Eytan Ruppin - Publications

Affiliations: 
Computer Science University of Maryland, College Park, College Park, MD 
Area:
Bioinformatics and Computational Biology

133 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Shaked MS, Dassa B, Sinha S, Di Agostino S, Azuri I, Mukherjee S, Aylon Y, Blandino G, Ruppin E, Oren M. A division of labor between YAP and TAZ in non-small cell lung cancer. Cancer Research. PMID 32816858 DOI: 10.1158/0008-5472.Can-20-0125  0.313
2020 Dattilo R, Mottini C, Camera E, Lamolinara A, Auslander N, Doglioni G, Muscolini M, Tang W, Planque M, Ercolani C, Buglioni S, Manni I, Trisciuoglio D, Boe A, Grande S, ... ... Ruppin E, et al. Pyrvinium pamoate induces death of triple-negative breast cancer stem-like cells and reduces metastases through effects on lipid anabolism. Cancer Research. PMID 32718996 DOI: 10.1158/0008-5472.Can-19-1184  0.322
2020 Erez A, Ruppin E, Keshet R, Lee JS. Abstract IA21: Blocking purine synthesis in cancer promotes response to immunotherapy Cancer Research. 80. DOI: 10.1158/1538-7445.Pedca19-Ia21  0.316
2020 Schischlik F, Lee JS, Shah N, Kaplan RN, Thiele CJ, Widemann B, Ruppin E. Abstract A46: Charting the synthetic lethality landscape in pediatric cancer to advance whole-exome precision-based treatments Cancer Research. 80. DOI: 10.1158/1538-7445.Pedca19-A46  0.382
2019 Katzir R, Polat IH, Harel M, Katz S, Foguet C, Selivanov VA, Sabatier P, Cascante M, Geiger T, Ruppin E. The landscape of tiered regulation of breast cancer cell metabolism. Scientific Reports. 9: 17760. PMID 31780802 DOI: 10.1038/S41598-019-54221-Y  0.357
2019 Pathria G, Lee JS, Hasnis E, Tandoc K, Scott DA, Verma S, Feng Y, Larue L, Sahu AD, Topisirovic I, Ruppin E, Ronai ZA. Translational reprogramming marks adaptation to asparagine restriction in cancer. Nature Cell Biology. PMID 31740775 DOI: 10.1038/S41556-019-0415-1  0.312
2019 Kwon SM, Budhu A, Woo HG, Chaisaingmongkol J, Dang H, Forgues M, Harris CC, Zhang G, Auslander N, Ruppin E, Mahidol C, Ruchirawat M, Wang XW. Functional Genomic Complexity Defines Intratumor Heterogeneity and Tumor Aggressiveness in Liver Cancer. Scientific Reports. 9: 16930. PMID 31729408 DOI: 10.1038/S41598-019-52578-8  0.302
2019 Nair NU, Das A, Rogkoti VM, Fokkelman M, Marcotte R, de Jong CG, Koedoot E, Lee JS, Meilijson I, Hannenhalli S, Neel BG, de Water BV, Le Dévédec SE, Ruppin E. Migration rather than proliferation transcriptomic signatures are strongly associated with breast cancer patient survival. Scientific Reports. 9: 10989. PMID 31358840 DOI: 10.1038/S41598-019-47440-W  0.307
2019 Magen A, Das Sahu A, Lee JS, Sharmin M, Lugo A, Gutkind JS, Schäffer AA, Ruppin E, Hannenhalli S. Beyond Synthetic Lethality: Charting the Landscape of Pairwise Gene Expression States Associated with Survival in Cancer. Cell Reports. 28: 938-948.e6. PMID 31340155 DOI: 10.1016/J.Celrep.2019.06.067  0.374
2019 Sahu AD, S Lee J, Wang Z, Zhang G, Iglesias-Bartolome R, Tian T, Wei Z, Miao B, Nair NU, Ponomarova O, Friedman AA, Amzallag A, Moll T, Kasumova G, Greninger P, ... ... Ruppin E, et al. Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy. Molecular Systems Biology. 15: e8323. PMID 30858180 DOI: 10.15252/Msb.20188323  0.34
2019 Feng X, Arang N, Rigiracciolo DC, Lee JS, Yeerna H, Wang Z, Lubrano S, Kishore A, Pachter JA, König GM, Maggiolini M, Kostenis E, Schlaepfer DD, Tamayo P, Chen Q, ... Ruppin E, et al. A Platform of Synthetic Lethal Gene Interaction Networks Reveals that the GNAQ Uveal Melanoma Oncogene Controls the Hippo Pathway through FAK. Cancer Cell. PMID 30773340 DOI: 10.1016/J.Ccell.2019.01.009  0.314
2019 Das A, Lee JS, Zhang G, Wang Z, Amzallag A, Boland G, Hannenhalli S, Herlyn M, Benes C, Gutkind JS, Flaherty K, Ruppin E. Abstract LB-149: Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy Cancer Research. 79. DOI: 10.1158/1538-7445.Am2019-Lb-149  0.352
2018 Silberman A, Goldman O, Boukobza Assayag O, Jacob A, Limanovich S, Adler L, Lee JS, Keshet R, Sarver A, Frug J, Stettner N, Galai S, Persi E, Bahar Halpern K, Zaltsman-Amir Y, ... ... Ruppin E, et al. Acid-induced downregulation of ASS1 contributes to the maintenance of intracellular pH in cancer. Cancer Research. PMID 30573518 DOI: 10.1158/0008-5472.Can-18-1062  0.312
2018 Tang W, Zhou M, Dorsey TH, Prieto DA, Wang XW, Ruppin E, Veenstra TD, Ambs S. Integrated proteotranscriptomics of breast cancer reveals globally increased protein-mRNA concordance associated with subtypes and survival. Genome Medicine. 10: 94. PMID 30501643 DOI: 10.1186/S13073-018-0602-X  0.318
2018 Pathria G, Scott DA, Feng Y, Sang Lee J, Fujita Y, Zhang G, Sahu AD, Ruppin E, Herlyn M, Osterman AL, Ronai ZA. Targeting the Warburg effect via LDHA inhibition engages ATF4 signaling for cancer cell survival. The Embo Journal. PMID 30209241 DOI: 10.15252/Embj.201899735  0.341
2018 Lee JS, Adler L, Karathia H, Carmel N, Rabinovich S, Auslander N, Keshet R, Stettner N, Silberman A, Agemy L, Helbling D, Eilam R, Sun Q, Brandis A, Malitsky S, ... ... Ruppin E, et al. Urea Cycle Dysregulation Generates Clinically Relevant Genomic and Biochemical Signatures. Cell. PMID 30100185 DOI: 10.1016/J.Cell.2018.07.019  0.305
2018 Lee JS, Das A, Jerby-Arnon L, Arafeh R, Auslander N, Davidson M, McGarry L, James D, Amzallag A, Park SG, Cheng K, Robinson W, Atias D, Stossel C, Buzhor E, ... ... Ruppin E, et al. Harnessing synthetic lethality to predict the response to cancer treatment. Nature Communications. 9: 2546. PMID 29959327 DOI: 10.1038/S41467-018-04647-1  0.327
2018 Tiram G, Ferber S, Ofek P, Eldar-Boock A, Ben-Shushan D, Yeini E, Krivitsky A, Blatt R, Almog N, Henkin J, Amsalem O, Yavin E, Cohen G, Lazarovici P, Lee JS, ... Ruppin E, et al. Reverting the molecular fingerprint of tumor dormancy as a therapeutic strategy for glioblastoma. Faseb Journal : Official Publication of the Federation of American Societies For Experimental Biology. fj201701568R. PMID 29856660 DOI: 10.1096/Fj.201701568R  0.305
2018 Nair NU, Das A, Amit U, Robinson W, Park SG, Basu M, Lugo A, Leor J, Ruppin E, Hannenhalli S. Putative functional genes in idiopathic dilated cardiomyopathy. Scientific Reports. 8: 66. PMID 29311597 DOI: 10.1038/S41598-017-18524-2  0.325
2018 Lee JS, Carmel N, Karathia H, Auslander N, Rabinovich S, Keshet R, Stettner N, Silberman A, Agemy L, Helbling D, Eilam R, Sun Q, Brandis A, Weiss H, Dimmock D, ... ... Ruppin E, et al. Abstract A69: Mutagenicity of urea cycle dysregulation and its implications for cancer immunotherapy Cancer Immunology Research. 6. DOI: 10.1158/2326-6074.Tumimm17-A69  0.348
2018 Feng X, Rigiracciolo D, Lee J, Yeerna H, Arang N, Lubrano S, Schlaepfer DD, Tamayo P, Ruppin E, Gutkind JS. Abstract 968: Targeting FAK inhibits YAP-dependent tumor growth in uveal melanoma Cancer Research. 78: 968-968. DOI: 10.1158/1538-7445.Am2018-968  0.319
2018 Lee JS, Das A, Jerby-Arnon L, Arafeh R, Davidson M, Amzallag A, Park SG, Cheng K, Robinson W, Atias D, Stossel C, Buzhor E, Stein G, Waterfall JJ, Meltzer PS, ... ... Ruppin E, et al. Abstract A188: Harnessing synthetic lethality to predict the response to cancer treatments Molecular Cancer Therapeutics. 17. DOI: 10.1158/1535-7163.Targ-17-A188  0.375
2018 Nair NU, Das A, Lee JS, Hannenhalli S, Dévédec SL, Water Bvd, Ruppin E. Abstract A023: Cell migration is a stronger predictor of patient survival in breast cancer than cell proliferation Molecular Cancer Therapeutics. 17. DOI: 10.1158/1535-7163.Targ-17-A023  0.334
2017 Auslander N, Cunningham CE, Toosi BM, McEwen EJ, Yizhak K, Vizeacoumar FS, Parameswaran S, Gonen N, Freywald T, Bhanumathy KK, Freywald A, Vizeacoumar FJ, Ruppin E. An integrated computational and experimental study uncovers FUT9 as a metabolic driver of colorectal cancer. Molecular Systems Biology. 13: 956-956. PMID 29196508 DOI: 10.15252/Msb.20177739  0.375
2017 Senft D, Leiserson MDM, Ruppin E, Ronai ZA. Precision Oncology: The Road Ahead. Trends in Molecular Medicine. PMID 28887051 DOI: 10.1016/J.Molmed.2017.08.003  0.313
2017 Duran-Frigola M, Siragusa L, Ruppin E, Barril X, Cruciani G, Aloy P. Detecting similar binding pockets to enable systems polypharmacology. Plos Computational Biology. 13: e1005522. PMID 28662117 DOI: 10.1371/Journal.Pcbi.1005522  0.303
2017 Lee JS, Das A, Jerby-Arnon L, Atias D, Amzallag A, Benes CH, Golan T, Ruppin E. Abstract PR09: Harnessing synthetic lethality to predict clinical outcomes of cancer treatment Molecular Cancer Therapeutics. 16. DOI: 10.1158/1538-8514.Synthleth-Pr09  0.376
2017 Magen A, Das A, Lee J, Hannenhalli S, Ruppin E. Abstract 1558: Data-driven approach to detecting novel gene interactions in cancer with applications to drug response prediction and cancer stratification Cancer Research. 77: 1558-1558. DOI: 10.1158/1538-7445.Am2017-1558  0.332
2016 Cohen O, Oberhardt M, Yizhak K, Ruppin E. Essential Genes Embody Increased Mutational Robustness to Compensate for the Lack of Backup Genetic Redundancy. Plos One. 11: e0168444. PMID 27997585 DOI: 10.1371/Journal.Pone.0168444  0.329
2016 Auslander N, Wagner A, Oberhardt M, Ruppin E. Data-Driven Metabolic Pathway Compositions Enhance Cancer Survival Prediction. Plos Computational Biology. 12: e1005125. PMID 27673682 DOI: 10.1371/Journal.Pcbi.1005125  0.371
2016 Cunningham CE, Li S, Vizeacoumar FS, Bhanumathy KK, Lee JS, Parameswaran S, Furber L, Abuhussein O, Paul JM, McDonald M, Templeton SD, Shukla H, El Zawily AM, Boyd F, Alli N, ... ... Ruppin E, et al. Therapeutic relevance of the protein phosphatase 2A in cancer. Oncotarget. PMID 27557495 DOI: 10.18632/Oncotarget.11399  0.34
2016 Mokryn O, Wagner A, Blattner M, Ruppin E, Shavitt Y. The Role of Temporal Trends in Growing Networks. Plos One. 11: e0156505. PMID 27486847 DOI: 10.1371/Journal.Pone.0156505  0.31
2016 Auslander N, Yizhak K, Weinstock A, Budhu A, Tang W, Wang XW, Ambs S, Ruppin E. A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer. Scientific Reports. 6: 29662. PMID 27406679 DOI: 10.1038/Srep29662  0.331
2016 Shaked I, Oberhardt MA, Atias N, Sharan R, Ruppin E. Metabolic Network Prediction of Drug Side Effects. Cell Systems. 2: 209-13. PMID 27135366 DOI: 10.1016/J.Cels.2016.03.001  0.325
2016 Oberhardt MA, Zarecki R, Reshef L, Xia F, Duran-Frigola M, Schreiber R, Henry CS, Ben-Tal N, Dwyer DJ, Gophna U, Ruppin E. Systems-Wide Prediction of Enzyme Promiscuity Reveals a New Underground Alternative Route for Pyridoxal 5'-Phosphate Production in E. coli. Plos Computational Biology. 12: e1004705. PMID 26821166 DOI: 10.1371/Journal.Pcbi.1004705  0.36
2016 Mazza A, Wagner A, Ruppin E, Sharan R. Functional Alignment of Metabolic Networks. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. PMID 26759932 DOI: 10.1089/Cmb.2015.0203  0.359
2016 Rabinovich S, Yizhak K, Sun Q, Brandis A, Helbling D, Dimmock D, Nagamani S, Ruppin E, Erez A. Abstract PR05: Aspartate metabolism links the urea cycle with nucleic acid synthesis in cancerous proliferation Molecular Cancer Research. 14. DOI: 10.1158/1557-3125.Metca15-Pr05  0.327
2015 Jerby-Arnon L, Ruppin E. Moving ahead on harnessing synthetic lethality to fight cancer. Molecular and Cellular Oncology. 2. PMID 27308440 DOI: 10.4161/23723556.2014.977150  0.372
2015 Rabinovich S, Adler L, Yizhak K, Sarver A, Silberman A, Agron S, Stettner N, Sun Q, Brandis A, Helbling D, Korman S, Itzkovitz S, Dimmock D, Ulitsky I, Nagamani SC, ... Ruppin E, et al. Diversion of aspartate in ASS1-deficient tumours fosters de novo pyrimidine synthesis. Nature. PMID 26560030 DOI: 10.1038/Nature15529  0.32
2015 Megchelenbrink W, Katzir R, Lu X, Ruppin E, Notebaart RA. Synthetic dosage lethality in the human metabolic network is highly predictive of tumor growth and cancer patient survival. Proceedings of the National Academy of Sciences of the United States of America. 112: 12217-22. PMID 26371301 DOI: 10.1073/Pnas.1508573112  0.408
2015 Wagner A, Cohen N, Kelder T, Amit U, Liebman E, Steinberg DM, Radonjic M, Ruppin E. Drugs that reverse disease transcriptomic signatures are more effective in a mouse model of dyslipidemia. Molecular Systems Biology. 11: 791. PMID 26148350 DOI: 10.15252/Msb.20145486  0.319
2015 Yizhak K, Chaneton B, Gottlieb E, Ruppin E. Modeling cancer metabolism on a genome scale. Molecular Systems Biology. 11: 817. PMID 26130389 DOI: 10.15252/Msb.20145307  0.391
2015 Ish-Am O, Kristensen DM, Ruppin E. Evolutionary Conservation of Bacterial Essential Metabolic Genes across All Bacterial Culture Media. Plos One. 10: e0123785. PMID 25894004 DOI: 10.1371/Journal.Pone.0123785  0.337
2015 Seaver SM, Bradbury LM, Frelin O, Zarecki R, Ruppin E, Hanson AD, Henry CS. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm. Frontiers in Plant Science. 6: 142. PMID 25806041 DOI: 10.3389/Fpls.2015.00142  0.35
2015 Patella F, Schug ZT, Persi E, Neilson LJ, Erami Z, Avanzato D, Maione F, Hernandez-Fernaud JR, Mackay G, Zheng L, Reid S, Frezza C, Giraudo E, Fiorio Pla A, Anderson K, ... Ruppin E, et al. Proteomics-based metabolic modeling reveals that fatty acid oxidation (FAO) controls endothelial cell (EC) permeability. Molecular & Cellular Proteomics : McP. 14: 621-34. PMID 25573745 DOI: 10.1074/Mcp.M114.045575  0.301
2015 Uziel O, Yosef N, Sharan R, Ruppin E, Kupiec M, Kushnir M, Beery E, Cohen-Diker T, Nordenberg J, Lahav M. The effects of telomere shortening on cancer cells: a network model of proteomic and microRNA analysis. Genomics. 105: 5-16. PMID 25451739 DOI: 10.1016/J.Ygeno.2014.10.013  0.327
2015 Patella F, Schug ZT, Persi E, Neilson LJ, Erami Z, Avanzato D, Maione F, Hernandez-Fernaud JR, Mackay G, Zheng L, Reid S, Frezza C, Giraudo E, Pla AF, Anderson K, ... Ruppin E, et al. Abstract B17: In-depth proteomics unveils fatty acid oxidation role in controlling vascular permeability Molecular Cancer Therapeutics. 14. DOI: 10.1158/1538-8514.Tumang15-B17  0.334
2015 Sahu AD, Lee JS, Hannenhalli S, Ruppin E. Abstract B56: Tracing synthetic rescue reprogramming to counteract cancer resistance Molecular Cancer Therapeutics. 14. DOI: 10.1158/1535-7163.Targ-15-B56  0.383
2014 Yizhak K, Gaude E, Le Dévédec S, Waldman YY, Stein GY, van de Water B, Frezza C, Ruppin E. Phenotype-based cell-specific metabolic modeling reveals metabolic liabilities of cancer. Elife. 3. PMID 25415239 DOI: 10.7554/Elife.03641  0.358
2014 Jerby-Arnon L, Pfetzer N, Waldman YY, McGarry L, James D, Shanks E, Seashore-Ludlow B, Weinstock A, Geiger T, Clemons PA, Gottlieb E, Ruppin E. Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality. Cell. 158: 1199-209. PMID 25171417 DOI: 10.1016/J.Cell.2014.07.027  0.383
2014 Stempler S, Yizhak K, Ruppin E. Integrating transcriptomics with metabolic modeling predicts biomarkers and drug targets for Alzheimer's disease. Plos One. 9: e105383. PMID 25127241 DOI: 10.1371/Journal.Pone.0105383  0.325
2014 Yizhak K, Le Dévédec SE, Rogkoti VM, Baenke F, de Boer VC, Frezza C, Schulze A, van de Water B, Ruppin E. A computational study of the Warburg effect identifies metabolic targets inhibiting cancer migration. Molecular Systems Biology. 10: 744. PMID 25086087 DOI: 10.15252/Msb.20134993  0.359
2014 Notebaart RA, Szappanos B, Kintses B, Pál F, Györkei Á, Bogos B, Lázár V, Spohn R, CsörgÅ‘ B, Wagner A, Ruppin E, Pál C, Papp B. Network-level architecture and the evolutionary potential of underground metabolism. Proceedings of the National Academy of Sciences of the United States of America. 111: 11762-7. PMID 25071190 DOI: 10.1073/Pnas.1406102111  0.37
2014 Zarecki R, Oberhardt MA, Reshef L, Gophna U, Ruppin E. A novel nutritional predictor links microbial fastidiousness with lowered ubiquity, growth rate, and cooperativeness. Plos Computational Biology. 10: e1003726. PMID 25033033 DOI: 10.1371/Journal.Pcbi.1003726  0.308
2014 Zarecki R, Oberhardt MA, Yizhak K, Wagner A, Shtifman Segal E, Freilich S, Henry CS, Gophna U, Ruppin E. Maximal sum of metabolic exchange fluxes outperforms biomass yield as a predictor of growth rate of microorganisms. Plos One. 9: e98372. PMID 24866123 DOI: 10.1371/Journal.Pone.0098372  0.314
2014 Yizhak K, Gaude E, Dévédec SL, Waldman YY, Stein GY, Water Bvd, Frezza C, Ruppin E. Author response: Phenotype-based cell-specific metabolic modeling reveals metabolic liabilities of cancer Elife. DOI: 10.7554/Elife.03641.023  0.333
2013 Goldstein I, Yizhak K, Madar S, Goldfinger N, Ruppin E, Rotter V. p53 promotes the expression of gluconeogenesis-related genes and enhances hepatic glucose production. Cancer & Metabolism. 1: 9. PMID 24280180 DOI: 10.1186/2049-3002-1-9  0.313
2013 Wagner A, Zarecki R, Reshef L, Gochev C, Sorek R, Gophna U, Ruppin E. Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious. Proceedings of the National Academy of Sciences of the United States of America. 110: 19166-71. PMID 24198337 DOI: 10.1073/Pnas.1312361110  0.379
2013 Yizhak K, Gabay O, Cohen H, Ruppin E. Model-based identification of drug targets that revert disrupted metabolism and its application to ageing. Nature Communications. 4: 2632. PMID 24153335 DOI: 10.1038/Ncomms3632  0.363
2013 Waldman YY, Geiger T, Ruppin E. A genome-wide systematic analysis reveals different and predictive proliferation expression signatures of cancerous vs. non-cancerous cells. Plos Genetics. 9: e1003806. PMID 24068970 DOI: 10.1371/Journal.Pgen.1003806  0.342
2013 Arnon LJ, Weinstock A, Geiger T, Ruppin E. Abstract A32: Systematic reconstruction of the cancer synthetic lethal network and its application for the identification of selective cancer drug targets Molecular Cancer Therapeutics. 12. DOI: 10.1158/1535-7163.Pms-A32  0.373
2012 Jerby L, Ruppin E. Predicting drug targets and biomarkers of cancer via genome-scale metabolic modeling. Clinical Cancer Research : An Official Journal of the American Association For Cancer Research. 18: 5572-84. PMID 23071359 DOI: 10.1158/1078-0432.Ccr-12-1856  0.373
2012 Stein GY, Yosef N, Reichman H, Horev J, Laser-Azogui A, Berens A, Resau J, Ruppin E, Sharan R, Tsarfaty I. Met kinetic signature derived from the response to HGF/SF in a cellular model predicts breast cancer patient survival. Plos One. 7: e45969. PMID 23049908 DOI: 10.1371/Journal.Pone.0045969  0.36
2012 Stempler S, Ruppin E. Analyzing gene expression from whole tissue vs. different cell types reveals the central role of neurons in predicting severity of Alzheimer's disease. Plos One. 7: e45879. PMID 23029292 DOI: 10.1371/Journal.Pone.0045879  0.314
2012 Magger O, Waldman YY, Ruppin E, Sharan R. Enhancing the prioritization of disease-causing genes through tissue specific protein interaction networks. Plos Computational Biology. 8: e1002690. PMID 23028288 DOI: 10.1371/Journal.Pcbi.1002690  0.336
2012 Jerby L, Wolf L, Denkert C, Stein GY, Hilvo M, Oresic M, Geiger T, Ruppin E. Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer. Cancer Research. 72: 5712-20. PMID 22986741 DOI: 10.1158/0008-5472.Can-12-2215  0.365
2012 Lobel L, Sigal N, Borovok I, Ruppin E, Herskovits AA. Integrative genomic analysis identifies isoleucine and CodY as regulators of Listeria monocytogenes virulence. Plos Genetics. 8: e1002887. PMID 22969433 DOI: 10.1371/Journal.Pgen.1002887  0.335
2012 Stempler S, Waldman YY, Wolf L, Ruppin E. Hippocampus neuronal metabolic gene expression outperforms whole tissue data in accurately predicting Alzheimer's disease progression. Neurobiology of Aging. 33: 2230.e13-2230.e21. PMID 22560482 DOI: 10.1016/J.Neurobiolaging.2012.04.003  0.332
2012 Ben-Shitrit T, Yosef N, Shemesh K, Sharan R, Ruppin E, Kupiec M. Systematic identification of gene annotation errors in the widely used yeast mutation collections. Nature Methods. 9: 373-8. PMID 22306811 DOI: 10.1038/Nmeth.1890  0.301
2012 Vardi L, Ruppin E, Sharan R. A linearized constraint-based approach for modeling signaling networks. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 19: 232-40. PMID 22300322 DOI: 10.1089/Cmb.2011.0277  0.319
2012 Mintz-Oron S, Meir S, Malitsky S, Ruppin E, Aharoni A, Shlomi T. Reconstruction of Arabidopsis metabolic network models accounting for subcellular compartmentalization and tissue-specificity. Proceedings of the National Academy of Sciences of the United States of America. 109: 339-44. PMID 22184215 DOI: 10.1073/Pnas.1100358109  0.316
2012 Yizhak K, Gabay O, Cohen H, Ruppin E. Metabolic modeling predicts perturbations extending lifespan in yeast and counteracting aging in mammalian muscle Bmc Proceedings. 6: 54. DOI: 10.1186/1753-6561-6-S3-P54  0.349
2011 Yosef N, Zalckvar E, Rubinstein AD, Homilius M, Atias N, Vardi L, Berman I, Zur H, Kimchi A, Ruppin E, Sharan R. ANAT: a tool for constructing and analyzing functional protein networks. Science Signaling. 4: pl1. PMID 22028466 DOI: 10.1126/Scisignal.2001935  0.342
2011 Gottlieb A, Magger O, Berman I, Ruppin E, Sharan R. PRINCIPLE: a tool for associating genes with diseases via network propagation. Bioinformatics (Oxford, England). 27: 3325-6. PMID 22016407 DOI: 10.1093/Bioinformatics/Btr584  0.309
2011 Reuveni S, Meilijson I, Kupiec M, Ruppin E, Tuller T. Genome-scale analysis of translation elongation with a ribosome flow model. Plos Computational Biology. 7: e1002127. PMID 21909250 DOI: 10.1371/Journal.Pcbi.1002127  0.334
2011 Frezza C, Zheng L, Folger O, Rajagopalan KN, MacKenzie ED, Jerby L, Micaroni M, Chaneton B, Adam J, Hedley A, Kalna G, Tomlinson IP, Pollard PJ, Watson DG, Deberardinis RJ, ... ... Ruppin E, et al. Haem oxygenase is synthetically lethal with the tumour suppressor fumarate hydratase. Nature. 477: 225-8. PMID 21849978 DOI: 10.1038/Nature10363  0.329
2011 Folger O, Jerby L, Frezza C, Gottlieb E, Ruppin E, Shlomi T. Predicting selective drug targets in cancer through metabolic networks. Molecular Systems Biology. 7: 501. PMID 21694718 DOI: 10.1038/Msb.2011.35  0.387
2011 Yizhak K, Tuller T, Papp B, Ruppin E. Metabolic modeling of endosymbiont genome reduction on a temporal scale. Molecular Systems Biology. 7: 479. PMID 21451589 DOI: 10.1038/Msb.2011.11  0.382
2011 Shlomi T, Benyamini T, Gottlieb E, Sharan R, Ruppin E. Genome-scale metabolic modeling elucidates the role of proliferative adaptation in causing the Warburg effect. Plos Computational Biology. 7: e1002018. PMID 21423717 DOI: 10.1371/Journal.Pcbi.1002018  0.362
2011 Folger O, Jerby L, Frezza C, Gottlieb E, Ruppin E, Shlomi T. Predicting selective drug targets in cancer through metabolic networks Nature. 7. DOI: 10.1038/Msb.2011.51  0.354
2010 Zur H, Ruppin E, Shlomi T. iMAT: an integrative metabolic analysis tool. Bioinformatics (Oxford, England). 26: 3140-2. PMID 21081510 DOI: 10.1093/Bioinformatics/Btq602  0.33
2010 Jerby L, Shlomi T, Ruppin E. Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. Molecular Systems Biology. 6: 401. PMID 20823844 DOI: 10.1038/Msb.2010.56  0.331
2010 Ruppin E, Papin JA, de Figueiredo LF, Schuster S. Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks. Current Opinion in Biotechnology. 21: 502-10. PMID 20692823 DOI: 10.1016/J.Copbio.2010.07.002  0.348
2010 Yizhak K, Benyamini T, Liebermeister W, Ruppin E, Shlomi T. Integrating quantitative proteomics and metabolomics with a genome-scale metabolic network model. Bioinformatics (Oxford, England). 26: i255-60. PMID 20529914 DOI: 10.1093/Bioinformatics/Btq183  0.352
2010 Benyamini T, Folger O, Ruppin E, Shlomi T. Flux balance analysis accounting for metabolite dilution. Genome Biology. 11: R43. PMID 20398381 DOI: 10.1186/Gb-2010-11-4-R43  0.323
2010 Freilich S, Kreimer A, Borenstein E, Gophna U, Sharan R, Ruppin E. Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species. Plos Computational Biology. 6: e1000690. PMID 20195496 DOI: 10.1371/Journal.Pcbi.1000690  0.321
2010 Vanunu O, Magger O, Ruppin E, Shlomi T, Sharan R. Associating genes and protein complexes with disease via network propagation. Plos Computational Biology. 6: e1000641. PMID 20090828 DOI: 10.1371/Journal.Pcbi.1000641  0.343
2010 Peleg T, Yosef N, Ruppin E, Sharan R. Network-free inference of knockout effects in yeast. Plos Computational Biology. 6: e1000635. PMID 20066032 DOI: 10.1371/Journal.Pcbi.1000635  0.365
2009 Tuller T, Ruppin E, Kupiec M. Properties of untranslated regions of the S. cerevisiae genome. Bmc Genomics. 10: 391. PMID 19698117 DOI: 10.1186/1471-2164-10-391  0.32
2009 Diamant I, Eldar YC, Rokhlenko O, Ruppin E, Shlomi T. A network-based method for predicting gene-nutrient interactions and its application to yeast amino-acid metabolism. Molecular Biosystems. 5: 1732-9. PMID 19593469 DOI: 10.1039/B823287N  0.365
2009 Freilich S, Kreimer A, Borenstein E, Yosef N, Sharan R, Gophna U, Ruppin E. Metabolic-network-driven analysis of bacterial ecological strategies. Genome Biology. 10: R61. PMID 19500338 DOI: 10.1186/Gb-2009-10-6-R61  0.322
2009 Mintz-Oron S, Aharoni A, Ruppin E, Shlomi T. Network-based prediction of metabolic enzymes' subcellular localization. Bioinformatics (Oxford, England). 25: i247-52. PMID 19477995 DOI: 10.1093/Bioinformatics/Btp209  0.315
2009 Tuller T, Kupiec M, Ruppin E. Co-evolutionary networks of genes and cellular processes across fungal species. Genome Biology. 10: R48. PMID 19416514 DOI: 10.1186/Gb-2009-10-5-R48  0.324
2009 Shlomi T, Cabili MN, Ruppin E. Predicting metabolic biomarkers of human inborn errors of metabolism. Molecular Systems Biology. 5: 263. PMID 19401675 DOI: 10.1038/Msb.2009.22  0.349
2009 Yosef N, Ungar L, Zalckvar E, Kimchi A, Kupiec M, Ruppin E, Sharan R. Toward accurate reconstruction of functional protein networks. Molecular Systems Biology. 5: 248. PMID 19293828 DOI: 10.1038/Msb.2009.3  0.354
2008 Borenstein E, Kupiec M, Feldman MW, Ruppin E. Large-scale reconstruction and phylogenetic analysis of metabolic environments. Proceedings of the National Academy of Sciences of the United States of America. 105: 14482-7. PMID 18787117 DOI: 10.1073/Pnas.0806162105  0.317
2008 Shlomi T, Cabili MN, Herrgård MJ, Palsson BØ, Ruppin E. Network-based prediction of human tissue-specific metabolism. Nature Biotechnology. 26: 1003-10. PMID 18711341 DOI: 10.1038/Nbt.1487  0.333
2008 Dost B, Shlomi T, Gupta N, Ruppin E, Bafna V, Sharan R. QNet: a tool for querying protein interaction networks. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 15: 913-25. PMID 18707533 DOI: 10.1089/Cmb.2007.0172  0.314
2008 Deutscher D, Meilijson I, Schuster S, Ruppin E. Can single knockouts accurately single out gene functions? Bmc Systems Biology. 2: 50. PMID 18564419 DOI: 10.1186/1752-0509-2-50  0.358
2008 Kreimer A, Borenstein E, Gophna U, Ruppin E. The evolution of modularity in bacterial metabolic networks. Proceedings of the National Academy of Sciences of the United States of America. 105: 6976-81. PMID 18460604 DOI: 10.1073/Pnas.0712149105  0.346
2008 Shachar R, Ungar L, Kupiec M, Ruppin E, Sharan R. A systems-level approach to mapping the telomere length maintenance gene circuitry. Molecular Systems Biology. 4: 172. PMID 18319724 DOI: 10.1038/Msb.2008.13  0.341
2008 Behre J, Wilhelm T, von Kamp A, Ruppin E, Schuster S. Structural robustness of metabolic networks with respect to multiple knockouts. Journal of Theoretical Biology. 252: 433-41. PMID 18023456 DOI: 10.1016/J.Jtbi.2007.09.043  0.339
2007 Shlomi T, Herrgard M, Portnoy V, Naim E, Palsson BØ, Sharan R, Ruppin E. Systematic condition-dependent annotation of metabolic genes. Genome Research. 17: 1626-33. PMID 17895423 DOI: 10.1101/Gr.6678707  0.349
2007 Rokhlenko O, Shlomi T, Sharan R, Ruppin E, Pinter RY. Constraint-based functional similarity of metabolic genes: going beyond network topology. Bioinformatics (Oxford, England). 23: 2139-46. PMID 17586548 DOI: 10.1093/Bioinformatics/Btm319  0.367
2007 Fishel I, Kaufman A, Ruppin E. Meta-analysis of gene expression data Bioinformatics. 23: 1599-1606. PMID 17463023 DOI: 10.1093/Bioinformatics/Btm149  0.324
2007 Shlomi T, Eisenberg Y, Sharan R, Ruppin E. A genome-scale computational study of the interplay between transcriptional regulation and metabolism. Molecular Systems Biology. 3: 101. PMID 17437026 DOI: 10.1038/Msb4100141  0.354
2007 Meshi O, Shlomi T, Ruppin E. Evolutionary conservation and over-representation of functionally enriched network patterns in the yeast regulatory network. Bmc Systems Biology. 1: 1-7. PMID 17408505 DOI: 10.1186/1752-0509-1-1  0.305
2007 Kupiec M, Sharan R, Ruppin E. Genetic interactions in yeast: is robustness going bust? Molecular Systems Biology. 3: 97. PMID 17389877 DOI: 10.1038/Msb4100146  0.314
2007 Yosef N, Yakhini Z, Tsalenko A, Kristensen V, Børresen-Dale AL, Ruppin E, Sharan R. A supervised approach for identifying discriminating genotype patterns and its application to breast cancer data. Bioinformatics (Oxford, England). 23: e91-8. PMID 17237111 DOI: 10.1093/Bioinformatics/Btl298  0.324
2007 Borenstein E, Shlomi T, Ruppin E, Sharan R. Gene loss rate: a probabilistic measure for the conservation of eukaryotic genes. Nucleic Acids Research. 35: e7. PMID 17158152 DOI: 10.1093/Nar/Gkl792  0.332
2006 Kaufman A, Dror G, Meilijson I, Ruppin E. Gene Expression of Caenorhabditis elegans Neurons Carries Information on Their Synaptic Connectivity Plos Computational Biology. 2. PMID 17154715 DOI: 10.1371/Journal.Pcbi.0020167  0.33
2006 Deutscher D, Meilijson I, Kupiec M, Ruppin E. Multiple knockout analysis of genetic robustness in the yeast metabolic network. Nature Genetics. 38: 993-8. PMID 16941010 DOI: 10.1038/Ng1856  0.356
2006 Bilu Y, Shlomi T, Barkai N, Ruppin E. Conservation of expression and sequence of metabolic genes is reflected by activity across metabolic states. Plos Computational Biology. 2: e106. PMID 16933982 DOI: 10.1371/Journal.Pcbi.0020106  0.35
2006 Yosef N, Kaufman A, Ruppin E. Inferring functional pathways from multi-perturbation data. Bioinformatics (Oxford, England). 22: e539-46. PMID 16873518 DOI: 10.1093/Bioinformatics/Btl204  0.348
2006 Keinan A, Sandbank B, Hilgetag CC, Meilijson I, Ruppin E. Axiomatic scalable neurocontroller analysis via the Shapley value. Artificial Life. 12: 333-52. PMID 16859444 DOI: 10.1162/Artl.2006.12.3.333  0.325
2006 Shlomi T, Segal D, Ruppin E, Sharan R. QPath: A method for querying pathways in a protein-protein interaction network Bmc Bioinformatics. 7. PMID 16606460 DOI: 10.1186/1471-2105-7-199  0.321
2006 Saggie-Wexler K, Keinan A, Ruppin E. Neural Processing of Counting in Evolved Spiking and McCulloch-Pitts Agents Artificial Life. 12: 1-16. PMID 16393448 DOI: 10.1162/106454606775186428  0.309
2005 Kaufman A, Keinan A, Meilijson I, Kupiec M, Ruppin E. Quantitative analysis of genetic and neuronal multi-perturbation experiments. Plos Computational Biology. 1: e64. PMID 16322764 DOI: 10.1371/Journal.Pcbi.0010064  0.31
2005 Shlomi T, Berkman O, Ruppin E. Regulatory on/off minimization of metabolic flux changes after genetic perturbations Proceedings of the National Academy of Sciences of the United States of America. 102: 7695-7700. PMID 15897462 DOI: 10.1073/Pnas.0406346102  0.33
2004 Keinan A, Sandbank B, Hilgetag CC, Meilijson I, Ruppin E. Fair attribution of functional contribution in artificial and biological networks. Neural Computation. 16: 1887-915. PMID 15265327 DOI: 10.1162/0899766041336387  0.327
2004 Saggie K, Keinan A, Ruppin E. Spikes that count: rethinking spikiness in neurally embedded systems Neurocomputing. 58: 303-311. DOI: 10.1016/J.Neucom.2004.01.060  0.313
2004 Keinan A, Hilgetag CC, Meilijson I, Ruppin E. Causal localization of neural function: The Shapley value method Neurocomputing. 58: 215-222. DOI: 10.1016/J.Neucom.2004.01.046  0.304
2003 Boshy S, Ruppin E. Evolving small neurocontrollers with self-organized compact encoding Artificial Life. 9: 131-151. PMID 12906726 DOI: 10.1162/106454603322221496  0.311
2003 Segev L, Aharonov R, Meilijson I, Ruppin E. High-dimensional analysis of evolutionary autonomous agents. Artificial Life. 9: 1-20. PMID 12725679 DOI: 10.1162/106454603321489491  0.314
2003 Aharonov R, Segev L, Meilijson I, Ruppin E. Localization of function via lesion analysis. Neural Computation. 15: 885-913. PMID 12689391 DOI: 10.1162/08997660360581949  0.318
2001 Aharonov-barki R, Beker T, Ruppin E. Emergence of Memory-Driven Command Neurons in Evolved Artificial Agents Neural Computation. 13: 691-716. PMID 11244562 DOI: 10.1162/089976601300014529  0.3
1999 Horn D, Levy N, Ruppin E. The importance of nonlinear dendritic processing in multimodular memory networks Neurocomputing. 26: 389-394. DOI: 10.1016/S0925-2312(99)00029-6  0.3
1996 Meilijson I, Ruppin E. Optimal firing in sparsely-connected low-activity attractor networks Biological Cybernetics. 74: 479-485. DOI: 10.1007/Bf00209419  0.301
1995 Meilijson I, Ruppin E, Sipper M. A single-iteration threshold Hamming network Ieee Transactions On Neural Networks. 6: 261-266. PMID 18263307 DOI: 10.1109/72.363428  0.305
1994 Meilijson I, Ruppin E. Optimal signalling in attractor neural networks Network: Computation in Neural Systems. 5: 277-298. DOI: 10.1088/0954-898X_5_2_010  0.306
1993 Herrmann M, Ruppin E, Usher M. A neural model of the dynamic activation of memory Biological Cybernetics. 68: 455-463. PMID 8476986 DOI: 10.1007/Bf00198778  0.305
1993 Meilijson I, Ruppin E. History-dependent attractor neural networks Network: Computation in Neural Systems. 4: 195-221. DOI: 10.1088/0954-898X_4_2_004  0.321
1990 Ruppin E, Usher M. An attractor neural network model of semantic fact retrieval Network: Computation in Neural Systems. 1: 325-344. DOI: 10.1088/0954-898X_1_3_003  0.303
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