Publications

Publications

2018

The germline genetic component of drug sensitivity in cancer cell lines.
Menden MP, Casale FP, Stephan J, Bignell GR, Iorio F, McDermott U, Garnett MJ, Saez-Rodriguez J, Stegle O. Nature communications Volume 9 (2018) p.3385 DOI: 10.1038/s41467-018-05811-3
Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting.
Iorio F, Behan FM, Gonçalves E, Bhosle SG, Chen E, Shepherd R, Beaver C, Ansari R, Pooley R, Wilkinson P, Harper S, Butler AP, Stronach EA, Saez-Rodriguez J, Yusa K, Garnett MJ. BMC genomics Volume 19 (2018) p.604 DOI: 10.1186/s12864-018-4989-y
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In silico prioritization of transporter-drug relationships from drug sensitivity screens
Cesar-Razquin A, Girardi E, Yang M, Brehme M, Saez-Rodriguez J, Superti-Furga G. Preprint DOI: 10.1101/381335
A microfluidics platform for combinatorial drug screening on cancer biopsies.
Eduati F, Utharala R, Madhavan D, Neumann UP, Longerich T, Cramer T, Saez-Rodriguez J, Merten CA. Nature communications Volume 9 (2018) p.2434 DOI: 10.1038/s41467-018-04919-w
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Benchmark and integration of resources for the estimation of human transcription factor activities
Garcia-Alonso L, Ibrahim MM, Turei D, Saez-Rodriguez J. Preprint DOI: 10.1101/337915
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Analysis of the human kinome and phosphatome reveals diseased signaling networks induced by overexpression
Lun X, Szklarczyk D, Gabor A, Dobberstein N, Zanotelli VRT, Saez-Rodriguez J, von Mering C, Bodenmiller B. Preprint DOI: 10.1101/314716
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Genomic, Proteomic and Phenotypic Heterogeneity in HeLa Cells across Laboratories: Implications for Reproducibility of Research Results
Liu Y, Mi Y, Mueller T, Kreibich S, Williams EG, Van Drogen A, Borel C, Germain P, Frank M, Bludau I, Mehnert M, Seifert M, Emmenlauer M, Sorg I, Bezrukov F, Bena FS, Zhou H, Dehio C, Testa G, Saez-Rodriguez J, Antonarakis SE, Hardt W, Aebersold R. Preprint DOI: 10.1101/307421
Pathway-based dissection of the genomic heterogeneity of cancer hallmarks' acquisition with SLAPenrich.
Iorio F, Garcia-Alonso L, Brammeld JS, Martincorena I, Wille DR, McDermott U, Saez-Rodriguez J. Scientific reports Volume 8 (2018) p.6713 DOI: 10.1038/s41598-018-25076-6
GDSCTools for mining pharmacogenomic interactions in cancer.
Cokelaer T, Chen E, Iorio F, Menden MP, Lightfoot H, Saez-Rodriguez J, Garnett MJ. Bioinformatics (Oxford, England) Volume 34 (2018) p.1226-1228 DOI: 10.1093/bioinformatics/btx744
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Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer
Berndt N, Egners A, Mastrobuoni G, Vvedenskaya O, Fragoulis A, Dugourd A, Bulik S, Pietzke M, Bielow C, van Gassel R, Olde Damink S, Erdem M, Saez-Rodriguez J, Holzhuetter H, Kempa S, Cramer T. Preprint DOI: 10.1101/275040
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CELLector: Genomics Guided Selection of Cancer in vitro Models
Najgebauer H, Yang M, Francies H, Stronach EA, Garnett MJ, Saez-Rodriguez J, Iorio F. Preprint DOI: 10.1101/275032
Whither systems medicine?
Apweiler R, Beissbarth T, Berthold MR, Blüthgen N, Burmeister Y, Dammann O, Deutsch A, Feuerhake F, Franke A, Hasenauer J, Hoffmann S, Höfer T, Jansen PL, Kaderali L, Klingmüller U, Koch I, Kohlbacher O, Kuepfer L, Lammert F, Maier D, Pfeifer N, Radde N, Rehm M, Roeder I, Saez-Rodriguez J, Sax U, Schmeck B, Schuppert A, Seilheimer B, Theis FJ, Vera J, Wolkenhauer O. Experimental & molecular medicine Volume 50 (2018) p.e453 DOI: 10.1038/emm.2017.290
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Rapid proteotyping reveals cancer biology and drug response determinants in the NCI-60 cells
Guo T, Luna A, Koh CC, Rajapakse V, Wu Z, Menden MP, Cheng Y, Calzone L, Martignetti L, Ori A, Iskar M, Gillet L, Zhong Q, Varma S, Schmitt U, Qiu P, Sun Y, zhu Y, Wild P, Mathew G, Bork P, Beck M, Saez-Rodriguez J, Reinhold W, Sander C, Pommier Y, Aebersold R. Preprint DOI: 10.1101/268953
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Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases
Choobdar S, Ahsen ME, Crawford J, Tomasoni M, Lamparter D, Lin J, Hescott B, Hu X, Mercer J, Natoli T, Narayan R, Subramanian A, Stolovitzky G, Kutalik Z, Lage K, Slonim DK, Saez-Rodriguez J, Cowen LJ, Bergmann S, Marbach D, The DREAM Module Identification Challenge Consortium. Preprint DOI: 10.1101/265553
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A functional landscape of chronic kidney disease entities from public transcriptomic data
Tajti F, Antoranz A, Ibrahim MM, Kim H, Ceccarelli F, Kuppe C, Alexopoulos LG, Kramann R, Saez-Rodriguez J. Preprint DOI: 10.1101/265447
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Modelling cell-cell interactions from spatial molecular data with spatial variance component analysis
Arnol D, Schapiro D, Bodenmiller B, Saez-Rodriguez J, Stegle O. Preprint DOI: 10.1101/265256
NADH Shuttling Couples Cytosolic Reductive Carboxylation of Glutamine with Glycolysis in Cells with Mitochondrial Dysfunction.
Gaude E, Schmidt C, Gammage PA, Dugourd A, Blacker T, Chew SP, Saez-Rodriguez J, O'Neill JS, Szabadkai G, Minczuk M, Frezza C. Molecular cell Volume 69 (2018) p.581-593.e7 DOI: 10.1016/j.molcel.2018.01.034
Perturbation-response genes reveal signaling footprints in cancer gene expression.
Schubert M, Klinger B, Klünemann M, Sieber A, Uhlitz F, Sauer S, Garnett MJ, Blüthgen N, Saez-Rodriguez J. Nature communications Volume 9 (2018) p.20 DOI: 10.1038/s41467-017-02391-6

2017

Transcription Factor Activities Enhance Markers of Drug Sensitivity in Cancer.
Garcia-Alonso L, Iorio F, Matchan A, Fonseca N, Jaaks P, Peat G, Pignatelli M, Falcone F, Benes CH, Dunham I, Bignell G, McDade SS, Garnett MJ, Saez-Rodriguez J. Cancer research Volume 78 (2018) p.769-780 DOI: 10.1158/0008-5472.can-17-1679
Systems Pharmacology Dissection of Cholesterol Regulation Reveals Determinants of Large Pharmacodynamic Variability between Cell Lines.
Blattmann P, Henriques D, Zimmermann M, Frommelt F, Sauer U, Saez-Rodriguez J, Aebersold R. Cell systems Volume 5 (2017) p.604-619.e7 DOI: 10.1016/j.cels.2017.11.002
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Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting
Iorio F, Behan FM, Goncalves E, Bhosle S, Chen E, Shepherd R, Beaver C, Ansari R, Pooley R, Wilkinson P, Harper S, Butler AP, Stronach E, Saez-Rodriguez J, Yusa K, Garnett MJ. Preprint DOI: 10.1101/228189
Post-translational regulation of metabolism in fumarate hydratase deficient cancer cells.
Gonçalves E, Sciacovelli M, Costa ASH, Tran MGB, Johnson TI, Machado D, Frezza C, Saez-Rodriguez J. Metabolic engineering Volume 45 (2018) p.149-157 DOI: 10.1016/j.ymben.2017.11.011
Widespread Post-transcriptional Attenuation of Genomic Copy-Number Variation in Cancer.
Gonçalves E, Fragoulis A, Garcia-Alonso L, Cramer T, Saez-Rodriguez J, Beltrao P. Cell systems Volume 5 (2017) p.386-398.e4 DOI: 10.1016/j.cels.2017.08.013
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A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination prediction
Menden MP, Wang D, Guan Y, Mason M, Szalai B, Bulusu KC, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslavskiy M, Jang IS, Ghazoui Z, Ahsen ME, Vogel R, Chaibub Neto E, Norman T, Tang EK, Garnett MJ, Di Veroli G, Fawell S, Stolovitzky G, Guinney J, Dry JR, Saez-Rodriguez J, AstraZeneca-Sanger Drug Combination DREAM Consorti. Preprint DOI: 10.1101/200451
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A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.
Gönen M, Weir BA, Cowley GS, Vazquez F, Guan Y, Jaiswal A, Karasuyama M, Uzunangelov V, Wang T, Tsherniak A, Howell S, Marbach D, Hoff B, Norman TC, Airola A, Bivol A, Bunte K, Carlin D, Chopra S, Deran A, Ellrott K, Gopalacharyulu P, Graim K, Kaski S, Khan SA, Newton Y, Ng S, Pahikkala T, Paull E, Sokolov A, Tang H, Tang J, Wennerberg K, Xie Y, Zhan X, Zhu F, Broad-DREAM Community, Aittokallio T, Mamitsuka H, Stuart JM, Boehm JS, Root DE, Xiao G, Stolovitzky G, Hahn WC, Margolin AA. Cell systems Volume 5 (2017) p.485-497.e3 DOI: 10.1016/j.cels.2017.09.004
A parallel metaheuristic for large mixed-integer dynamic optimization problems, with applications in computational biology.
Penas DR, Henriques D, González P, Doallo R, Saez-Rodriguez J, Banga JR. PloS one Volume 12 (2017) p.e0182186 DOI: 10.1371/journal.pone.0182186
Genomic Determinants of Protein Abundance Variation in Colorectal Cancer Cells.
Roumeliotis TI, Williams SP, Gonçalves E, Alsinet C, Del Castillo Velasco-Herrera M, Aben N, Ghavidel FZ, Michaut M, Schubert M, Price S, Wright JC, Yu L, Yang M, Dienstmann R, Guinney J, Beltrao P, Brazma A, Pardo M, Stegle O, Adams DJ, Wessels L, Saez-Rodriguez J, McDermott U, Choudhary JS. Cell reports Volume 20 (2017) p.2201-2214 DOI: 10.1016/j.celrep.2017.08.010
Logic Modeling in Quantitative Systems Pharmacology.
Traynard P, Tobalina L, Eduati F, Calzone L, Saez-Rodriguez J. CPT: pharmacometrics & systems pharmacology Volume 6 (2017) p.499-511 DOI: 10.1002/psp4.12225
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GDSCTools for Mining Pharmacogenomic Interactions in Cancer
Cokelaer T, Chen E, Iorio F, Menden MP, Lightfoot H, Saez-Rodriguez J, Mathew GJ. Preprint DOI: 10.1101/166223
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Sequanix: A Dynamic Graphical Interface for Snakemake Workflows
Desvillechabrol D, Legendre R, Rioualen C, Bouchier C, van Helden J, Kennedy S, Cokelaer T. Preprint DOI: 10.1101/162701
Benchmarking substrate-based kinase activity inference using phosphoproteomic data.
Hernandez-Armenta C, Ochoa D, Gonçalves E, Saez-Rodriguez J, Beltrao P. Bioinformatics (Oxford, England) Volume 33 (2017) p.1845-1851 DOI: 10.1093/bioinformatics/btx082
Mechanism-based biomarker discovery.
Antoranz A, Sakellaropoulos T, Saez-Rodriguez J, Alexopoulos LG. Drug discovery today Volume 22 (2017) p.1209-1215 DOI: 10.1016/j.drudis.2017.04.013
Drug Resistance Mechanisms in Colorectal Cancer Dissected with Cell Type-Specific Dynamic Logic Models.
Eduati F, Doldàn-Martelli V, Klinger B, Cokelaer T, Sieber A, Kogera F, Dorel M, Garnett MJ, Blüthgen N, Saez-Rodriguez J. Cancer research Volume 77 (2017) p.3364-3375 DOI: 10.1158/0008-5472.can-17-0078
Genome-wide chemical mutagenesis screens allow unbiased saturation of the cancer genome and identification of drug resistance mutations.
Brammeld JS, Petljak M, Martincorena I, Williams SP, Alonso LG, Dalmases A, Bellosillo B, Robles-Espinoza CD, Price S, Barthorpe S, Tarpey P, Alifrangis C, Bignell G, Vidal J, Young J, Stebbings L, Beal K, Stratton MR, Saez-Rodriguez J, Garnett M, Montagut C, Iorio F, McDermott U. Genome research Volume 27 (2017) p.613-625 DOI: 10.1101/gr.213546.116
System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.
Terfve C, Sabidó E, Wu Y, Gonçalves E, Choi M, Vaga S, Vitek O, Saez-Rodriguez J, Aebersold R. Journal of proteome research Volume 16 (2017) p.831-841 DOI: 10.1021/acs.jproteome.6b00815
Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast.
Gonçalves E, Raguz Nakic Z, Zampieri M, Wagih O, Ochoa D, Sauer U, Beltrao P, Saez-Rodriguez J. PLoS computational biology Volume 13 (2017) p.e1005297 DOI: 10.1371/journal.pcbi.1005297

2016

Efficient randomization of biological networks while preserving functional characterization of individual nodes.
Iorio F, Bernardo-Faura M, Gobbi A, Cokelaer T, Jurman G, Saez-Rodriguez J. BMC bioinformatics Volume 17 (2016) p.542 DOI: 10.1186/s12859-016-1402-1
Stem cell-like transcriptional reprogramming mediates metastatic resistance to mTOR inhibition.
Mateo F, Arenas EJ, Aguilar H, Serra-Musach J, de Garibay GR, Boni J, Maicas M, Du S, Iorio F, Herranz-Ors C, Islam A, Prado X, Llorente A, Petit A, Vidal A, Català I, Soler T, Venturas G, Rojo-Sebastian A, Serra H, Cuadras D, Blanco I, Lozano J, Canals F, Sieuwerts AM, de Weerd V, Look MP, Puertas S, García N, Perkins AS, Bonifaci N, Skowron M, Gómez-Baldó L, Hernández V, Martínez-Aranda A, Martínez-Iniesta M, Serrat X, Cerón J, Brunet J, Barretina MP, Gil M, Falo C, Fernández A, Morilla I, Pernas S, Plà MJ, Andreu X, Seguí MA, Ballester R, Castellà E, Nellist M, Morales S, Valls J, Velasco A, Matias-Guiu X, Figueras A, Sánchez-Mut JV, Sánchez-Céspedes M, Cordero A, Gómez-Miragaya J, Palomero L, Gómez A, Gajewski TF, Cohen EEW, Jesiotr M, Bodnar L, Quintela-Fandino M, López-Bigas N, Valdés-Mas R, Puente XS, Viñals F, Casanovas O, Graupera M, Hernández-Losa J, Ramón Y Cajal S, García-Alonso L, Saez-Rodriguez J, Esteller M, Sierra A, Martín-Martín N, Matheu A, Carracedo A, González-Suárez E, Nanjundan M, Cortés J, Lázaro C, Odero MD, Martens JWM, Moreno-Bueno G, Barcellos-Hoff MH, Villanueva A, Gomis RR, Pujana MA. Oncogene Volume 36 (2017) p.2737-2749 DOI: 10.1038/onc.2016.427
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Rapid identification of optimal drug combinations for personalized cancer therapy using microfluidics
Eduati F, Utharala R, Madhavan D, Neumann UP, Cramer T, Saez-Rodriguez J, Merten CA. Preprint DOI: 10.1101/093906
OmniPath: guidelines and gateway for literature-curated signaling pathway resources.
Türei D, Korcsmáros T, Saez-Rodriguez J. Nature methods Volume 13 (2016) p.966-967 DOI: 10.1038/nmeth.4077
A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia.
Tzelepis K, Koike-Yusa H, De Braekeleer E, Li Y, Metzakopian E, Dovey OM, Mupo A, Grinkevich V, Li M, Mazan M, Gozdecka M, Ohnishi S, Cooper J, Patel M, McKerrell T, Chen B, Domingues AF, Gallipoli P, Teichmann S, Ponstingl H, McDermott U, Saez-Rodriguez J, Huntly BJP, Iorio F, Pina C, Vassiliou GS, Yusa K. Cell reports Volume 17 (2016) p.1193-1205 DOI: 10.1016/j.celrep.2016.09.079
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Pathway-based dissection of the genomic heterogeneity of cancer hallmarks' acquisition with SLAPenrich
Iorio F, Garcia-Alonso L, Brammeld JS, Martincorena I, Wille DR, McDermott U, Saez-Rodriguez J. Preprint DOI: 10.1101/077701
Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition.
Sciacovelli M, Gonçalves E, Johnson TI, Zecchini VR, da Costa AS, Gaude E, Drubbel AV, Theobald SJ, Abbo SR, Tran MG, Rajeeve V, Cardaci S, Foster S, Yun H, Cutillas P, Warren A, Gnanapragasam V, Gottlieb E, Franze K, Huntly B, Maher ER, Maxwell PH, Saez-Rodriguez J, Frezza C. Nature Volume 537 (2016) p.544-547 DOI: 10.1038/nature19353
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Phosphoproteomics-based Profiling of Kinase Activities in Cancer Cells
Wirbel J, Rodriguez Cutillas P, Saez-Rodriguez J. Preprint DOI: 10.1101/066019
A Landscape of Pharmacogenomic Interactions in Cancer.
Iorio F, Knijnenburg TA, Vis DJ, Bignell GR, Menden MP, Schubert M, Aben N, Gonçalves E, Barthorpe S, Lightfoot H, Cokelaer T, Greninger P, van Dyk E, Chang H, de Silva H, Heyn H, Deng X, Egan RK, Liu Q, Mironenko T, Mitropoulos X, Richardson L, Wang J, Zhang T, Moran S, Sayols S, Soleimani M, Tamborero D, Lopez-Bigas N, Ross-Macdonald P, Esteller M, Gray NS, Haber DA, Stratton MR, Benes CH, Wessels LFA, Saez-Rodriguez J, McDermott U, Garnett MJ. Cell Volume 166 (2016) p.740-754 DOI: 10.1016/j.cell.2016.06.017
A rule-based model of insulin signalling pathway.
Di Camillo B, Carlon A, Eduati F, Toffolo GM. BMC systems biology Volume 10 (2016) p.38 DOI: 10.1186/s12918-016-0281-4
A computational method for designing diverse linear epitopes including citrullinated peptides with desired binding affinities to intravenous immunoglobulin.
Patro R, Norel R, Prill RJ, Saez-Rodriguez J, Lorenz P, Steinbeck F, Ziems B, Luštrek M, Barbarini N, Tiengo A, Bellazzi R, Thiesen HJ, Stolovitzky G, Kingsford C. BMC bioinformatics Volume 17 (2016) p.155 DOI: 10.1186/s12859-016-1008-7
Transcriptional response networks for elucidating mechanisms of action of multitargeted agents.
Kibble M, Khan SA, Saarinen N, Iorio F, Saez-Rodriguez J, Mäkelä S, Aittokallio T. Drug discovery today Volume 21 (2016) p.1063-1075 DOI: 10.1016/j.drudis.2016.03.001
Integrated transcriptomic and proteomic analysis identifies protein kinase CK2 as a key signaling node in an inflammatory cytokine network in ovarian cancer cells.
Kulbe H, Iorio F, Chakravarty P, Milagre CS, Moore R, Thompson RG, Everitt G, Canosa M, Montoya A, Drygin D, Braicu I, Sehouli J, Saez-Rodriguez J, Cutillas PR, Balkwill FR. Oncotarget Volume 7 (2016) p.15648-15661 DOI: 10.18632/oncotarget.7255
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Inferring causal molecular networks: empirical assessment through a community-based effort.
Hill SM, Heiser LM, Cokelaer T, Unger M, Nesser NK, Carlin DE, Zhang Y, Sokolov A, Paull EO, Wong CK, Graim K, Bivol A, Wang H, Zhu F, Afsari B, Danilova LV, Favorov AV, Lee WS, Taylor D, Hu CW, Long BL, Noren DP, Bisberg AJ, HPN-DREAM Consortium, Mills GB, Gray JW, Kellen M, Norman T, Friend S, Qutub AA, Fertig EJ, Guan Y, Song M, Stuart JM, Spellman PT, Koeppl H, Stolovitzky G, Saez-Rodriguez J, Mukherjee S. Nature methods Volume 13 (2016) p.310-318 DOI: 10.1038/nmeth.3773
Annexin A1 sustains tumor metabolism and cellular proliferation upon stable loss of HIF1A.
Rohwer N, Bindel F, Grimm C, Lin SJ, Wappler J, Klinger B, Blüthgen N, Du Bois I, Schmeck B, Lehrach H, de Graauw M, Goncalves E, Saez-Rodriguez J, Tan P, Grabsch HI, Prigione A, Kempa S, Cramer T. Oncotarget Volume 7 (2016) p.6693-6710 DOI: 10.18632/oncotarget.6793

2015

The orchestra of lipid-transfer proteins at the crossroads between metabolism and signaling.
Chiapparino A, Maeda K, Turei D, Saez-Rodriguez J, Gavin AC. Progress in lipid research Volume 61 (2016) p.30-39 DOI: 10.1016/j.plipres.2015.10.004
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Pharmacogenomic agreement between two cancer cell line data sets.
Cancer Cell Line Encyclopedia Consortium, Genomics of Drug Sensitivity in Cancer Consortium. Nature Volume 528 (2015) p.84-87 DOI: 10.1038/nature15736
Extended notions of sign consistency to relate experimental data to signaling and regulatory network topologies.
Thiele S, Cerone L, Saez-Rodriguez J, Siegel A, Guziołowski C, Klamt S. BMC bioinformatics Volume 16 (2015) p.345 DOI: 10.1186/s12859-015-0733-7
A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions.
Iorio F, Shrestha RL, Levin N, Boilot V, Garnett MJ, Saez-Rodriguez J, Draviam VM. PloS one Volume 10 (2015) p.e0139446 DOI: 10.1371/journal.pone.0139446
DREAMTools: a Python package for scoring collaborative challenges.
Cokelaer T, Bansal M, Bare C, Bilal E, Bot BM, Chaibub Neto E, Eduati F, de la Fuente A, Gönen M, Hill SM, Hoff B, Karr JR, Küffner R, Menden MP, Meyer P, Norel R, Pratap A, Prill RJ, Weirauch MT, Costello JC, Stolovitzky G, Saez-Rodriguez J. F1000Research Volume 4 (2015) p.1030 DOI: 10.12688/f1000research.7118.2
Large-scale models of signal propagation in human cells derived from discovery phosphoproteomic data.
Terfve CD, Wilkes EH, Casado P, Cutillas PR, Saez-Rodriguez J. Nature communications Volume 6 (2015) p.8033 DOI: 10.1038/ncomms9033
Designing Experiments to Discriminate Families of Logic Models.
Videla S, Konokotina I, Alexopoulos LG, Saez-Rodriguez J, Schaub T, Siegel A, Guziolowski C. Frontiers in bioengineering and biotechnology Volume 3 (2015) p.131 DOI: 10.3389/fbioe.2015.00131
Modeling Signaling Networks to Advance New Cancer Therapies.
Saez-Rodriguez J, MacNamara A, Cook S. Annual review of biomedical engineering Volume 17 (2015) p.143-163 DOI: 10.1146/annurev-bioeng-071813-104927
Prediction of human population responses to toxic compounds by a collaborative competition.
Eduati F, Mangravite LM, Wang T, Tang H, Bare JC, Huang R, Norman T, Kellen M, Menden MP, Yang J, Zhan X, Zhong R, Xiao G, Xia M, Abdo N, Kosyk O, NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration, Friend S, Dearry A, Simeonov A, Tice RR, Rusyn I, Wright FA, Stolovitzky G, Xie Y, Saez-Rodriguez J. Nature biotechnology Volume 33 (2015) p.933-940 DOI: 10.1038/nbt.3299
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Integrative approaches for signalling and metabolic networks.
Hatzimanikatis V, Saez-Rodriguez J. Integrative biology : quantitative biosciences from nano to macro Volume 7 (2015) p.844-845 DOI: 10.1039/c5ib90030a
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Identification of drug-specific pathways based on gene expression data: application to drug induced lung injury.
Melas IN, Sakellaropoulos T, Iorio F, Alexopoulos LG, Loh WY, Lauffenburger DA, Saez-Rodriguez J, Bai JP. Integrative biology : quantitative biosciences from nano to macro Volume 7 (2015) p.904-920 DOI: 10.1039/c4ib00294f
Empirical inference of circuitry and plasticity in a kinase signaling network.
Wilkes EH, Terfve C, Gribben JG, Saez-Rodriguez J, Cutillas PR. Proceedings of the National Academy of Sciences of the United States of America Volume 112 (2015) p.7719-7724 DOI: 10.1073/pnas.1423344112
Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach.
Henriques D, Rocha M, Saez-Rodriguez J, Banga JR. Bioinformatics (Oxford, England) Volume 31 (2015) p.2999-3007 DOI: 10.1093/bioinformatics/btv314
A single-cell model of PIP3 dynamics using chemical dimerization.
MacNamara A, Stein F, Feng S, Schultz C, Saez-Rodriguez J. Bioorganic & medicinal chemistry Volume 23 (2015) p.2868-2876 DOI: 10.1016/j.bmc.2015.04.074
Prospective derivation of a living organoid biobank of colorectal cancer patients.
van de Wetering M, Francies HE, Francis JM, Bounova G, Iorio F, Pronk A, van Houdt W, van Gorp J, Taylor-Weiner A, Kester L, McLaren-Douglas A, Blokker J, Jaksani S, Bartfeld S, Volckman R, van Sluis P, Li VS, Seepo S, Sekhar Pedamallu C, Cibulskis K, Carter SL, McKenna A, Lawrence MS, Lichtenstein L, Stewart C, Koster J, Versteeg R, van Oudenaarden A, Saez-Rodriguez J, Vries RG, Getz G, Wessels L, Stratton MR, McDermott U, Meyerson M, Garnett MJ, Clevers H. Cell Volume 161 (2015) p.933-945 DOI: 10.1016/j.cell.2015.03.053
BioPreDyn-bench: a suite of benchmark problems for dynamic modelling in systems biology.
Villaverde AF, Henriques D, Smallbone K, Bongard S, Schmid J, Cicin-Sain D, Crombach A, Saez-Rodriguez J, Mauch K, Balsa-Canto E, Mendes P, Jaeger J, Banga JR. BMC systems biology Volume 9 (2015) p.8 DOI: 10.1186/s12918-015-0144-4
Cooperative development of logical modelling standards and tools with CoLoMoTo.
Naldi A, Monteiro PT, Müssel C, Consortium for Logical Models and Tools, Kestler HA, Thieffry D, Xenarios I, Saez-Rodriguez J, Helikar T, Chaouiya C. Bioinformatics (Oxford, England) Volume 31 (2015) p.1154-1159 DOI: 10.1093/bioinformatics/btv013

2014

Phosphoproteomic analyses reveal novel cross-modulation mechanisms between two signaling pathways in yeast.
Vaga S, Bernardo-Faura M, Cokelaer T, Maiolica A, Barnes CA, Gillet LC, Hegemann B, van Drogen F, Sharifian H, Klipp E, Peter M, Saez-Rodriguez J, Aebersold R. Molecular systems biology Volume 10 (2014) p.767 DOI: 10.15252/msb.20145112
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Dynamic transcription factor activity and networks during ErbB2 breast oncogenesis and targeted therapy.
Weiss MS, Peñalver Bernabé B, Shin S, Asztalos S, Dubbury SJ, Mui MD, Bellis AD, Bluver D, Tonetti DA, Saez-Rodriguez J, Broadbelt LJ, Jeruss JS, Shea LD. Integrative biology : quantitative biosciences from nano to macro Volume 6 (2014) p.1170-1182 DOI: 10.1039/c4ib00086b
Exploiting combinatorial patterns in cancer genomic data for personalized therapy and new target discovery.
Schubert M, Iorio F. Pharmacogenomics Volume 15 (2014) p.1943-1946 DOI: 10.2217/pgs.14.157
A community computational challenge to predict the activity of pairs of compounds.
Bansal M, Yang J, Karan C, Menden MP, Costello JC, Tang H, Xiao G, Li Y, Allen J, Zhong R, Chen B, Kim M, Wang T, Heiser LM, Realubit R, Mattioli M, Alvarez MJ, Shen Y, NCI-DREAM Community, Gallahan D, Singer D, Saez-Rodriguez J, Xie Y, Stolovitzky G, Califano A, NCI-DREAM Community. Nature biotechnology Volume 32 (2014) p.1213-1222 DOI: 10.1038/nbt.3052
Fast randomization of large genomic datasets while preserving alteration counts.
Gobbi A, Iorio F, Dawson KJ, Wedge DC, Tamborero D, Alexandrov LB, Lopez-Bigas N, Garnett MJ, Jurman G, Saez-Rodriguez J. Bioinformatics (Oxford, England) Volume 30 (2014) p.i617-23 DOI: 10.1093/bioinformatics/btu474
Signaling networks in MS: a systems-based approach to developing new pharmacological therapies.
Kotelnikova E, Bernardo-Faura M, Silberberg G, Kiani NA, Messinis D, Melas IN, Artigas L, Schwartz E, Mazo I, Masso M, Alexopoulos LG, Mas JM, Olsson T, Tegner J, Martin R, Zamora A, Paul F, Saez-Rodriguez J, Villoslada P. Multiple sclerosis (Houndmills, Basingstoke, England) Volume 21 (2015) p.138-146 DOI: 10.1177/1352458514543339
A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models.
Ryll A, Bucher J, Bonin A, Bongard S, Gonçalves E, Saez-Rodriguez J, Niklas J, Klamt S. Bio Systems Volume 124 (2014) p.26-38 DOI: 10.1016/j.biosystems.2014.07.002
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Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming.
Guziolowski C, Videla S, Eduati F, Thiele S, Cokelaer T, Siegel A, Saez-Rodriguez J. Bioinformatics (Oxford, England) Volume 30 (2014) p.1942-1942 DOI: 10.1093/bioinformatics/btu357
A community effort to assess and improve drug sensitivity prediction algorithms.
Costello JC, Heiser LM, Georgii E, Gönen M, Menden MP, Wang NJ, Bansal M, Ammad-ud-din M, Hintsanen P, Khan SA, Mpindi JP, Kallioniemi O, Honkela A, Aittokallio T, Wennerberg K, NCI DREAM Community, Collins JJ, Gallahan D, Singer D, Saez-Rodriguez J, Kaski S, Gray JW, Stolovitzky G. Nature biotechnology Volume 32 (2014) p.1202-1212 DOI: 10.1038/nbt.2877
A rapidly reversible chemical dimerizer system to study lipid signaling in living cells.
Feng S, Laketa V, Stein F, Rutkowska A, MacNamara A, Depner S, Klingmüller U, Saez-Rodriguez J, Schultz C. Angewandte Chemie (International ed. in English) Volume 53 (2014) p.6720-6723 DOI: 10.1002/anie.201402294
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MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics.
Egea JA, Henriques D, Cokelaer T, Villaverde AF, MacNamara A, Danciu DP, Banga JR, Saez-Rodriguez J. BMC Bioinformatics Volume 15 (2014) p.136 DOI: 10.1186/1471-2105-15-136
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Leucine modulates dynamic phosphorylation events in insulin signaling pathway and enhances insulin-dependent glycogen synthesis in human skeletal muscle cells.
Di Camillo B, Eduati F, Nair SK, Avogaro A, Toffolo GM. BMC cell biology Volume 15 (2014) p.9 DOI: 10.1186/1471-2121-15-9
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Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach.
Meyer P, Cokelaer T, Chandran D, Kim KH, Loh PR, Tucker G, Lipson M, Berger B, Kreutz C, Raue A, Steiert B, Timmer J, Bilal E, Sauro HM, Stolovitzky G, Saez-Rodriguez J. BMC systems biology Volume 8 (2014) p.13 DOI: 10.1186/1752-0509-8-13
PIP₃ induces the recycling of receptor tyrosine kinases.
Laketa V, Zarbakhsh S, Traynor-Kaplan A, Macnamara A, Subramanian D, Putyrski M, Mueller R, Nadler A, Mentel M, Saez-Rodriguez J, Pepperkok R, Schultz C. Science signaling Volume 7 (2014) p.ra5 DOI: 10.1126/scisignal.2004532
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Frequency and function of KIR+ CD8+ T cells in HTLV-1 infection.
Twigger K, Rowan A, Seich al Basatena N, MacNamara A, Retiere C, Gould K, Taylor GP, Asquith B, Bangham CR. Retrovirology Volume 11 (2014) p.P79-P79 DOI: 10.1186/1742-4690-11-S1-P79

2013

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Network based elucidation of drug response: from modulators to targets.
Iorio F, Saez-Rodriguez J, di Bernardo D. BMC systems biology Volume 7 (2013) p.139 DOI: 10.1186/1752-0509-7-139
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SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.
Chaouiya C, Bérenguier D, Keating SM, Naldi A, van Iersel MP, Rodriguez N, Dräger A, Büchel F, Cokelaer T, Kowal B, Wicks B, Gonçalves E, Dorier J, Page M, Monteiro PT, von Kamp A, Xenarios I, de Jong H, Hucka M, Klamt S, Thieffry D, Le Novère N, Saez-Rodriguez J, Helikar T. BMC systems biology Volume 7 (2013) p.135 DOI: 10.1186/1752-0509-7-135
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Path2Models: large-scale generation of computational models from biochemical pathway maps.
Büchel F, Rodriguez N, Swainston N, Wrzodek C, Wrzodek C, Czauderna T, Keller R, Mittag F, Schubert M, Glont M, Golebiewski M, van Iersel M, Keating S, Rall M, Wybrow M, Hermjakob H, Hucka M, Kell DB, Müller W, Mendes P, Zell A, Chaouiya C, Saez-Rodriguez J, Schreiber F, Laibe C, Dräger A, Le Novère N. BMC systems biology Volume 7 (2013) p.116 DOI: 10.1186/1752-0509-7-116
BioServices: a common Python package to access biological Web Services programmatically.
Cokelaer T, Pultz D, Harder LM, Serra-Musach J, Saez-Rodriguez J. Bioinformatics (Oxford, England) Volume 29 (2013) p.3241-3242 DOI: 10.1093/bioinformatics/btt547
Cyrface: An interface from Cytoscape to R that provides a user interface to R packages.
Gonçalves E, Mirlach F, Saez-Rodriguez J. F1000Research Volume 2 (2013) p.192 DOI: 10.12688/f1000research.2-192.v2
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Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming.
Guziolowski C, Videla S, Eduati F, Thiele S, Cokelaer T, Siegel A, Saez-Rodriguez J. Bioinformatics (Oxford, England) Volume 29 (2013) p.2320-2326 DOI: 10.1093/bioinformatics/btt393
Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties.
Menden MP, Iorio F, Garnett M, McDermott U, Benes CH, Ballester PJ, Saez-Rodriguez J. PloS one Volume 8 (2013) p.e61318 DOI: 10.1371/journal.pone.0061318
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Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors.
Casado P, Alcolea MP, Iorio F, Rodríguez-Prados JC, Rodríguez-Prados JC, Vanhaesebroeck B, Saez-Rodriguez J, Joel S, Cutillas PR. Genome biology Volume 14 (2013) p.R37 DOI: 10.1186/gb-2013-14-4-r37
Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models.
Gonçalves E, Bucher J, Ryll A, Niklas J, Mauch K, Klamt S, Rocha M, Saez-Rodriguez J. Molecular bioSystems Volume 9 (2013) p.1576-1583 DOI: 10.1039/c3mb25489e
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Critical assessment of automated flow cytometry data analysis techniques.
Aghaeepour N, Finak G, FlowCAP Consortium, DREAM Consortium, Hoos H, Mosmann TR, Brinkman R, Gottardo R, Scheuermann RH. Nature methods Volume 10 (2013) p.228-238 DOI: 10.1038/nmeth.2365
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Evaluation of methods for modeling transcription factor sequence specificity.
Weirauch MT, Cote A, Norel R, Annala M, Zhao Y, Riley TR, Saez-Rodriguez J, Cokelaer T, Vedenko A, Talukder S, DREAM5 Consortium, Bussemaker HJ, Morris QD, Bulyk ML, Stolovitzky G, Hughes TR. Nature biotechnology Volume 31 (2013) p.126-134 DOI: 10.1038/nbt.2486
CySBGN: a Cytoscape plug-in to integrate SBGN maps.
Gonçalves E, van Iersel M, Saez-Rodriguez J. BMC bioinformatics Volume 14 (2013) p.17 DOI: 10.1186/1471-2105-14-17
Modeling signaling networks with different formalisms: a preview.
MacNamara A, Henriques D, Saez-Rodriguez J. Methods in molecular biology (Clifton, N.J.) Volume 1021 (2013) p.89-105 DOI: 10.1007/978-1-62703-450-0_5
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Construction of cell type-specific logic models of signaling networks using CellNOpt.
Morris MK, Melas I, Saez-Rodriguez J. Methods in molecular biology (Clifton, N.J.) Volume 930 (2013) p.179-214 DOI: 10.1007/978-1-62703-059-5_8

2012

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Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.
Mitsos A, Melas IN, Morris MK, Saez-Rodriguez J, Lauffenburger DA, Alexopoulos LG. PloS one Volume 7 (2012) p.e50085 DOI: 10.1371/journal.pone.0050085
DvD: An R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data.
Pacini C, Iorio F, Gonçalves E, Iskar M, Iskar M, Klabunde T, Bork P, Saez-Rodriguez J. Bioinformatics (Oxford, England) Volume 29 (2013) p.132-134 DOI: 10.1093/bioinformatics/bts656
CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.
Terfve C, Cokelaer T, Henriques D, MacNamara A, Goncalves E, Morris MK, van Iersel M, Lauffenburger DA, Saez-Rodriguez J. BMC systems biology Volume 6 (2012) p.133 DOI: 10.1186/1752-0509-6-133
Transcriptional data: a new gateway to drug repositioning?
Iorio F, Rittman T, Ge H, Menden M, Saez-Rodriguez J. Drug discovery today Volume 18 (2013) p.350-357 DOI: 10.1016/j.drudis.2012.07.014
State-time spectrum of signal transduction logic models.
MacNamara A, Terfve C, Henriques D, Bernabé BP, Saez-Rodriguez J. Physical biology Volume 9 (2012) p.045003 DOI: 10.1088/1478-3975/9/4/045003
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Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein interaction network.
Serra-Musach J, Aguilar H, Iorio F, Comellas F, Berenguer A, Brunet J, Saez-Rodriguez J, Pujana MA. Integrative biology : quantitative biosciences from nano to macro Volume 4 (2012) p.1038-1048 DOI: 10.1039/c2ib20052j
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Integrating literature-constrained and data-driven inference of signalling networks.
Eduati F, De Las Rivas J, Di Camillo B, Toffolo G, Saez-Rodriguez J. Bioinformatics (Oxford, England) Volume 28 (2012) p.2311-2317 DOI: 10.1093/bioinformatics/bts363
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L-py: an L-system simulation framework for modeling plant architecture development based on a dynamic language.
Boudon F, Pradal C, Cokelaer T, Prusinkiewicz P, Godin C. Frontiers in plant science Volume 3 (2012) p.76 DOI: 10.3389/fpls.2012.00076
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In contrast to HIV, KIR3DS1 does not influence outcome in HTLV-1 retroviral infection.
O'Connor GM, Seich Al Basatena NK, Olavarria V, MacNamara A, Vine A, Ying Q, Hisada M, Galvão-Castro B, Asquith B, McVicar DW. Human immunology Volume 73 (2012) p.783-787 DOI: 10.1016/j.humimm.2012.05.006
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Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks.
Kirouac DC, Saez-Rodriguez J, Swantek J, Burke JM, Lauffenburger DA, Sorger PK. BMC systems biology Volume 6 (2012) p.29 DOI: 10.1186/1752-0509-6-29
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Systematic identification of genomic markers of drug sensitivity in cancer cells.
Garnett MJ, Edelman EJ, Heidorn SJ, Greenman CD, Dastur A, Lau KW, Greninger P, Thompson IR, Luo X, Soares J, Liu Q, Iorio F, Surdez D, Chen L, Milano RJ, Bignell GR, Tam AT, Davies H, Stevenson JA, Barthorpe S, Lutz SR, Kogera F, Lawrence K, McLaren-Douglas A, Mitropoulos X, Mironenko T, Thi H, Richardson L, Zhou W, Jewitt F, Zhang T, O'Brien P, Boisvert JL, Price S, Hur W, Yang W, Deng X, Butler A, Choi HG, Chang JW, Baselga J, Stamenkovic I, Engelman JA, Sharma SV, Delattre O, Saez-Rodriguez J, Gray NS, Settleman J, Futreal PA, Haber DA, Stratton MR, Ramaswamy S, McDermott U, Benes CH. Nature Volume 483 (2012) p.570-575 DOI: 10.1038/nature11005
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Construction of large signaling pathways using an adaptive perturbation approach with phosphoproteomic data.
Melas IN, Mitsos A, Messinis DE, Weiss TS, Rodriguez JS, Alexopoulos LG. Molecular bioSystems Volume 8 (2012) p.1571-1584 DOI: 10.1039/c2mb05482e
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Dynamic modeling of miRNA-mediated feed-forward loops.
Eduati F, Di Camillo B, Karbiener M, Scheideler M, Corà D, Caselle M, Toffolo G. Journal of computational biology : a journal of computational molecular cell biology Volume 19 (2012) p.188-199 DOI: 10.1089/cmb.2011.0274
Modeling signaling networks using high-throughput phospho-proteomics.
Terfve C, Saez-Rodriguez J. Advances in experimental medicine and biology Volume 736 (2012) p.19-57 DOI: 10.1007/978-1-4419-7210-1_2
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Mapping the human phosphatome on growth pathways.
Sacco F, Gherardini PF, Paoluzi S, Saez-Rodriguez J, Helmer-Citterich M, Ragnini-Wilson A, Castagnoli L, Cesareni G. Molecular systems biology Volume 8 (2012) p.603 DOI: 10.1038/msb.2012.36

2011

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KIR2DL2 enhances protective and detrimental HLA class I-mediated immunity in chronic viral infection.
Seich Al Basatena NK, Macnamara A, Vine AM, Thio CL, Astemborski J, Usuku K, Osame M, Kirk GD, Donfield SM, Goedert JJ, Bangham CR, Carrington M, Khakoo SI, Asquith B. PLoS pathogens Volume 7 (2011) p.e1002270 DOI: 10.1371/journal.ppat.1002270
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Crowdsourcing network inference: the DREAM predictive signaling network challenge.
Prill RJ, Saez-Rodriguez J, Alexopoulos LG, Sorger PK, Stolovitzky G. Science signaling Volume 4 (2011) p.mr7 DOI: 10.1126/scisignal.2002212
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Adaptation as a genome-wide autoregulatory principle in the stress response of yeast.
De Palo G, Eduati F, Zampieri M, Di Camillo B, Toffolo G, Altafini C. IET systems biology Volume 5 (2011) p.269-279 DOI: 10.1049/iet-syb.2009.0050
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Short communication an interferon-γ ELISPOT assay with two cytotoxic T cell epitopes derived from HTLV-1 tax region 161-233 discriminates HTLV-1-associated myelopathy/tropical spastic paraparesis patients from asymptomatic HTLV-1 carriers in a Peruvian population.
Best I, López G, Talledo M, MacNamara A, Verdonck K, González E, Tipismana M, Asquith B, Gotuzzo E, Vanham G, Clark D. AIDS research and human retroviruses Volume 27 (2011) p.1207-1212 DOI: 10.1089/aid.2011.0029
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Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli.
Morris MK, Saez-Rodriguez J, Clarke DC, Sorger PK, Lauffenburger DA. PLoS computational biology Volume 7 (2011) p.e1001099 DOI: 10.1371/journal.pcbi.1001099
Setting the standards for signal transduction research.
Saez-Rodriguez J, Alexopoulos LG, Stolovitzky G. Science signaling Volume 4 (2011) p.pe10 DOI: 10.1126/scisignal.2001844
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HTSanalyzeR: an R/Bioconductor package for integrated network analysis of high-throughput screens.
Wang X, Terfve C, Rose JC, Markowetz F. Bioinformatics (Oxford, England) Volume 27 (2011) p.879-880 DOI: 10.1093/bioinformatics/btr028
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In vivo expression of human T-lymphotropic virus type 1 basic leucine-zipper protein generates specific CD8+ and CD4+ T-lymphocyte responses that correlate with clinical outcome.
Hilburn S, Rowan A, Demontis MA, MacNamara A, Asquith B, Bangham CR, Taylor GP. The Journal of infectious diseases Volume 203 (2011) p.529-536 DOI: 10.1093/infdis/jiq078