NEMO: Cancer subtyping by integration of partial multi-omic data
N. Rappoport and R. Shamir.
bioRxiv, doi: http://dx.doi.org/10.1101/415224, 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
biorxiv, doi: https://doi.org/10.1101/371120.
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.