Publications
List of Publications
35. Lynn, N., Tuller, T. (2024) Detecting and understanding meaningful cancerous mutations based on computational models of mRNA splicing. npj Syst Biol Appl 10, 25 (2024). https://doi.org/10.1038/s41540-024-00351-7.
34. Arnon E, Cain S, Uzan A, Nathan R, Spiegel O & Toledo S. Robust Time-of-Arrival Location-Estimation Algorithms for Wildlife Tracking. Sensors 2023. 23, 9460.
33. Arnon E, Uzan A, Handel M, Cain S, Toledo S & Spiegel O. ViewShedR: A new open-source tool for cumulative, subtractive, and elevated line-of-sight analysis. Royal Society Open Science. 2023. 10(6). 221333.
32. Mayer, O.; Bugis, J.; Kozlova, D.; Leemann, A.; Mansur, S.; Peerutin, I.; Mendelovich, N.; Mazin, M.; Friedmann‐Morvinski, D.; Shomron, N. Cytoskeletal Protein Palladin in Adult Gliomas Predicts Disease Incidence, Progression, and Prognosis. Cancers 2022, 14, 5130. https://doi.org/10.3390/ cancers14205130.
31. H. Levi, S. Carmi, S. Rosset, R. Yerushalmi, A. Zick, T. Yablonski-Peretz, .... (127 members of the BCAC Consortium)..., S. Ben-Shachar, N. Elefant*, R. Shamir* and R. Elkon* (2023) Evaluation of European-based polygenic risk score for breast cancer on Ashkenazi Jewish women. Journal of Medical Genetics doi:10.1136/jmg-2023-109185 (2023).
30. Gao Z, Zhang Y, Cramer N, Przeworski M, Moorjani P (2022). Limited role of generation time changes in driving the evolution of the mutation spectrum in humans. Elife 12, e81188 (2023).
29. A. Gervits and R. Sharan. Predicting genetic interactions, cell line dependencies and drug sensitivities with variational graph auto-encoder. Frontiers in Bioinformatics, 2:1025783, 2022.
28. M. Chintalapati and P. Moorjani (2020) Evolution of the mutation rate across primates. Current Opinion in Genetics & Development, Volume 62, 2020, Pages 58-64, ISSN 0959-437X, https://doi.org/10.1016/j.gde.2020.05.028.
27. Vissat LL, Cain S, Toledo S, Spiegel O & Getz WM (2023) Categorizing the geometry of animal diel movement patterns with examples from high-resolution barn owl tracking. Movement Ecology, Movement Ecology. 2023. Mar; 11:15.
26. Cain S, Solomon T, Leshem Y, Toledo S, Arnon E, Roulin A & Spiegel O (2023) Movement predictability of individual barn owls facilitates home range size and survival estimation. Movement Ecology, 2023. Feb; 11:10.
25. E. Avnat, G. Shapira, D. Gurwitz, N. Shomron (2022) Elevated Expression of RGS2 May Underlie Reduced Olfaction in COVID-19 Patients. J. Pers. Med. 2022, 12, 1396. https://doi.org/10.3390/jpm12091396.
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 Activation. Front. 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 analysis. Bioinformatics, 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 data. bioRxiv, 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 therapy. Journal 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 viruses. Molecular 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.
