1.            Piran, Z. & Nitzan, M. SiFT: uncovering hidden biological processes by probabilistic filtering of single-cell data. Nat. Commun. 15, (2024).

2.            Moriel, N., Memet, E. & Nitzan, M. Optimal sequencing budget allocation for trajectory reconstruction of single cells. Bioinformatics 40, i446–i452 (2024).

3.            Moriel, N., Ricci, M. & Nitzan, M. LET’S DO THE TIME-WARP-ATTEND: LEARNING TOPOLOGICAL INVARIANTS OF DYNAMICAL SYSTEMS. in 12th International Conference on Learning Representations, ICLR 2024 (International Conference on Learning Representations, ICLR, 2024).

4.            Piran, Z., Cohen, N., Hoshen, Y. & Nitzan, M. Disentanglement of single-cell data with biolord. Nat. Biotechnol. (2024) doi:10.1038/s41587-023-02079-x.

5.            Karin, J., Bornfeld, Y. & Nitzan, M. scPrisma infers, filters and enhances topological signals in single-cell data using spectral template matching. Nat. Biotechnol. 41, 1645–1654 (2023).

6.            Mages, S. et al. TACCO unifies annotation transfer and decomposition of cell identities for single-cell and spatial omics. Nat. Biotechnol. 41, 1465–1473 (2023).

7.            Heumos, L. et al. Best practices for single-cell analysis across modalities. Nat. Rev. Genet. 24, 550–572 (2023).

8.            Sheng, Y., Barak, B. & Nitzan, M. Robust reconstruction of single-cell RNA-seq data with iterative gene weight updates. Bioinformatics 39, I423–I430 (2023).

9.            Adler, M. et al. Emergence of division of labor in tissues through cell interactions and spatial cues. Cell Rep. 42, (2023).

10.          Ricci, M., Moriel, N., Piran, Z. & Nitzan, M. PHASE2VEC: DYNAMICAL SYSTEMS EMBEDDING WITH A PHYSICS-INFORMED CONVOLUTIONAL NETWORK. in 11th International Conference on Learning Representations, ICLR 2023 (International Conference on Learning Representations, ICLR, 2023).

11.          Guo, Y., Nitzan, M. & Brenner, M. P. Programming cell growth into different cluster shapes using diffusible signals. PLoS Comput. Biol. 17, (2021).

12.          Biancalani, T. et al. Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram. Nat. Methods 18, 1352–1362 (2021).

13.          Moriel, N. et al. NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport. Nat. Protoc. 16, 4177–4200 (2021).

14.          Sadeh, R. 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. 39, 642 (2021).

15.          Sadeh, R. et al. ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells of origin. Nat. Biotechnol. 39, 586–598 (2021).

16.          Nitzan, M. & Brenner, M. P. Revealing lineage-related signals in single-cell gene expression using random matrix theory. Proc. Natl. Acad. Sci. U. S. A. 118, (2021).

17.          Haralampiev, I. et al. Selective flexible packaging pathways of the segmented genome of influenza A virus. Nat. Commun. 11, (2020).

18.          Holmes, A. B. et al. Single-cell analysis of germinal-center B cells informs on lymphoma cell of origin and outcome. J. Exp. Med. 217, (2020).

19.          Forrow, A. et al. Statistical optimal transport via factored couplings. in 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019 (PLMR, 2020).

20.          Nitzan, M., Karaiskos, N., Friedman, N. & Rajewsky, N. Gene expression cartography. Nature 576, 132–137 (2019).

21.          Nitzan, M., Nitzan, S. & Segal-Halevi, E. Flexible level-1 consensus ensuring stable social choice: analysis and algorithms. Soc. Choice Welfare 50, 457–479 (2018).

22.          Schurr, R. et al. Temporal dissociation of neocortical and hippocampal contributions to mental time travel using intracranial recordings in humans. Front. Comput. Neurosci. 12, (2018).

23.          Casadiego, J., Nitzan, M., Hallerberg, S. & Timme, M. Model-free inference of direct network interactions from nonlinear collective dynamics. Nat. Commun. 8, (2017).

24.          Nitzan, M., Rehani, R. & Margalit, H. Integration of Bacterial Small RNAs in Regulatory Networks. Annual Review of Biophysics vol. 46 131–148 (2017).

25.          Nitzan, M., Casadiego, J. & Timme, M. Revealing physical interaction networks from statistics of collective dynamics. Sci. Adv. 3, (2017).

26.          Peer, M., Nitzan, M., Bick, A. S., Levin, N. & Arzy, S. Evidence for functional networks within the human brain’s white matter. J. Neurosci. 37, 6394–6407 (2017).

27.          Nitzan, M., Katzav, E., Kühn, R. & Biham, O. Distance distribution in configuration-model networks. Phys. Rev. E 93, (2016).

28.          Rosenfeld, N., Nitzan, M. & Globerson, A. Discriminative learning of infection models. in 9th ACM International Conference on Web Search and Data Mining, WSDM 2016 563–572 (Association for Computing Machinery, Inc, 2016). doi:10.1145/2835776.2835802.

29.          Katzav, E. et al. Analytical results for the distribution of shortest path lengths in random networks. EPL 111, (2015).

30.          Nitzan, M., Shimoni, Y., Rosolio, O., Margalit, H. & Biham, O. Stochastic analysis of bistability in coherent mixed feedback loops combining transcriptional and posttranscriptional regulations. Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys. 91, (2015).

31.          Sajman, J. et al. Degradation of Ndd1 by APC/CCdh1 generates a feed forward loop that times mitotic protein accumulation. Nat. Commun. 6, (2015).

32.          Nitzan, M., Mintzer, S. & Margalit, H. Approaches and developments in studying the human microbiome network. Isr. J. Ecol. Evol. 61, 90–94 (2015).

33.          Nitzan, M. et al. A defense-offense multi-layered regulatory switch in a pathogenic bacterium. Nucleic Acids Res. 43, 1357–1369 (2015).

34.          Nitzan, M., Steiman-Shimony, A., Altuvia, Y., Biham, O. & Margalit, H. Interactions between distant ceRNAs in regulatory networks. Biophys. J. 106, 2254–2266 (2014).

35.          Nitzan, M., Wassarman, K. M., Biham, O. & Margalit, H. Global regulation of transcription by a small RNA: A quantitative view. Biophys. J. 106, 1205–1214 (2014).

36.          Peer, M. et al. Reversible functional connectivity disturbances during transient global amnesia. Ann. Neurol. 75, 634–643 (2014).

37.          Mills, E., Baruch, K., Aviv, G., Nitzan, M. & Rosenshine, I. Dynamics of the type III secretion system activity of enteropathogenic Escherichia coli. MBio 4, (2013).

38.          Zahavi, E. E. et al. Bundle-forming pilus retraction enhances enteropathogenic Escherichia coli infectivity. Mol. Biol. Cell 22, 2436–2447 (2011).