Mechanistic systems modeling to guide drug discovery and development.
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Jason A. Papin | Cynthia J Musante | Jason A Papin | Brian J Schmidt | C. Musante | B. Schmidt | J. Papin
[1] Y. Z. Ider,et al. Quantitative estimation of insulin sensitivity. , 1979, The American journal of physiology.
[2] R. Bergman,et al. Physiologic evaluation of factors controlling glucose tolerance in man: measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose. , 1981, The Journal of clinical investigation.
[3] D. D’Alessio,et al. Enteral Enhancement of Glucose Disposition by Both Insulin-Dependent and Insulin-Independent Processes: A Physiological Role of Glucagon-Like Peptide I , 1995, Diabetes.
[4] Cynthia L. Stokes,et al. Biological systems modeling: Powerful discipline for biomedical e‐R&D , 2000 .
[5] J. DiMasi. New drug development in the United States from 1963 to 1999 , 2001, Clinical pharmacology and therapeutics.
[6] J. Deisenhofer,et al. Structural Mechanism for Statin Inhibition of HMG-CoA Reductase , 2001, Science.
[7] C J Musante,et al. Small- and large-scale biosimulation applied to drug discovery and development. , 2002, Drug discovery today.
[8] R. Bergman,et al. The evolution of β‐cell dysfunction and insulin resistance in type 2 diabetes , 2002, European journal of clinical investigation.
[9] Patrick Poulin,et al. Prediction of pharmacokinetics prior to in vivo studies. II. Generic physiologically based pharmacokinetic models of drug disposition. , 2002, Journal of pharmaceutical sciences.
[10] R. W. Hansen,et al. The price of innovation: new estimates of drug development costs. , 2003, Journal of health economics.
[11] J. Nielsen,et al. Integration of gene expression data into genome-scale metabolic models. , 2004, Metabolic engineering.
[12] Ping Zhang,et al. Guidelines for computer modeling of diabetes and its complications , 2004 .
[13] Philip J. Barter,et al. Intensive lipid lowering with atorvastatin in patients with stable coronary disease. , 2005, The New England journal of medicine.
[14] Alex Bangs,et al. Predictive biosimulation and virtual patients in pharmaceutical R and D. , 2005, Studies in health technology and informatics.
[15] Nadine A Defranoux,et al. In Silico Modeling and Simulation of Bone Biology: A Proposal , 2005, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.
[16] Michael P Gulseth,et al. Ximelagatran: an orally active direct thrombin inhibitor. , 2005, American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists.
[17] J. Rullmann,et al. Systems biology for battling rheumatoid arthritis: application of the Entelos PhysioLab platform. , 2005, Systems biology.
[18] A. Kansal,et al. Application of predictive biosimulation within pharmaceutical clinical development: examples of significance for translational medicine and clinical trial design. , 2005, Systems biology.
[19] Van V. Brantner,et al. Estimating the cost of new drug development: is it really 802 million dollars? , 2006, Health affairs.
[20] Seth Michelson,et al. In silico prediction of clinical efficacy. , 2006, Current opinion in biotechnology.
[21] G. Clermont,et al. MATHEMATICAL MODEL PREDICTING OUTCOMES OF SEPSIS PATIENTS TREATED WITH XIGRIS®: ENHANCE TRIAL , 2006 .
[22] Hugo Kubinyi,et al. Success Stories of Computer‐Aided Design , 2006 .
[23] B. Palsson,et al. Towards multidimensional genome annotation , 2006, Nature Reviews Genetics.
[24] D. Kell. Systems biology, metabolic modelling and metabolomics in drug discovery and development. , 2006, Drug discovery today.
[25] Michael Hucka,et al. SBMLToolbox: an SBML toolbox for MATLAB users , 2006, Bioinform..
[26] Alex Lawrence Bangs,et al. Target Identification and Validation Using Human Simulation Models , 2006 .
[27] A. Tall,et al. The failure of torcetrapib: was it the molecule or the mechanism? , 2006, Arteriosclerosis, thrombosis, and vascular biology.
[28] S. Klamt,et al. GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism , 2007, Genome Biology.
[29] M. Caulfield,et al. Effects of torcetrapib in patients at high risk for coronary events. , 2007, The New England journal of medicine.
[30] Christopher R. Myers,et al. Universally Sloppy Parameter Sensitivities in Systems Biology Models , 2007, PLoS Comput. Biol..
[31] S. Nissen,et al. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes. , 2007, The New England journal of medicine.
[32] B. Palsson,et al. Genome-scale Reconstruction of Metabolic Network in Bacillus subtilis Based on High-throughput Phenotyping and Gene Essentiality Data* , 2007, Journal of Biological Chemistry.
[33] J. Trimmer,et al. APPLICATION OF PREDICTIVE BIOSIMULATION TO THE STUDY OF ATHEROSCLEROSIS: DEVELOPMENT OF THE CARDIOVASCULAR PHYSIOLAB ® PLATFORM AND EVALUATION OF CETP INHIBITOR THERAPY , 2007 .
[34] Bernhard O. Palsson,et al. Investigating the metabolic capabilities of Mycobacterium tuberculosis H37Rv using the in silico strain iNJ661 and proposing alternative drug targets , 2007 .
[35] Anthony Dowell,et al. Main morbidities recorded in the women's international study of long duration oestrogen after menopause (WISDOM): a randomised controlled trial of hormone replacement therapy in postmenopausal women , 2007, BMJ : British Medical Journal.
[36] O. Demin,et al. The Edinburgh human metabolic network reconstruction and its functional analysis , 2007, Molecular systems biology.
[37] Monica L. Mo,et al. Global reconstruction of the human metabolic network based on genomic and bibliomic data , 2007, Proceedings of the National Academy of Sciences.
[38] B. Palsson,et al. Systems analysis of energy metabolism elucidates the affected respiratory chain complex in Leigh's syndrome. , 2007, Molecular genetics and metabolism.
[39] Neema Jamshidi,et al. A genome-scale, constraint-based approach to systems biology of human metabolism. , 2007, Molecular bioSystems.
[40] John A Wagner,et al. Effect of the cholesteryl ester transfer protein inhibitor, anacetrapib, on lipoproteins in patients with dyslipidaemia and on 24-h ambulatory blood pressure in healthy individuals: two double-blind, randomised placebo-controlled phase I studies , 2007, The Lancet.
[41] Jason A. Papin,et al. Systems analysis of metabolism in the pathogenic trypanosomatid Leishmania major , 2008, Molecular systems biology.
[42] Bernhard O. Palsson,et al. Context-Specific Metabolic Networks Are Consistent with Experiments , 2008, PLoS Comput. Biol..
[43] Jason A. Papin,et al. * Corresponding authors , 2006 .
[44] Markus J. Herrgård,et al. Network-based prediction of human tissue-specific metabolism , 2008, Nature Biotechnology.
[45] W-C Hwang,et al. Identification of Information Flow‐Modulating Drug Targets: A Novel Bridging Paradigm for Drug Discovery , 2008, Clinical pharmacology and therapeutics.
[46] Bernhard O. Palsson,et al. Constraint-based analysis of metabolic capacity of Salmonella typhimurium during host-pathogen interaction , 2009, BMC Systems Biology.
[47] Jason A. Papin,et al. Applications of genome-scale metabolic reconstructions , 2009, Molecular systems biology.
[48] E. Ruppin,et al. Predicting metabolic biomarkers of human inborn errors of metabolism , 2009, Molecular systems biology.
[49] George Steiner,et al. Safety and tolerability of dalcetrapib. , 2009, The American journal of cardiology.
[50] Simon Daefler,et al. Systems approach to investigating host-pathogen interactions in infections with the biothreat agent Francisella. Constraints-based model of Francisella tularensis , 2010, BMC Systems Biology.
[51] Bernhard O. Palsson,et al. BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions , 2010, BMC Bioinformatics.
[52] Eytan Ruppin,et al. Network-based prediction of metabolic enzymes' subcellular localization , 2009, Bioinform..
[53] A Lawrence Gould,et al. Design of the DEFINE trial: determining the EFficacy and tolerability of CETP INhibition with AnacEtrapib. , 2009, American heart journal.
[54] Neema Jamshidi,et al. Genome-scale network analysis of imprinted human metabolic genes , 2009, Epigenetics.
[55] Philip E. Bourne,et al. Drug Discovery Using Chemical Systems Biology: Identification of the Protein-Ligand Binding Network To Explain the Side Effects of CETP Inhibitors , 2009, PLoS Comput. Biol..
[56] Daniel Bloomfield,et al. Efficacy and safety of the cholesteryl ester transfer protein inhibitor anacetrapib as monotherapy and coadministered with atorvastatin in dyslipidemic patients. , 2009, American heart journal.
[57] A. Barabasi,et al. Targets Drug Genomes Identify Novel Antimicrobial Staphylococcus Aureus of Multiple Reconstruction and Flux Balance Analysis Comparative Genome-scale Metabolic Supplemental Material , 2009 .
[58] Ravi Iyengar,et al. Network analyses in systems pharmacology , 2009, Bioinform..
[59] Jaques Reifman,et al. A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis , 2009, BMC Systems Biology.
[60] Steven B Waters,et al. Treatment with Sitagliptin or Metformin Does Not Increase Body Weight despite Predicted Reductions in Urinary Glucose Excretion , 2009, Journal of diabetes science and technology.
[61] J Sarkar,et al. Mathematical modeling of community-acquired pneumonia patients , 2009, Critical Care.
[62] V. Schachter,et al. Genome-scale models of bacterial metabolism: reconstruction and applications , 2008, FEMS microbiology reviews.
[63] Adam M. Feist,et al. Reconstruction of biochemical networks in microorganisms , 2009, Nature Reviews Microbiology.
[64] Nagasuma R. Chandra,et al. Flux balance analysis of biological systems: applications and challenges , 2009, Briefings Bioinform..
[65] Jean-Claude Tardif,et al. Rationale and design of the dal-OUTCOMES trial: efficacy and safety of dalcetrapib in patients with recent acute coronary syndrome. , 2009, American heart journal.
[66] Desmond S. Lun,et al. Interpreting Expression Data with Metabolic Flux Models: Predicting Mycobacterium tuberculosis Mycolic Acid Production , 2009, PLoS Comput. Biol..
[67] Bernhard O. Palsson,et al. A detailed genome-wide reconstruction of mouse metabolism based on human Recon 1 , 2010, BMC Systems Biology.
[68] Eytan Ruppin,et al. iMAT: an integrative metabolic analysis tool , 2010, Bioinform..
[69] Xiaobo Zhou,et al. Predicting enzyme targets for cancer drugs by profiling human Metabolic reactions in NCI-60 cell lines , 2010, BMC Bioinformatics.
[70] Eytan Ruppin,et al. Integrating quantitative proteomics and metabolomics with a genome-scale metabolic network model , 2010, Bioinform..
[71] Rajiv Mahajan,et al. Food and drug administration’s critical path initiative and innovations in drug development paradigm: Challenges, progress, and controversies , 2010, Journal of pharmacy & bioallied sciences.
[72] C. Gille,et al. HepatoNet1: a comprehensive metabolic reconstruction of the human hepatocyte for the analysis of liver physiology , 2010, Molecular systems biology.
[73] Jens Timmer,et al. Systems biology of mammalian cells: a report from the Freiburg conference. , 2010, BioEssays : news and reviews in molecular, cellular and developmental biology.
[74] Xiang-Sun Zhang,et al. Drug Target Identification Based on Flux Balance Analysis of Metabolic Networks , 2010 .
[75] Jennifer G. Robinson,et al. Safety and tolerability of dalcetrapib (RO4607381/JTT-705): results from a 48-week trial , 2010, European heart journal.
[76] Suhua Chang,et al. Exploring the metabolic network of the epidemic pathogen Burkholderia cenocepacia J2315 via genome-scale reconstruction , 2011, BMC Systems Biology.
[77] S. Lee,et al. Genome-scale metabolic network analysis and drug targeting of multi-drug resistant pathogen Acinetobacter baumannii AYE. , 2010, Molecular bioSystems.
[78] Christopher P Cannon,et al. Safety of anacetrapib in patients with or at high risk for coronary heart disease. , 2010, The New England journal of medicine.
[79] G. Mills,et al. Future of personalized medicine in oncology: a systems biology approach. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[80] Philip E. Bourne,et al. Drug Off-Target Effects Predicted Using Structural Analysis in the Context of a Metabolic Network Model , 2010, PLoS Comput. Biol..
[81] Jean-Marie C. Bouteiller,et al. Computational studies of NMDA receptors: differential effects of neuronal activity on efficacy of competitive and non-competitive antagonists. , 2010, Open access bioinformatics.
[82] Arnold von Eckardstein,et al. Mulling over the odds of CETP inhibition , 2010 .
[83] James H. Doroshow,et al. AACR-FDA-NCI Cancer Biomarkers Collaborative Consensus Report: Advancing the Use of Biomarkers in Cancer Drug Development , 2010, Clinical Cancer Research.
[84] K Gadkar,et al. The Type 1 Diabetes PhysioLab® Platform: a validated physiologically based mathematical model of pathogenesis in the non‐obese diabetic mouse , 2010, Clinical and experimental immunology.
[85] B. Palsson,et al. Insight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions , 2010, Molecular systems biology.
[86] Adilson E Motter,et al. Improved network performance via antagonism: From synthetic rescues to multi-drug combinations , 2010, BioEssays : news and reviews in molecular, cellular and developmental biology.
[87] R Sarangapani,et al. A SYSTEMS MODELING APPROACH TO UNDERSTANDING THE MECHANISMS OF RENAL PROTECTION OBSERVED IN THE AVOID STUDY: 5C.02 , 2010 .
[88] E. Ruppin,et al. Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism , 2010, Molecular systems biology.
[89] B. Palsson,et al. Large-scale in silico modeling of metabolic interactions between cell types in the human brain , 2010, Nature Biotechnology.
[90] Jennifer G. Robinson,et al. Dalcetrapib: a review of Phase II data , 2010, Expert opinion on investigational drugs.
[91] Neema Jamshidi,et al. Mass action stoichiometric simulation models: incorporating kinetics and regulation into stoichiometric models. , 2010, Biophysical journal.
[92] James A. Eddy,et al. In silico models of cancer , 2010, Wiley interdisciplinary reviews. Systems biology and medicine.
[93] C. Gallen,et al. Strategic challenges in neurotherapeutic pharmaceutical development , 2011, NeuroRX.
[94] Jason A. Papin,et al. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks , 2011, BMC Systems Biology.
[95] E. Ruppin,et al. Predicting selective drug targets in cancer through metabolic networks , 2011, Molecular systems biology.
[96] Roded Sharan,et al. Genome-Scale Metabolic Modeling Elucidates the Role of Proliferative Adaptation in Causing the Warburg Effect , 2011, PLoS Comput. Biol..
[97] Jason A. Papin,et al. Functional integration of a metabolic network model and expression data without arbitrary thresholding , 2011, Bioinform..
[98] Xiang-Sun Zhang,et al. Two-stage flux balance analysis of metabolic networks for drug target identification , 2011, BMC Systems Biology.
[99] Anna Georgieva,et al. Using a Systems Biology Approach to Explore Hypotheses Underlying Clinical Diversity of the Renin Angiotensin System and the Response to Antihypertensive Therapies , 2011 .
[100] Aarash Bordbar,et al. iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states , 2011, BMC Systems Biology.
[101] Aarash Bordbar,et al. A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology , 2011, BMC Systems Biology.
[102] Marcel J. T. Reinders,et al. Predicting Metabolic Fluxes Using Gene Expression Differences As Constraints , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[103] Gabriela Kalna,et al. Haem oxygenase is synthetically lethal with the tumour suppressor fumarate hydratase , 2011, Nature.
[104] Russ B. Altman,et al. Bioinformatics challenges for personalized medicine , 2011, Bioinform..
[105] Ronan M. T. Fleming,et al. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 , 2007, Nature Protocols.
[106] C. Allaart,et al. Identification of CXCL13 as a marker for rheumatoid arthritis outcome using an in silico model of the rheumatic joint. , 2011, Arthritis and rheumatism.
[107] Karim Wahba,et al. Abstract 9560: Clinical Trial Simulations of Dyslipidemic Patients in a Mechanistic Model of Cardiovascular Disease Predict Little Impact on CHD Events by CETP Inhibitors , 2011 .
[108] Jaques Reifman,et al. Modeling synergistic drug inhibition of Mycobacterium tuberculosis growth in murine macrophages. , 2011, Molecular bioSystems.
[109] Seth I. Berger,et al. Role of systems pharmacology in understanding drug adverse events , 2011, Wiley interdisciplinary reviews. Systems biology and medicine.
[110] Christoph Kaleta,et al. In Silico Evidence for Gluconeogenesis from Fatty Acids in Humans , 2011, PLoS Comput. Biol..
[111] F. Pammolli,et al. The productivity crisis in pharmaceutical R&D , 2011, Nature Reviews Drug Discovery.
[112] S. Lee,et al. Integrative genome-scale metabolic analysis of Vibrio vulnificus for drug targeting and discovery , 2011, Molecular systems biology.
[113] J. DiMasi. The Value of Improving the Productivity of the Drug Development Process , 2012, PharmacoEconomics.
[114] Jason A. Papin,et al. Metabolic network analysis predicts efficacy of FDA-approved drugs targeting the causative agent of a neglected tropical disease , 2012, BMC Systems Biology.
[115] A. Bordbar,et al. Using the reconstructed genome‐scale human metabolic network to study physiology and pathology , 2012, Journal of internal medicine.
[116] Ernesto S. Nakayasu,et al. Model-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation , 2012, Molecular systems biology.
[117] 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..