| Combining drug and gene similarity measures for drug-target elucidation L Perlman, A Gottlieb, N Atias, E Ruppin, R Sharan Journal of computational biology 18 (2), 133-145, 2011 | 229 | 2011 |
| An algorithmic framework for predicting side effects of drugs N Atias, R Sharan Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA, 2011 | 154 | 2011 |
| Alternative splicing regulates biogenesis of miRNAs located across exon-intron junctions Z Melamed, A Levy, R Ashwal-Fluss, G Lev-Maor, K Mekahel, N Atias, ... Molecular cell 50 (6), 869-881, 2013 | 117 | 2013 |
| Metabolic network prediction of drug side effects I Shaked, MA Oberhardt, N Atias, R Sharan, E Ruppin Cell systems 2 (3), 209-213, 2016 | 109 | 2016 |
| Interactome mapping provides a network of neurodegenerative disease proteins and uncovers widespread protein aggregation in affected brains C Haenig, N Atias, AK Taylor, A Mazza, MH Schaefer, J Russ, ... Cell reports 32 (7), 2020 | 84 | 2020 |
| ANAT: a tool for constructing and analyzing functional protein networks N Yosef, E Zalckvar, AD Rubinstein, M Homilius, N Atias, L Vardi, ... Science signaling 4 (196), pl1-pl1, 2011 | 64 | 2011 |
| A network-based analysis of colon cancer splicing changes reveals a tumorigenesis-favoring regulatory pathway emanating from ELK1 D Hollander, M Donyo, N Atias, K Mekahel, Z Melamed, S Yannai, ... Genome research 26 (4), 541-553, 2016 | 61 | 2016 |
| Comparative analysis of protein networks: hard problems, practical solutions N Atias, R Sharan Communications of the ACM 55 (5), 88-97, 2012 | 55 | 2012 |
| Regulation of Sec16 levels and dynamics links proliferation and secretion KD Tillmann, V Reiterer, F Baschieri, J Hoffmann, V Millarte, MA Hauser, ... Journal of cell science 128 (4), 670-682, 2015 | 46 | 2015 |
| Systematic identification and correction of annotation errors in the genetic interaction map of Saccharomyces cerevisiae N Atias, M Kupiec, R Sharan Nucleic acids research 44 (5), e50-e50, 2016 | 18 | 2016 |
| Experimental design schemes for learning Boolean network models N Atias, M Gershenzon, K Labazin, R Sharan Bioinformatics 30 (17), i445-i452, 2014 | 17 | 2014 |
| A Genetic Screen for High Copy Number Suppressors of the Synthetic Lethality Between elg1Δ and srs2Δ in Yeast I Gazy, B Liefshitz, A Bronstein, O Parnas, N Atias, R Sharan, M Kupiec G3: Genes, Genomes, Genetics 3 (5), 917-926, 2013 | 16 | 2013 |
| iPoint: an integer programming based algorithm for inferring protein subnetworks N Atias, R Sharan Molecular BioSystems 9 (7), 1662-1669, 2013 | 15 | 2013 |
| ANAT 2.0: reconstructing functional protein subnetworks Y Almozlino, N Atias, D Silverbush, R Sharan BMC bioinformatics 18, 1-5, 2017 | 14 | 2017 |
| Pathway-based analysis of genomic variation data N Atias, S Istrail, R Sharan Current opinion in genetics & development 23 (6), 622-626, 2013 | 13 | 2013 |
| An algorithmic framework for predicting side-effects of drugs N Atias, R Sharan Research in Computational Molecular Biology: 14th Annual International …, 2010 | 8 | 2010 |
| An Algorithmic Framework for Predicting Side Effects of Drugs R Sharan, N Atias Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA, 2011 | | 2011 |
| Comparative Analysis of Protein Networks: Hard Problems, Practical Solutions Examining tools that provide valuable insight about molecular components within a cell. N Atias, R Sharan | | |
Roded SharanTel Aviv UniversityEmail verificata su post.tau.ac.il
