Publications

updated: 30.05.2022

 

List of Publications

 

24. A. Dolitzky, G. Shapira, S. Grisaru-Tal, I. Hazut, S. Avlas, Y. Gordon, M. Itan, N. Shomron and A. Munitz (2021) Transcriptional Profiling of Mouse Eosinophils Identifies Distinct Gene Signatures Following Cellular ActivationFront. Immunol.,  https://doi.org/10.3389/fimmu.2021.802839. 

 

23. G. Shapira, R. Abu Hamad, C. Weiner, N. Rainy, R. Sorek-Abramovich, P. Benveniste-Levkovitz, R. Rock, E. Avnat, O. Levtzion-Korach, A. Bar Chaim, N. Shomron (2022) Population differences in antibody response to SARS-CoV-2 infection and BNT162b2 vaccination. FASEB Journal, https://doi.org/10.1096/fj.202101492R.

 

22. K. Halabi, E. Levy Karin, L. Guéguen, I. Mayrose (2021) A Codon Model for Associating Phenotypic Traits with Altered Selective Patterns of Sequence Evolution. Systematic Biology, Volume 70, Issue 3, Pages 608–622, https://doi.org/10.1093/sysbio/syaa087. 

 

21. D. Groenewoud, A. Shye, R. Elkon (2022) Incorporating regulatory interactions into gene-set analyses for GWAS data: A controlled analysis with the MAGMA tool. PLoS Comp Bio. https://doi.org/10.1371/journal.pcbi.1009908.

 

20. A. Gayoso, Z. Steier, R. Lopez, J. Regier, K. L. Nazor, A. Streets & N. Yosef (2021) Joint probabilistic modeling of single-cell multi-omic data with totalVI. Nature Methods, volume 18, pages272–282 (2021).

 

19. T. A. Hait,  R. Elkon,  and R. Shamir (2022) CT-FOCS: a novel method for inferring cell type-specific enhancer-promoter maps.  Nucleic Acids Research, gkac048, https://doi.org/10.1093/nar/gkac048 (2022).

 

18. H. Levi, N. Rahmanian, R. Elkon, R. Shamir (2022) The DOMINO web-server for active module identification analysisBioinformatics, btac067, https://doi.org/10.1093/bioinformatics/btac067.  

 

17. B. Yao,  C. Hsu, G. Goldner, Y. Michaeli,  Y. Ebenstein,  and J. Listgarten (2021) Nanopore callers for epigenetics from limited supervised databioRxiv, doi: https://doi.org/10.1101/2021.06.17.448800.

 

16. G. Gilad, I. Sason and R. Sharan (2021) An automated approach for determining the number of components in non-negative matrix factorization with application to mutational signature learning (2021) Machine Learning: Science and Technology, Volume 2, Number 1, 015013.

 

15. Y. Kim,* M. D.M. Leiserson,* P. Moorjani,* R. Sharan,* D. Wojtowicz,* and T. M. Przytycka* (2021) "Mutational Signatures: From Methods to Mechanisms". Annual Review of Biomedical Data Science, Vol. 4:189-206 (Volume publication date July 2021), https://doi.org/10.1146/annurev-biodatasci-122320-120920. *equal contribution.

 

14. S. Bahiri Elitzur, R. Cohen-Kupiec, D. Yacobi, L. Fine, B. Apt, A. Diament & T. Tuller (2021) Prokaryotic rRNA-mRNA interactions are involved in all translation steps and shape bacterial transcripts. RNA Biology, Pages 684-698 | Published online: 29 Sep 2021, https://doi.org/10.1080/15476286.2021.1978767.

 

13. I. Israel-Elgali, L. Hertzberg, G. Shapira, A. Segev, I. Krieger, U. Nitzan, Y. Bloch, N. Pillar, O. Mayer, A. Weizman, D. Gurwitz, N. Shomron (2021) Blood transcriptional response to treatment-resistant depression during electroconvulsive therapyJournal of Psychiatric Research, Volume 141, 2021, Pages 92-103, ISSN 0022-3956, https://doi.org/10.1016/j.jpsychires.2021.06.039.

 

12.  S. Belaish,  I. Israel-Elgali,  G. Shapira,  I. Krieger, A. Segev, U. Nitzan, M. Majer, Y. Bloch, A. Weizman, D. Gurwitz, N. Shomron & L. Hertzberg (2021) Genome wide analysis implicates upregulation of proteasome pathway in major depressive disorder. Transl Psychiatry 11, 409 (2021). https://doi.org/10.1038/s41398-021-01529-x.

 

11. K. Halabi, I. Mayrose (2021) Mechanisms Underlying Host Range Variation in Flavivirus: From Empirical Knowledge to Predictive Models. J Mol Evol (2021). https://doi.org/10.1007/s00239-021-10013-5.

 

10. H. Levi, R. Elkon, R. Shamir (2021) "DOMINO - a novel network-based active module identification algorithm with reduced rate of false calls". Molecular Systems Biology 17:e9593 (2021).

 

9.  M. Levy, A. Frishberg, I. Gat-Viks (2020) Inferring cellular heterogeneity of associations from single cell genomics. Bioinformatics, Volume 36, Issue 11, June 2020, Pages 3466–3473, https://doi.org/10.1093/bioinformatics/btaa151.

 

8.  D. Levin,  and  T. Tuller (2020) Whole cell biophysical modeling of codon-tRNA competition reveals novel insights related to translation dynamics. PLoS Compt. Biol., https://doi.org/10.1371/journal.pcbi.1008038.

 

7. D.D. Erdmann-Pham, K. Dao Duc, and Y.S. Song (2020) The key parameters that govern translation efficiency. Cell Systems, Vol. 10, Issue 2, (2020) 183-192.e6.

 

6. T. S. Hsieh, C. Cattoglio, E. Slobodyanyuk, A. S. Hansen, O. J. Rando, R. Tjian, X. Darzacq (2020) Resolving the 3D Landscape of Transcription-Linked Mammalian Chromatin Folding. Mol Cell. 2020 May 7;78(3):539-553.e8. 

 

5. H. Wang, L. Pipes, R. Nielsen (2020) Synonymous mutations and the molecular evolution of SARS-CoV-2 origins. Virus Evolution, veaa098, https://doi.org/10.1093/ve/veaa098. 

 

4. L. Pipes, H. Wang, J. P. Huelsenbeck, R. Nielsen (2020) Assessing Uncertainty in the Rooting of the SARS-CoV-2 Phylogeny. Molecular Biology and Evolution, msaa316, https://doi.org/10.1093/molbev/msaa316.

 

3. M. Chintalapati  and P. Moorjani (2020) Evolution of the mutation rate across primates. Current Opinion in Genetics & Development, 62, 58-64.

 

2. T. Kustin and A. Stern (2020) Biased mutation and selection in RNA virusesMolecular Biology and Evolution, msaa247, https://doi.org/10.1093/molbev/msaa247.

 

1. G. Ling, D. Miller, R. Nielsen, A. Stern (2019) A Bayesian framework for inferring the influence of sequence context on point mutations. Molecular Biology and Evolution, msz248, https://doi.org/10.1093/molbev/msz248.

 

 

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