Differential metabolic activity and discovery of therapeutic targets using summarized metabolic pathway models

[1]  Cardona Alzate,et al.  Predicción y selección de variables con bosques aleatorios en presencia de variables correlacionadas , 2020 .

[2]  Joaquín Dopazo,et al.  A comparison of mechanistic signaling pathway activity analysis methods , 2018, Briefings Bioinform..

[3]  Marta R. Hidalgo,et al.  Gene Expression Integration into Pathway Modules Reveals a Pan-Cancer Metabolic Landscape. , 2018, Cancer research.

[4]  Francisco J. Planes,et al.  Creation and analysis of biochemical constraint-based models : the COBRA Toolbox v 3 . 0 26 th February 2018 , 2018 .

[5]  Francisco J. Planes,et al.  Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0. , 2017, 1710.04038.

[6]  C. Lindskog,et al.  A pathology atlas of the human cancer transcriptome , 2017, Science.

[7]  Phillip G. Montgomery,et al.  Defining a Cancer Dependency Map , 2017, Cell.

[8]  Jacob K. Asiedu,et al.  The Drug Repurposing Hub: a next-generation drug library and information resource , 2017, Nature Medicine.

[9]  J. Settleman,et al.  Proline Starvation Induces Unresolved ER Stress and Hinders mTORC1-Dependent Tumorigenesis. , 2016, Cell metabolism.

[10]  A. Schulze,et al.  The multifaceted roles of fatty acid synthesis in cancer , 2016, Nature Reviews Cancer.

[11]  E. Gottlieb,et al.  The metabolic fate of acetate in cancer , 2016, Nature Reviews Cancer.

[12]  Francisco Salavert,et al.  High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes , 2016, bioRxiv.

[13]  Eytan Ruppin,et al.  Data-Driven Metabolic Pathway Compositions Enhance Cancer Survival Prediction , 2016, PLoS Comput. Biol..

[14]  Emanuel J. V. Gonçalves,et al.  Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition , 2016, Nature.

[15]  Joaquín Dopazo,et al.  Web-based network analysis and visualization using CellMaps , 2016, Bioinform..

[16]  Francisco Salavert,et al.  Actionable pathways: interactive discovery of therapeutic targets using signaling pathway models , 2016, Nucleic Acids Res..

[17]  C. Thompson,et al.  The Emerging Hallmarks of Cancer Metabolism. , 2016, Cell metabolism.

[18]  S. Beloribi-Djefaflia,et al.  Lipid metabolic reprogramming in cancer cells , 2016, Oncogenesis.

[19]  Walter Kolch,et al.  Signaling pathway models as biomarkers: Patient-specific simulations of JNK activity predict the survival of neuroblastoma patients , 2015, Science Signaling.

[20]  Francisco Salavert,et al.  Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity , 2015, Scientific Reports.

[21]  S. Sarkar,et al.  Inhibiting WEE1 Selectively Kills Histone H3K36me3-Deficient Cancers by dNTP Starvation , 2015, Cancer cell.

[22]  Theresa Zhang,et al.  Personalized genomic analyses for cancer mutation discovery and interpretation , 2015, Science Translational Medicine.

[23]  J. Rabinowitz,et al.  Quantitative analysis of acetyl-CoA production in hypoxic cancer cells reveals substantial contribution from acetate , 2014, Cancer & Metabolism.

[24]  Joaquín Dopazo,et al.  Understanding disease mechanisms with models of signaling pathway activities , 2014, BMC Systems Biology.

[25]  R. Weinberg,et al.  Dihydropyrimidine Accumulation Is Required for the Epithelial-Mesenchymal Transition , 2014, Cell.

[26]  D. Laifenfeld,et al.  Systems diagnostics: anticipating the next generation of diagnostic tests based on mechanistic insight into disease. , 2014, Drug discovery today.

[27]  J. Dopazo.  Genomics and transcriptomics in drug discovery. , 2014, Drug discovery today.

[28]  Zachary A. King,et al.  Constraint-based models predict metabolic and associated cellular functions , 2014, Nature Reviews Genetics.

[29]  N. Vaidehi,et al.  Human breast cancer metastases to the brain display GABAergic properties in the neural niche , 2014, Proceedings of the National Academy of Sciences.

[30]  P. Pollard,et al.  Succinate: a new epigenetic hacker. , 2013, Cancer cell.

[31]  Francisco Salavert,et al.  Inferring the functional effect of gene expression changes in signaling pathways , 2013, Nucleic Acids Res..

[32]  Fabien Zoulim,et al.  Advances in the development of nucleoside and nucleotide analogues for cancer and viral diseases , 2013, Nature Reviews Drug Discovery.

[33]  Ronan M. T. Fleming,et al.  A community-driven global reconstruction of human metabolism , 2013, Nature Biotechnology.

[34]  D. Vitkup,et al.  Heterogeneity of tumor-induced gene expression changes in the human metabolic network , 2013, Nature Biotechnology.

[35]  W. Kaelin,et al.  Influence of Metabolism on Epigenetics and Disease , 2013, Cell.

[36]  Susumu Goto,et al.  Modular Architecture of Metabolic Pathways Revealed by Conserved Sequences of Reactions , 2013, J. Chem. Inf. Model..

[37]  Karen Blyth,et al.  Serine starvation induces stress and p53 dependent metabolic remodeling in cancer cells , 2012, Nature.

[38]  Monica Chiogna,et al.  Along signal paths: an empirical gene set approach exploiting pathway topology , 2012, Nucleic acids research.

[39]  KyungMann Kim,et al.  Contrasting treatment‐specific survival using double‐robust estimators , 2012 .

[40]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumors , 2012, Nature.

[41]  Neil Swainston,et al.  Improving metabolic flux predictions using absolute gene expression data , 2012, BMC Systems Biology.

[42]  E. Mardis,et al.  A 50-Gene Intrinsic Subtype Classifier for Prognosis and Prediction of Benefit from Adjuvant Tamoxifen , 2012, Clinical Cancer Research.

[43]  Sandrine Dudoit,et al.  More power via graph-structured tests for differential expression of gene networks , 2012, 1206.6980.

[44]  Benjamin E. Gross,et al.  The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. , 2012, Cancer discovery.

[45]  Natapol Pornputtapong,et al.  Reconstruction of Genome-Scale Active Metabolic Networks for 69 Human Cell Types and 16 Cancer Types Using INIT , 2012, PLoS Comput. Biol..

[46]  Atul J. Butte,et al.  Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges , 2012, PLoS Comput. Biol..

[47]  Carlos González-Alcón,et al.  Modeling of leishmaniasis infection dynamics: novel application to the design of effective therapies , 2012, BMC Systems Biology.

[48]  Jason A. Papin,et al.  TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks , 2011, BMC Systems Biology.

[49]  K. Buhman,et al.  Migration of MDA-MB-231 breast cancer cells depends on the availability of exogenous lipids and cholesterol esterification , 2011, Clinical & Experimental Metastasis.

[50]  E. Ruppin,et al.  Predicting selective drug targets in cancer through metabolic networks , 2011, Molecular Systems Biology.

[51]  Rajiv Dhir,et al.  Identification of Hydroxysteroid (17β) dehydrogenase type 12 (HSD17B12) as a CD8+ T-cell-defined human tumor antigen of human carcinomas , 2011, Cancer Immunology, Immunotherapy.

[52]  Eytan Ruppin,et al.  iMAT: an integrative metabolic analysis tool , 2010, Bioinform..

[53]  R. Tagliaferri,et al.  Discovery of drug mode of action and drug repositioning from transcriptional responses , 2010, Proceedings of the National Academy of Sciences.

[54]  M. Warmuth,et al.  Targeted Cancer Therapies in the Twenty‐First Century: Lessons From Imatinib , 2010, Clinical pharmacology and therapeutics.

[55]  J. Dopazo,et al.  Multidimensional Gene Set Analysis of Genomic Data , 2010, PloS one.

[56]  M. Robinson,et al.  A scaling normalization method for differential expression analysis of RNA-seq data , 2010, Genome Biology.

[57]  Julio Saez-Rodriguez,et al.  Identifying Drug Effects via Pathway Alterations using an Integer Linear Programming Optimization Formulation on Phosphoproteomic Data , 2009, PLoS Comput. Biol..

[58]  Pooja Mittal,et al.  A novel signaling pathway impact analysis , 2009, Bioinform..

[59]  Markus J. Herrgård,et al.  Network-based prediction of human tissue-specific metabolism , 2008, Nature Biotechnology.

[60]  David S Wishart,et al.  DrugBank and its relevance to pharmacogenomics. , 2008, Pharmacogenomics.

[61]  T. Henzinger,et al.  Executable cell biology , 2007, Nature Biotechnology.

[62]  P. Khatri,et al.  A systems biology approach for pathway level analysis. , 2007, Genome research.

[63]  Kenneth H. Buetow,et al.  Identification of Key Processes Underlying Cancer Phenotypes Using Biologic Pathway Analysis , 2007, PloS one.

[64]  M. Oti,et al.  The modular nature of genetic diseases , 2006, Clinical genetics.

[65]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[66]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[67]  M. Pierotti,et al.  DHCR24 gene expression is upregulated in melanoma metastases and associated to resistance to oxidative stress‐induced apoptosis , 2005, International journal of cancer.

[68]  Joaquín Dopazo,et al.  FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes , 2004, Bioinform..

[69]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[70]  Y. Benjamini,et al.  Controlling the false discovery rate in behavior genetics research , 2001, Behavioural Brain Research.

[71]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[72]  Vladimir Vapnik,et al.  An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.

[73]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[74]  M. Pagano,et al.  Survival analysis. , 1996, Nutrition.

[75]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[76]  A. Qureshi,et al.  Increasing the thermosensitivity of a mammary tumor (CA755) through dietary modification. , 1986, European journal of cancer & clinical oncology.

[77]  Rupert G. Miller,et al.  Survival Analysis , 2022, The SAGE Encyclopedia of Research Design.

[78]  W. McGuire.  Estrogen receptors in human breast cancer. , 1973, The Journal of clinical investigation.

[79]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[80]  E. Kaplan,et al.  Nonparametric Estimation from Incomplete Observations , 1958 .