Sharan, Roded

Protein networks in disease

Ideker, T., & Sharan, R. (2008) · Genome Research

Bioinformatics and Genomic NetworksBiomedical Text Mining and Ontologies

Cited by 817

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

Ma, J., Yu, M. K., Fong, S., Ono, K., Sage, E., Demchak, B., Sharan, R., & Ideker, T. (2018) · Nature Methods

Gene Regulatory Network AnalysisMicrobial Metabolic Engineering and Bioproduction

Cited by 435

A genome‐scale computational study of the interplay between transcriptional regulation and metabolism

Shlomi, T., Eisenberg, Y., Sharan, R., & Ruppin, E. (2007) · Molecular Systems Biology

Microbial Metabolic Engineering and BioproductionGene Regulatory Network Analysis

Cited by 254

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

Shlomi, T., Benyamini, T., Gottlieb, E., Sharan, R., & Ruppin, E. (2011) · PLoS Computational Biology

Cancer, Hypoxia, and MetabolismMicrobial Metabolic Engineering and Bioproduction

Cited by 244

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

Ma, J., Fong, S. H., Luo, Y., Bakkenist, C. J., Shen, J. P., Mourragui, S., Wessels, L. F. A., Hafner, M., Sharan, R., Peng, J., et al. (2021) · Nature Cancer

Computational Drug Discovery MethodsDomain Adaptation and Few-Shot Learning

Cited by 180

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

Segal, E. S., Gritsenko, V., Levitan, A., Yadav, B., Dror, N., Steenwyk, J. L., Silberberg, Y., Mielich, K., Rokas, A., Gow, N. A. R., et al. (2018) · mBio

Fungal and yeast genetics researchAntifungal resistance and susceptibility

Cited by 150

Environmental stresses disrupt telomere length homeostasis

Romano, G. H., Harari, Y., Yehuda, T., Podhorzer, A., Rubinstein, L., Shamir, R., Gottlieb, A., Silberberg, Y., Pe'er, D., Ruppin, E., et al. (2013) · PLoS Genetics

Telomeres, Telomerase, and SenescenceGenetics, Aging, and Longevity in Model Organisms

Cited by 107

Transcriptional regulation of protein complexes within and across species

Tan, K., Shlomi, T., Feizi, H., Ideker, T., & Sharan, R. (2007) · Proceedings of the National Academy of Sciences

Bioinformatics and Genomic NetworksGene Regulatory Network Analysis

Cited by 58

Identification of Essential Genes and Fluconazole Susceptibility Genes in Candida glabrata by Profiling Hermes Transposon Insertions

Gale, A. N., Sakhawala, R. M., Levitan, A., Sharan, R., Berman, J., Timp, W., & Cunningham, K. W. (2020) · G3 Genes|Genomes|Genetics

Antifungal resistance and susceptibilityFungal and yeast genetics research

Cited by 56

The first enhancer in an enhancer chain safeguards subsequent enhancer-promoter contacts from a distance

Song, W., Sharan, R., & Ovcharenko, I. (2019) · Genome Biology

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 28

Network-Free Inference of Knockout Effects in Yeast

Peleg, T., Yosef, N., Ruppin, E., & Sharan, R. (2010) · PLoS Computational Biology

Bioinformatics and Genomic NetworksGene Regulatory Network Analysis

Cited by 14

An adversarial scheme for integrating multi-modal data on protein function

Nasser, R., Schaffer, L. V., Ideker, T., & Sharan, R. (2025) · Cell Systems

Bioinformatics and Genomic NetworksMachine Learning in Bioinformatics

Cited by 2