Publications

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• Pour M, Nachman I. (2019) 
  Building Blastocysts from Stem Cells. Preview
  Stem Cell Reports. 2019 Sep 10;13(3):437-439. doi: 10.1016/j.stemcr.2019.08.009.
   

• Pour, AS Kumar, M Walther, L Wittler, A Meissner, I Nachman ( 2019)
  Emergence and patterning dynamics of mouse definitive endoderm‏.
  bioRxiv, 728642‏
   

• Thakurela, S.†, Sindhu, C.†,, Yurkovsky, E.†,  Smith, Z.D.†, Riemenschneider, C.,  Nachman, I.**,  Meissner, A.** (2019)
  Differential regulation of OCT4 targets facilitates reacquisition of pluripotency.
  Nature Communications, 2019 Sep 30;10(1):4444
   

• Tanner N, Kleifeld O, Nachman I, Prag G. (2019)
  Remodeling Membrane Binding by Mono-Ubiquitylation. (2019)
  Biomolecules. 2019 Jul 31;9(8). pii: E325. doi: 10.3390/biom9080325.
   

• Levin, T., Sade, H., Ben-Shabat Binyamini, R., Pour, M., Nachman, I., Lellouche, JP. (2019)
  Tungsten Disulfide-Based Nanocomposites for Photothermal Therapy
  Beilstein J. Nanotechnol. 2019, 10, 811-822
   

• Kaminski Strauss, S.,  et. al.(2019)
  Evolthon: a community endeavor to evolve lab evolution. 
  PLoS Biology. 29;17(3):e3000182. doi: 10.1371/journal.pbio.3000182.
   

• Sagy, N., Slovin, S., Allalouf, M., Pour, M., Savyon, G., Boxman, J., Nachman, I. (2019)
  Prediction and control of symmetry breaking in embryoid bodies by environment and signal integration.
  Development 2019 146: dev181917
   

• Nandi S, Bhunia S, Zeiri L, Pour M, Nachman I, Reichmann D, Lellouche JP, Jelinek R. (2017)
  Bifunctional Carbon-Dot-WS2 Nanorods for Photothermal Therapy and Cell Imaging.
  Chemistry. 2017 Jan 18;23(4):963-969. doi: 10.1002/chem.201604787.
   

• Boxman, J.†, Sagy, N.†, Achanta, S., Vadigepalli, R., Nachman, I. (2016)
  Integrated live imaging and molecular profiling of embryoid bodies reveals a synchronized progression of early differentiation.
  Scientific Reports 6, Article number: 31623 (2016)  doi:10.1038/srep31623

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• Cohen, A., Weindling, E., Rabinovich, E., Nachman, I., Fuchs, S., Chuartzman, S., Gal, L., Schuldiner, M., Bar-Nun, S. (2016)
  Water-Transfer Slows Aging in Saccharomyces cerevisiae.
  PLoS One 10;11(2), e0148650.

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• Y. Goldshmidt†, E. Yurkovsky†, A. Reif, R. Rosner, A. Akiva, Nachman I. (2015)
  Control of relative timing and stoichiometry by a master regulator 
  PLoS One 10(5), 2015 e0127339.  

 

• M. Pour†, I. Pilzer†, R. Rosner, ZD. Smith, A. Meissner, I. Nachman (2015)  

       Epigenetic predisposition to reprogramming fates in somatic cells. 

       EMBO reports (2015) 16, 370-378.

 

• E. Yurkovsky, I. Nachman (2013).

       Event timing at the single cell level. 

       Brief Funct Genomics.  2013 Mar;12(2):90-8.

 

• D. Salomon†, E. Bosis†, D. Dar, I. Nachman, G. Sessa (2012)

       Expression of Pseudomonas syringae type III effectors in yeast under stress conditions reveals that HopX1 attenuates activation          of the high osmolarity glycerol MAP kinase pathway. 

       Microbiology 158(11), pp. 2859-69.

 

• G. Aidelberg†, Y. Goldschmidt†, I. Nachman (2012).

       A microfluidic device for studying multiple distinct strains.

        J. Vis. Exp. e4257 10.3791/4257, DOI : 10.3791/4257.

 

• A. Cohen, L. Ross, I. Nachman, S. Bar-Nun (2012).

       Aggregation of PolyQ Proteins Is Increased upon Yeast Aging and Affected by Sir2 and Hsf1: Novel Quantitative Biochemical and         Microscopic Assays. 

       PLoS One 7(9): e44785. doi:10.1371/journal.pone.0044785

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• Z. D. Smith†, I. Nachman†, A. Regev, A. Meissner (2010)

       Dynamic single cell imaging of direct reprogramming reveals an early specifying event. 

       Nature Biotechnology 28(5), 521 – 526

 

• I. Nachman, A, Regev (2009)

      BRNI: Modular Analysis of Transcriptional Regulatory Programs. 

      BMC Bioinformatics 2009, 10:155.

 

• I. Nachman, S. Ramanathan (2008).

      HIV-1 Positive Feedback and Lytic Fate.

      Nature Genetics 2008 Apr;40(4):382-3. [News & Views].

 

• I. Nachman, A, Regev, S. Ramanathan (2007).

      Dissecting Timing Variability in Yeast Meiosis. 

      Cell 131(3), 544 – 556.

 

• G. Elidan, I. Nachman, N. Friedman (2007).

       “Ideal Parent” Structure Learning for Continuous Variables Bayesian Networks. 

       JMLR 8, 1799–1833.

 

• I. Nachman, A, Regev, N. Friedman (2004).

      Inferring Quantitative Models of Regulatory Networks From Expression Data. Proc. 12’th International Conference on Intelligent          Systems in Molecular Biology (ISMB04);

      Bioinformatics 20:I248–I256.

 

• I. Nachman†, G. Elidan†, N. Friedman (2004).

      “Ideal Parent” Structure Learning for Continuous Variables Networks. Proc.

      20’th Conference on Uncertainty in Artificial Intel ligence (UAI04).

 

• N. Friedman , I. Nachman (2000).

      Gaussian Process Networks. Proc.

      16’th Conf. on Uncertainty in Artificial Intel ligence (UAI00).

 

• N. Friedman , M. Linial, I. Nachman, D. Pe’er (2000).

       Using Bayesian Networks to Analyze Expression Data. 

        J. Computational Biology 7 (3,4), 601 – 620.

 

• A. Ben-Dor, L. Bruhn, N. Friedman , I. Nachman, M. Schummer, Z. Yakhini (2000).

       Tissue Classification with Gene Expression Profiles.

        J. Computational Biology 7 (3,4), 559 – 583.

 

• N. Friedman , M. Linial, I. Nachman, D. Pe’er (2000).

      Using Bayesian Networks to Analyze Expression Data. Proc.

       The 4’th Annual International Conference on Computational Molecular Biology (RECOMB00).

 

• A. Ben-Dor, L. Bruhn, N. Friedman , I. Nachman, M. Schummer, Z. Yakhini (2000).

       Tissue Classification with Gene Expression Profiles. Proc.

       The 4’th Annual International Conference on Computational Molecular Biology (RECOMB00).

 

• N. Friedman , I. Nachman, D. Pe’er (1999).

       Learning Bayesian Network Structure from Massive Datasets: The Sparse Candidate Algorithm. Proc.

       15’th Conf. on Uncertaintys in Artificial Intel ligence (UAI99).

† equal contribution