World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
23982
World Ranking
1572
National Ranking
33

Biology and Biochemistry

D-Index
80
Citations
26913
World Ranking
4028
National Ranking
38

Overview

Roded Sharan is affiliated with Tel Aviv University in Israel and has contributed extensively to the field of Biochemistry, Genetics and Molecular Biology, with a particular focus on Molecular Biology. Their body of work includes 116 publications primarily in this domain.

Their research covers several subfields, including Molecular Biology, Cancer Research, Biophysics, Genetics, and Infectious Diseases. The main topics they investigate include Bioinformatics and Genomic Networks, Gene Expression and Cancer Classification, Cell Image Analysis Techniques, Cancer Genomics and Diagnostics, Single-cell and Spatial Transcriptomics, Computational Drug Discovery Methods, and Genomics and Phylogenetic Studies.

Among the notable recent papers by Roded Sharan are:

  • Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients, 2021, Nature Cancer
  • Interactome Mapping Provides a Network of Neurodegenerative Disease Proteins and Uncovers Widespread Protein Aggregation in Affected Brains, 2020, Cell Reports
  • SARS-CoV-2 variants evolve convergent strategies to remodel the host response, 2023, Cell
  • Effect of SARS-CoV-2 proteins on vascular permeability, 2021, eLife
  • Current and future directions in network biology, 2024, Bioinformatics Advances

Roded Sharan frequently collaborates with several researchers, including Mark D.M. Leiserson, Rami Nasser, Itay Sason, Einat Beery, and Meir Lahav.

The scientist has published consistently in a range of venues, with frequent publications in bioRxiv (Cold Spring Harbor Laboratory), Bioinformatics Advances, Bioinformatics, eLife, and Genome Medicine.

Best Publications

  • Network-based prediction of protein function

    Roded Sharan;Igor Ulitsky;Ron Shamir

  • Discovering statistically significant biclusters in gene expression data.

    Amos Tanay;Roded Sharan;Ron Shamir

  • Associating Genes and Protein Complexes with Disease via Network Propagation

    Oron Vanunu;Oded Magger;Eytan Ruppin;Tomer Shlomi

  • Protein networks in disease.

    Trey Ideker;Roded Sharan

  • Conserved patterns of protein interaction in multiple species

    Roded Sharan;Silpa Suthram;Ryan M. Kelley;Tanja Kuhn

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

    Assaf Gottlieb;Gideon Y Stein;Gideon Y Stein;Eytan Ruppin;Roded Sharan

  • Network propagation: a universal amplifier of genetic associations

    Lenore Cowen;Trey Ideker;Benjamin J. Raphael;Roded Sharan

  • Modeling cellular machinery through biological network comparison

    Roded Sharan;Trey Ideker

  • Conserved pathways within bacteria and yeast as revealed by global protein network alignment

    Brian P. Kelley;Roded Sharan;Richard M. Karp;Taylor Sittler

  • Center CLICK: A Clustering Algorithm with Applications to Gene Expression Analysis

    Roded Sharan;Ron Shamir

  • Competitive and cooperative metabolic interactions in bacterial communities.

    Shiri Freilich;Raphy Zarecki;Omer Eilam;Ella Shtifman Segal

  • An initial blueprint for myogenic differentiation

    Alexandre Blais;Mary Tsikitis;Diego Acosta-Alvear;Roded Sharan

  • PathBLAST: a tool for alignment of protein interaction networks.

    Brian P. Kelley;Bingbing Yuan;Fran Lewitter;Roded Sharan

  • Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data

    Amos Tanay;Roded Sharan;Martin Kupiec;Ron Shamir

  • Cluster graph modification problems

    Ron Shamir;Roded Sharan;Dekel Tsur

  • CLICK and EXPANDER: a system for clustering and visualizing gene expression data.

    Roded Sharan;Adi Maron-Katz;Ron Shamir

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

    Jianzhu Ma;Michael Ku Yu;Samson Fong;Keiichiro Ono

  • EXPANDER – an integrative program suite for microarray data analysis

    Ron Shamir;Adi Maron-Katz;Amos Tanay;Chaim Linhart

  • Genome-Wide In Silico Identification of Transcriptional Regulators Controlling the Cell Cycle in Human Cells

    Ran Elkon;Chaim Linhart;Roded Sharan;Ron Shamir

  • Biclustering Algorithms: A Survey

    Amos Tanay;Roded Sharan;Ron Shamir

  • Revealing modularity and organization in the yeast molecular network by integrated analysis of highl

    Amos Tanay;Roded Sharan;Martin Kupiec;Ron Shamir

Frequent Co-Authors

Eytan Ruppin
Eytan Ruppin National Institutes of Health
Ron Shamir
Ron Shamir Tel Aviv University
Martin Kupiec
Martin Kupiec Tel Aviv University
Trey Ideker
Trey Ideker University of California, San Diego
Nir Yosef
Nir Yosef University of California, Berkeley
Richard M. Karp
Richard M. Karp University of California, Berkeley
Teresa M. Przytycka
Teresa M. Przytycka National Institutes of Health
Zohar Yakhini
Zohar Yakhini Technion – Israel Institute of Technology
Amos Tanay
Amos Tanay Weizmann Institute of Science
Vineet Bafna
Vineet Bafna University of California, San Diego

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