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Roded Sharan

Active 1996–2025

195
Papers
20,806
Citations
70
h-index
141
i10-index

Citations

Citations per year for Roded Sharan1970: 1 citations1973: 1 citations1980: 1 citations1987: 1 citations1991: 2 citations1993: 4 citations1994: 4 citations1998: 1 citations1999: 2 citations2000: 6 citations2001: 11 citations2002: 25 citations2003: 40 citations2004: 127 citations2005: 216 citations2006: 306 citations2007: 363 citations2008: 414 citations2009: 483 citations2010: 531 citations2011: 570 citations2012: 512 citations2013: 509 citations2014: 504 citations2015: 534 citations2016: 462 citations2017: 433 citations2018: 464 citations2019: 690 citations2020: 673 citations2021: 615 citations2022: 583 citations2023: 413 citations2024: 533 citations2025: 335 citations2026: 58 citations1971–1972: no citations, so these years are not shown1974–1979: no citations, so these years are not shown1981–1986: no citations, so these years are not shown1988–1990: no citations, so these years are not shown1992: no citations, so this year is not shown1995–1997: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 3,174 citing papers, 27.2% of this breakdownChina: 1,673 citing papers, 14.3% of this breakdownUnited Kingdom: 618 citing papers, 5.3% of this breakdownGermany: 607 citing papers, 5.2% of this breakdownCanada: 437 citing papers, 3.7% of this breakdownItaly: 425 citing papers, 3.6% of this breakdownIsrael: 421 citing papers, 3.6% of this breakdownFrance: 381 citing papers, 3.3% of this breakdownIndia: 349 citing papers, 3% of this breakdownSpain: 270 citing papers, 2.3% of this breakdownNetherlands: 207 citing papers, 1.8% of this breakdownAustralia: 198 citing papers, 1.7% of this breakdown
0%27.2%Other 25%

Institutions

Fields

  • Biochemistry, Genetics and Molecular Biology61.5%
  • Computer Science23.6%
  • Medicine6%
  • Physics and Astronomy1.8%
  • Agricultural and Biological Sciences1.4%
  • Environmental Science1.2%
  • Other4.5%

Topics

  • Bioinformatics and Genomic Networks15.5%
  • Computational Drug Discovery Methods7.2%
  • Gene expression and cancer classification6.5%
  • Gene Regulatory Network Analysis3.8%
  • Microbial Metabolic Engineering and Bioproduction3.6%
  • Machine Learning in Bioinformatics3%
  • Other60.4%

Coauthors

All papers

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  1. PREDICT: a method for inferring novel drug indications with application to personalized medicine

    Authors: Assaf Gottlieb, Gideon Y. Stein, Eytan Ruppin, Roded Sharan - Molecular Systems Biology 2011 cited by 886

  2. Network propagation: a universal amplifier of genetic associations

    Authors: Lenore Cowen, Trey Ideker, Benjamin J. Raphael, Roded Sharan - Nature Reviews Genetics 2017 cited by 729

  3. Using deep learning to model the hierarchical structure and function of a cell

    Authors: Jianzhu Ma, Michael Yu, Samson Fong, Keiichiro Ono, Eric Sage, Barry Demchak, Roded Sharan, Trey Ideker - Nature Methods 2018 cited by 449

  4. Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients

    Authors: Jianzhu Ma, Samson Fong, Yunan Luo, Christopher J. Bakkenist, John Paul Shen, Soufiane Mourragui, Lodewyk F.A. Wessels, Marc Hafner, Roded Sharan, Jian Peng, Trey Ideker - Nature Cancer 2021 cited by 185

  5. SARS-CoV-2 variants evolve convergent strategies to remodel the host response

    Authors: Mehdi Bouhaddou, Ann‐Kathrin Reuschl, Benjamin J. Polacco, Lucy Thorne, Manisha R. Ummadi, Chengjin Ye, Romel Rosales, Adrian Pelin, Jyoti Batra, Gwendolyn Μ. Jang, Jiewei Xu, Jack M. Moen, Alicia Richards, Yuan Zhou, Bhavya Harjai, Erica Stevenson, Ajda Rojc, Roberta Ragazzini, Matthew V. X. Whelan, Wilhelm Furnon, Giuditta De Lorenzo, Vanessa M. Cowton, Abdullah M. Syed, Alison Ciling, Noa Deutsch, Daniel Pirak, Giulia Dowgier, Dejan Mesner, Jane Turner, Briana L McGovern, Myosotys Rodriguez, Rocio Leiva-Rebollo, Alistair S. Dunham, Xiaofang Zhong, Manon Eckhardt, Andrea Fossati, Nicholas Liotta, Thomas Kehrer, Anastasija Čupić, Magdalena Rutkowska, Ignacio Mena, Sadaf Aslam, Alyssa Hoffert, Helene Foussard, Charles Ochieng’ Olwal, Weiqing Huang, Thomas P. Zwaka, John Pham, Molly Lyons, Laura K. Donohue, Aliesha Griffin, Rebecca Nugent, Kevin Holden, Robert Deans, Pablo Avilés, José A. López-Martín, José Jimeno, Kirsten Obernier, Jacqueline M. Fabius, Margaret Soucheray, Ruth Hüttenhain, Irwin Jungreis, Manolis Kellis, Ignacia Echeverria, Kliment A. Verba, Paola Bonfanti, Pedro Beltrão, Roded Sharan, Jennifer A. Doudna, Luis Martínez‐Sobrido, Arvind H. Patel, Massimo Palmarini, Lisa Miorin, Kris M. White, Danielle L. Swaney, Adolfo García‐Sastre, Clare Jolly, Lorena Zuliani‐Alvarez, Greg J. Towers, Nevan J. Krogan - Cell 2023 cited by 114

  6. Competitive and cooperative metabolic interactions in bacterial communities

    Authors: Shiri Freilich, Raphy Zarecki, Omer Eilam, E. Segal, Christopher S. Henry, Martin Kupiec, Uri Gophna, Roded Sharan, Eytan Ruppin - Nature Communications 2011 cited by 587

  7. Associating Genes and Protein Complexes with Disease via Network Propagation

    Authors: Oron Vanunu, Oded Magger, Eytan Ruppin, Tomer Shlomi, Roded Sharan - PLoS Computational Biology, PLoS Comput. Biol. 2010 cited by 922

  8. INDI: a computational framework for inferring drug interactions and their associated recommendations

    Authors: Assaf Gottlieb, Gideon Y. Stein, Yoram Oron, Eytan Ruppin, Roded Sharan - Molecular Systems Biology 2012 cited by 282

  9. Current and future directions in network biology

    Authors: Marinka Žitnik, Michelle M. Li, Aydin Wells, Kimberly Glass, Deisy Morselli Gysi, Arjun Krishnan, T. M. Murali, Predrag Radivojac, Sushmita Roy, Anaı̈s Baudot, Serdar Bozdag, Danny Z. Chen, Lenore Cowen, Kapil Devkota, Anthony Gitter, Sara J.C. Gosline, Pengfei Gu, Pietro Hiram Guzzi, Heng Huang, Meng Jiang, Ziynet Nesibe Kesimoglu, Mehmet Koyutürk, Jian Ma, Alexander R. Pico, Nataša Pržulj, Teresa M. Przytycka, Benjamin J. Raphael, Anna Ritz, Roded Sharan, Yang Shen, Mona Singh, Donna K. Slonim, Hanghang Tong, Xinan Yang, Byung-Jun Yoon, Haiyuan Yu, Tijana Milenković - Bioinformatics Advances 2024 cited by 95

  10. Network‐based prediction of protein function

    Authors: Roded Sharan, Igor Ulitsky, Ron Shamir - Molecular Systems Biology 2007 cited by 1,098

  11. To Embed or Not: Network Embedding as a Paradigm in Computational Biology

    Authors: Walter Nelson, Marinka Žitnik, Bo Wang, Jure Leskovec, Anna Goldenberg, Roded Sharan - Frontiers in Genetics 2019 cited by 186

  12. Combining Drug and Gene Similarity Measures for Drug-Target Elucidation

    Authors: Liat Perlman, Assaf Gottlieb, Nir Atias, Eytan Ruppin, Roded Sharan - Journal of Computational Biology, J. Comput. Biol. 2011 cited by 224

  13. Gene architecture directs splicing outcome in separate nuclear spatial regions

    Authors: Luna Tammer, Ofir Hameiri, Ifat Keydar, Vanessa Rachel Roy, Asaf Ashkenazy-Titelman, Noélia Custódio, Itay Sason, Ronna Shayevitch, Victoria Rodríguez-Vaello, José Rino, Galit Lev Maor, Yodfat Leader, Doha Khair, Erez Lieberman Aiden, Ran Elkon, Manuel Irimia, Roded Sharan, Yaron Shav‐Tal, Maria Carmo‐Fonseca, Gil Ast - Molecular Cell 2022 cited by 77

  14. Discovering statistically significant biclusters in gene expression data

    Authors: Amos Tanay, Roded Sharan, Ron Shamir - Bioinformatics, ISMB 2002 cited by 861

  15. Gene Essentiality Analyzed by In Vivo Transposon Mutagenesis and Machine Learning in a Stable Haploid Isolate of Candida albicans

    Authors: E. Segal, Vladimir Gritsenko, Anton Levitan, Bhawna Yadav, Naama Dror, Jacob L. Steenwyk, Yael Silberberg, Kevin Mielich, Antonis Rokas, Neil A. R. Gow, Reinhard Kunze, Roded Sharan, Judith Berman - mBio 2018 cited by 159

  16. Genome-Scale Metabolic Modeling Elucidates the Role of Proliferative Adaptation in Causing the Warburg Effect

    Authors: Tomer Shlomi, Tomer Benyamini, Eyal Gottlieb, Roded Sharan, Eytan Ruppin - PLoS Computational Biology, PLoS Comput. Biol. 2011 cited by 248

  17. The large-scale organization of the bacterial network of ecological co-occurrence interactions

    Authors: Shiri Freilich, Anat Kreimer, Isacc Meilijson, Uri Gophna, Roded Sharan, Eytan Ruppin - Nucleic Acids Research 2010 cited by 326

  18. A Method for Predicting Protein-Protein Interaction Types

    Authors: Yael Silberberg, Martin Kupiec, Roded Sharan - PLoS ONE 2014 cited by 31

  19. Modeling cellular machinery through biological network comparison

    Authors: Roded Sharan, Trey Ideker - Nature Biotechnology 2006 cited by 564

  20. Exosomal telomerase transcripts reprogram the microRNA transcriptome profile of fibroblasts and partially contribute to CAF formation

    Authors: Daniela Likonen, Maria Pinchasi, Einat Beery, Zinab Sarsor, Lorenzo Signorini, Asia Gervits, Roded Sharan, Meir Lahav, Pia Raanani, Orit Uziel - Scientific Reports 2022 cited by 18

  21. Protein networks in disease

    Authors: Trey Ideker, Roded Sharan - Genome Research 2008 cited by 836

  22. Interactome Mapping Provides a Network of Neurodegenerative Disease Proteins and Uncovers Widespread Protein Aggregation in Affected Brains

    Authors: Christian Haenig, Nir Atias, Alexander K. Taylor, Arnon Mazza, Martin H. Schaefer, Jenny Russ, Sean‐Patrick Riechers, Shushant Jain, Maura Coughlin, Jean−Fred Fontaine, Brian D. Freibaum, Lydia Brusendorf, Martina Zenkner, Pablo Porras, Martin Stroedicke, Sigrid Schnoegl, Kristin Arnsburg, Annett Boeddrich, Lucia Pigazzini, Peter Heutink, J. Paul Taylor, Janine Kirstein, Miguel A. Andrade‐Navarro, Roded Sharan, Erich E. Wanker - Cell Reports 2020 cited by 119

  23. Metabolic Network Prediction of Drug Side Effects

    Authors: Itay Shaked, Matthew Oberhardt, Nir Atias, Roded Sharan, Eytan Ruppin - Cell Systems 2016 cited by 91

  24. A systematic approach to orient the human protein–protein interaction network

    Authors: Dana Silverbush, Roded Sharan - Nature Communications 2019 cited by 75