Classification of node-positive melanomas into prognostic subgroups using keratin, immune and melanogenesis expression patterns
D. Netanely, S. Leibou, R. Parikh, N. Stern, H. Vaknine, R. Brenner, S. Amar, R. Haiat Factor, T. Perluk, J. Frand, E Nizri, D. Hershkovitz, V. Zemser-Werner, C. Levy, R. Shamir.
Oncogene https://doi.org/10.1038/s41388-021-01665-0 (2021).
Early detection of prostate gland and breast cancer risk based on routine check-up data using survival analysis trees for left-truncated and right-censored data
D. Coster, E. Fischer, S. Shenhar-Tsarfaty, T. Menes, S. Berliner, O. Rogowski, D. Zeltser, I. Shapira, E. Halperin, S. Rosset, M. Gorfine, R. Shamir.
MedRxiv, doi: https://doi.org/10.1101/2021.01.11.21249491.
Improving the efficiency of de Bruijn graph construction using compact universal hitting sets
Y. Ben-Ari, D. Flomin, L. Pu, Y. Orenstein, R. Shamir.
BioRxiv, https://www.biorxiv.org/content/10.1101/2020.11.08.373050v3 (2020). To appear in Proc. ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), August 1-4 2021.
MONET: Multi-omic patient module detection by omic selection
N. Rappoport, R. Safra, R. Shamir.
PLoS Computational Biology 16 (9) e1008182 (2020).
PlasClass improves plasmid sequence classification
D. Pellow, I. Mizrahi, R. Shamir.
PLoS Comput Biol, 16(4): e1007781. https://doi.org/10.1371/journal.pcbi.1007781, 2020.
Melanoma-secreted lysosomes trigger monocyte-derived dendritic cell apoptosis and limit cancer immunotherapy
N. S. Magal , L. Farhat-Younis , D. Rasoulouniriana , A. Glieberman , A. Gutwillig , L. Tal , D. Netanely, R. Shamir , R. Blau , H. Gutman ,P. Rider, Y. Carmi.
Cancer Research, doi: 10.1158/0008-5472.CAN-19-2944 (2020).
DOMINO: a novel network-based module detection algorithm with reduced rate of false calls
H. Levi, R. Elkon, R. Shamir.
Molecular Systems Biology 17:e9593 (2021).
SCAPP: An algorithm for improved plasmid assembly in metagenomes
D. Pellow, M. Probst, O. Furman, A. Zorea, Arik Segal, I. Mizrahi, R. Shamir.
BioRxiv doi: https://doi.org/10.1101/2020.01.12.903252 (January 2020).
Using the kinetics of C-reactive protein response to improve the differential diagnosis between acute bacterial and viral infections
D. Coster, A. Wasserman, E. Fisher, O. Rogowski, D. Zeltser, I. Shapira, D. Bernstein, Ahuva Meilik, E. Raykhshtat, P. Halpern, S. Berliner, S. Shenhar-Tsarfaty, R. Shamir.
Infection, https://doi.org/10.1007/s15010-019-01383-6.
PROMO: an interactive tool for analyzing clinically-labeled multi-omic cancer datasets
D. Netanely, N. Stern, I. Laufer, R. Shamir.
BMC Bioinformatics 20:732, https://doi.org/10.1186/s12859-019-3142-5 (2019).
Unravelling plasmidome distribution and interaction with its hosting microbiome
A. Kav Brown, R. Rozov, D. Bogmil, S. J. Sorensen, I. Benhar, E. Halperin, R. Shamir, I. Mizrahi.
Environmental Microbiology, https://doi.org/10.1111/1462-2920.14813 (2019).
Prodigy: personalized prioritization of driver genes
G. Dinstag, R. Shamir.
Bioinformatics btz815, https://doi.org/10.1093/bioinformatics/btz815 (2019)
Inaccuracy of the log‐rank approximation in cancer data analysis
N. Rappoport and R. Shamir.
Molecular Systems Biology (2019) 15:e8754https://doi.org/10.15252/msb.20188754.
Personalized prediction of adverse heart and kidney events using baseline and longitudinal data from SPRINT and ACCORD
G. Dinstag, D. Amar, E. Ingelsson, E. Ashley and R. Shamir.
PLOS ONE, https://doi.org/10.1371/journal.pone.0219728, 2019
CT-FOCS: a novel method for inferring cell type-specific enhancer-promoter maps
T. Hait, R. Elkon, R. Shamir.
BioRxiv, https://www.biorxiv.org/content/10.1101/707158v2
The EXPANDER integrated platform for transcriptome analysis
T. A. Hait, A.Maron-Katz., D. Sagir, D. Amar, I. Ulitsky, C. Linhart, A. Tanay, R. Sharan, Y. Shiloh, R. Elkon, R.Shamir.
Journal of Molecular Biology, https://doi.org/10.1016/j.jmb.2019.05.013 (2019).
NEMO: cancer subtyping by integration of partial multi-omic data
N. Rappoport and R. Shamir.
Bioinformatics, https://doi.org/10.1093/bioinformatics/btz058, 2018.
GePMI: A statistical model for personal intestinal microbiome identification
Z. Wang, H. Lou, R. Shamir, R. Jiang, T. Chen.
npj Biofilm and Microbiome} 4: 20, https://doi.org/10.1038/s41522-018-0065-2, 2018.
Genomic meta-analysis of the interplay between 3D chromatin organization and gene expression programs under basal and stress conditions
I. Nurick, R. Shamir and R. Elkon.
Epigenetics & Chromatin (2018) 11:49 https://doi.org/10.1186/s13072-018-0220-2
Multi-omic and multi-view clustering algorithms: review and cancer benchmark
N. Rappoport & R. Shamir
Nucleic Acids Research, 46 (20) pp. 10546–-10562, (2018).
Genome Rearrangement Problems with Single and Multiple Gene Copies: A Review
R. Zeira and R. Shamir.
Bioinformatics and Phylogenetics: Seminal contributions of Bernard Moret, T. Warnow, Editor, pp. 205--242, Springer Nature Switzerland AG 2019.
Computational analysis of mRNA expression profiling in the inner ear reveals candidate transcription factors associated with proliferation, differentiation, and deafness
K. Perl, R. Shamir and K. B. Avraham
Human Genomics, 12:30, https://doi.org/10.1186/s40246-018-0161-7, 2018.
Sorting cancer karyotypes using double-cut-and-joins, duplications and deletions
R. Zeira and R. Shamir.
Bioinformatics, bty381, https://doi.org/10.1093/bioinformatics/bty381
FOCS: a novel method for analyzing enhancer and gene activity patterns infers an extensive enhancer–promoter map
T. A. Hait, D. Amar, R. Shamir, R. Elkon.
Genome Biology, 19:56, https://doi.org/10.1186/s13059-018-1432-2, 2018.
MorphDB: Prioritizing Genes for Specialized Metabolism Pathways and Gene Ontology Categories in Plants
A. Zwaenepoel, T. Diels, D. Amar, T. Van Parys, R. Shamir, Y. Van de Peer and O. Tzfadia.
Front. Plant Sci., https://doi.org/10.3389/fpls.2018.0035, 2018.
ADEPTUS: A discovery tool for disease prediction, enrichment and network analysis based on profiles from many diseases
D. Amar, A. Vizel, C. Levy & R. Shamir.
Bioinformatics, bty027, https://doi.org/10.1093/bioinformatics/bty027, 2018.