft-wall billiards. Phys D Nonlinear Phenom 2004;187(1-4):136-145.

(147) Segal E, Shapira M, Regev A, Pe'er D, Botstein D, Koller D, et al. Module networks: Identifying regulatory modules and their condition-specific regulators from gene expression data. Nat Genet 2003;34(2):166-176.

(148) Getoor L, Friedman N, Koller D, Taskar B. Learning probabilistic models of link structure. J Mach Learn Res 2003;3(4-5):679-707.

(149) Modeling dependencies in protein-DNA binding sites. Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB; 2003.

(150) Friedman N, Koller D. Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks. Mach Learn 2003;50(1-2):95-125.

(151) Dekel B, Burakova T, Arditti FD, Reich-Zeliger S, Milstein O, Aviel-Ronen S, et al. Human and porcine early kidney precursors as a new source for transplantation. Nat Med 2003;9(1):53-60.

(152) Data perturbation for escaping local maxima in learning. Proceedings of the National Conference on Artificial Intelligence; 2002.

(153) Barash Y, Friedman N. Context-specific Bayesian clustering for gene expression data. J Comput Biol 2002;9(2):169-191.

(154) Andersen MF, Kaplan A, Friedman N, Davidson N. Stable islands in chaotic atom-optics billiards, caused by curved trajectories. J Phys B At Mol Opt Phys 2002;35(9):2183-2190.

(155) Agglomerative multivariate information bottleneck. Advances in Neural Information Processing Systems; 2002.

(156) Slonim N, Friedman N, Tishby N. Unsupervised document classification using sequential information maximization. SIGIR Forum 2002:129-136.

(157) Shalev-Shwartz S, Dubnov S, Friedman N, Singer Y. Robust temporal and spectral modeling for query by melody. SIGIR Forum 2002:331-338.

(158) Pupko T, Pe'er I, Hasegawa M, Graur D, Friedman N. A branch-and-bound algorithm for the inference of ancestral amino-acid sequences when the replacement rate varies among sites: Application to the evolution of five gene families. Bioinformatics 2002;18(8):1116-1123.

(159) From promoter sequence to expression: A probabilistic framework. Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB; 2002.

(160) An optimized single-beam dark optical trap. Conference on Quantum Electronics and Laser Science (QELS) - Technical Digest Series; 2002.

(161) Controlling dynamics in atom-optics billiards with external force fields. Conference on Quantum Electronics and Laser Science (QELS) - Technical Digest Series; 2002.

(162) Cojocaru G, Friedman N, Krupsky M, Yaron P, Simansky D, Yellin A, et al. Transcriptional profiling of non-small cell lung cancer using oligonucleotide microarrays. Chest 2002;121(3):44S.

(163) Friedman N, Ninio M, Pe'er I, Pupko T. A structural EM algorithm for phylogenetic inference. J Comput Biol 2002;9(2):331-353.

(164) Friedman N, Kaminski N. Statistical methods for analyzing gene expression data for cancer research. Ernst Schering Res Found Workshop 2002(38):109-131.

(165) Kaminski N, Friedman N. Practical approaches to analyzing results of microarray experiments. Am J Resp Cell Mol Biol 2002;27(2):125-132.

(166) Friedman N, Kaplan A, Davidson N. Dark optical traps for cold atoms. Adv At Mol Opt Phys 2002;48(C):99-151.

(167) Kaplan A, Friedman N, Davidson N. Optimized single-beam dark optical trap. J Opt Soc Am B 2002;19(6):1233-1238.

(168) Kaplan A, Friedman N, Andersen M, Davidson N. Observation of islands of stability in soft wall atom-optics billiards. Phys Rev Lett 2001;87(27):274101-274101-4.

(169) Kaplan A, Friedman N, Andersen M, Davidson N. Observation of islands of stability in soft wall atom-optics billiards. Phys Rev Lett 2001;87(27 I):2741011-2741014.

(170) Brafman RI, Friedman N. On decision-theoretic foundations for defaults. Artif Intell 2001;133(1-2):1-33.

(171) Kaplan A, Friedman N, Davidson N. Acousto-optic lens with very fast focus scanning. Opt Lett 2001;26(14):1078-1080.

(172) Friedman N, Halpern JY. Plausibility measures and default reasoning. J ACM 2001;48(4):648-685.

(173) Friedman N, Kaplan A, Carasso D, Davidson N. Observation of chaotic and regular dynamics in atom-optics billiards. Phys Rev Lett 2001;86(8):1518-1521.

(174) Kaminski N, Pilzer D, Cojocaru1 G, Margalit O, Friedman N, Reinstein S, et al. A composite genomic profile of lung cancer in smokers and nonsmokers. Nat Genet 2001;27(4S):63.

(175) Barash Y, Bejerano G, Friedman N. A simple hyper-geometric approach for discovering putative transcription factor binding sites. Lect Notes Comput Sci 2001;2149:278-293.

(176) Controlling the stability of motion in atom-optics billiards. Technical Digest - Summaries of Papers Presented at the Quantum Electronics and Laser Science Conference, QELS 2001; 2001.

(177) Discovering hidden variables: A structure-based approach. Advances in Neural Information Processing Systems; 2001.

(178) Pe'er D, Regev A, Elidan G, Friedman N. Inferring subnetworks from perturbed expression profiles. Bioinformatics 2001;17(SUPPL. 1):S215-S224.

(179) Segal E, Taskar B, Gasch A, Friedman N, Koller D. Rich probabilistic models for gene expression. Bioinformatics 2001;17(SUPPL. 1):S243-S252.

(180) A structural EM algorithm for phylogenetic inference. Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB; 2001.

(181) Class discovery in gene expression data. Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB; 2001.

(182) Context-specific Bayesian clustering for gene expression data. Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB; 2001.

(183) Friedman N, Kaplan A, Davidson N. Acousto-optic scanning system with very fast nonlinear scans. Opt Lett 2000;25(24):1762-1764.

(184) Friedman N, Linial M, Nachman I, Pe'er D. Using Bayesian networks to analyze expression data. J Comput Biol 2000;7(3-4):601-620.

(185) Ben-Dor A, Bruhn L, Friedman N, Nachman I, Schummer M, Yakhini Z. Tissue classification with gene expression profiles. J Comput Biol 2000;7(3-4):559-583.

(186) Khaykovich L, Baluschev S, Friedman N, Ozeri R, Fathi D, Davidson N. High sensitivity two-photon spectroscopy of cold atoms in a dark optical trap, using an electron shelving scheme. Conf Quant Electron Laser Sci QELS Tech Dig Ser 2000:141-142.

(187) Friedman N, Khaykovich L, Ozeri R, Davidson N. Atom optics with time-averaged optical potentials using a rapidly scanning laser beam. Conf Quant Electron Laser Sci QELS Tech Dig Ser 2000:166-167.

(188) Baluschev S, Friedman N, Khaykovich L, Carasso D, Johns B, Davidson N. Tunable and frequency-stabilized diode laser with a doppler-free two-photon zeeman lock. Appl Opt 2000;39(27):4970-4974.

(189) Khaykovich L, Friedman N, Baluschev S, Fathi D, Davidson N. Ultrasensitive two-photon spectroscopy based on long spin-relaxation time in a dark optical trap. Europhys Lett 2000;50(4):454-459.

(190) Friedman N, Khaykovich L, Ozeri R, Davidson N. Compression of cold atoms to very high densities in a rotating-beam blue-detuned optical trap. Phys Rev A 2000;61(3):4.

(191) Friedman N, Halpern JY, Koller D. First-Order Conditional Logic for Default Reasoning Revisited. ACM Trans Comput Log 2000;1(2):175-207.

(192) Friedman N, Khaykovich L, Ozeri R, Davidson N. Compression of cold atoms to very high densities in a rotating-beam blue-detuned optical trap. Phys Rev A 2000;61(3):314031-314034.

(193) Ozeri R, Khaykovich L, Friedman N, Davidson N. Large-volume single-beam dark optical trap for atoms using binary phase elements. J Opt Soc Am B 2000;17(7):1113-1116.

(194) Tissue classification with gene expression profiles. Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB; 2000.

(195) Sensitive spectroscopy and atom dynamics in a single beam optical trap. IQEC, International Quantum Electronics Conference Proceedings; 2000.

(196) Using Bayesian networks to analyze expression data. Proceedings of the Annual International Conference on Computational Molecular Biology, RECOMB; 2000.

(197) Learning probabilistic relational models. IJCAI International Joint Conference on Artificial Intelligence; 1999.

(198) Efficient Bayesian parameter estimation in large discrete domains. Advances in Neural Information Processing Systems; 1999.

(199) Friedman N, Halpern JY. Belief revision: A critique. J Logic Lang Inf 1999;8(4):401-420.

(200) Friedman N, Halpern JY. Modeling belief in dynamic systems Part II: revision and update. J Artif Intell Res 1999;10:117-167.

(201) Khaykovich L, Friedman N, Ozeri R, Davidson N. Compression of cold atoms to very high densities in a novel rotating-beam blue-detuned optical dipole trap. IQEC Int Quantum Electron Conf Proc 1999:312-313.

(202) Friedman N, Halpern JY. Plausibility measures and default reasoning: an overview. Proc Symp Logic Comput Sci 1999:130-135.

(203) Wolf Y, Kalish E, Badani E, Friedman N, Hauben DJ. Rubber foam and staples: Do they secure skin grafts? A model analysis and proposal of pressure enhancement techniques. Ann Plast Surg 1998;40(2):149-155.

(204) Generalized prioritized sweeping. Advances in Neural Information Processing Systems; 1998.

(205) Belief revision with unreliable observations. Proceedings of the National Conference on Artificial Intelligence; 1998.

(206) Structured representation of complex stochastic systems. Proceedings of the National Conference on Artificial Intelligence; 1998.

(207) Bayesian Q-learning. Proceedings of the National Conference on Artificial Intelligence; 1998.

(208) Friedman N, Ozeri R, Davidson N. Quantum reflection of atoms from a periodic dipole potential. J Opt Soc Am B 1998;15(6):1749-1756.

(209) Challenge: What is the impact of Bayesian networks on learning? IJCAI International Joint Conference on Artificial Intelligence; 1997.

(210) Wavelength dependence of the principal states of polarization in short segments of doped fiber. Proceedings of SPIE - The International Society for Optical Engineering; 1997.

(211) Friedman N, Eyal A, Tur M. The use of the principal states of polarization to describe tunability in a fiber laser. IEEE J Quantum Electron 1997;33(5):642-648.

(212) Friedman N, Geiger D, Goldszmidt M. Bayesian Network Classifiers. Mach Learn 1997;29(2-3):131-163.

(213) Friedman N, Halpern JY. Modeling belief in dynamic systems, Part I: Foundations. Artif Intell 1997;95(2):257-316.

(214) First-order conditional logic revisited. Proceedings of the National Conference on Artificial Intelligence; 1996.

(215) Building classifiers using Bayesian networks. Proceedings of the National Conference on Artificial Intelligence; 1996.

(216) Plausibility measures and default reasoning. Proceedings of the National Conference on Artificial Intelligence; 1996.

(217) Conditional logics of belief change. Proceedings of the National Conference on Artificial Intelligence; 1994.

(218) Ghera U, Friedman N, Tur M. Polarization related phenomena in Nd-doped fiber lasers. Opt Mater 1994;4(1):73-80.

(219) Ghera U, Friedman N, Tur M. A Fiber Laser with a Comb-Like Spectrum. IEEE Photonics Technol Lett 1993;5(10):1159-1161.