Network and systems biology: essential steps in virtualising drug discovery and development

Meacham, 2013, Tumour heterogeneity and cancer cell plasticity, Nature, 501, 328, 10.1038/nature12624 Ma, 2011, Pharmacogenetics, pharmacogenomics, and individualized medicine, Pharmacol Rev, 63, 437, 10.1124/pr.110.003533 Iyengar, 2013, Complex diseases require complex therapies, EMBO Rep, 14, 1039, 10.1038/embor.2013.177 Kovatchev, 2009, In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes, J Diabetes Sci Technol, 3, 44, 10.1177/193229680900300106 Shoemaker, 2006, The NCI60 human tumour cell line anticancer drug screen, Nat Rev Cancer, 6, 813, 10.1038/nrc1951 Hutchinson, 2011, High drug attrition rates – where are we going wrong?, Nat Rev Clin Oncol, 8, 189, 10.1038/nrclinonc.2011.34 Spear, 2001, Clinical application of pharmacogenetics, Trends Mol Med, 7, 201, 10.1016/S1471-4914(01)01986-4 Walters, 1998, Virtual screening – an overview, Drug Discov Today, 3, 160, 10.1016/S1359-6446(97)01163-X Hert, 2006, New methods for ligand-based virtual screening: use of data fusion and machine learning to enhance the effectiveness of similarity searching, J Chem Inf Model, 46, 462, 10.1021/ci050348j Wassermann, 2013, Bioturbo similarity searching: combining chemical and biological similarity to discover structurally diverse bioactive molecules, J Chem Inf Model, 53, 692, 10.1021/ci300607r Li, 2012, Versatile pathway-centric approach based on high-throughput sequencing to anticancer drug discovery, Proc Natl Acad Sci U S A, 109, 4609, 10.1073/pnas.1200305109 Lander, 2001, Initial sequencing and analysis of the human genome, Nature, 409, 860, 10.1038/35057062 Lehrach, 2013, DNA sequencing methods in human genetics and disease research, F1000Prime Rep, 5, 34, 10.12703/P5-34 International Cancer Genome Consortium, 2010, International network of cancer genome projects, Nature, 464, 993, 10.1038/nature08987 Kolodkin, 2012, Emergence of the silicon human and network targeting drugs, Eur J Pharm Sci, 46, 190, 10.1016/j.ejps.2011.06.006 Hood, 2012, Revolutionizing medicine in the 21st century through systems approaches, Biotechnol J, 7, 992, 10.1002/biot.201100306 Van’t Veer, 2002, Gene expression profiling predicts clinical outcome of breast cancer, Nature, 415, 530, 10.1038/415530a Wang, 2005, Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer, Lancet, 365, 671, 10.1016/S0140-6736(05)70933-8 Shen, 2009, Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis, Bioinformatics, 25, 2906, 10.1093/bioinformatics/btp543 Shen, 2012, Integrative subtype discovery in glioblastoma using iCluster, PLoS ONE, 7, e35236, 10.1371/journal.pone.0035236 Ali, 2014, Genome-driven integrated classification of breast cancer validated in over 7,500 samples, Genome Biol, 15, 431, 10.1186/s13059-014-0431-1 Bertucci, 2014, EndoPredict predicts for the response to neoadjuvant chemotherapy in ER-positive, HER2-negative breast cancer, Cancer Lett, 355, 70, 10.1016/j.canlet.2014.09.014 Hornberger, 2012, Clinical validity/utility, change in practice patterns, and economic implications of risk stratifiers to predict outcomes for early-stage breast cancer: a systematic review, J Natl Cancer Inst, 104, 1068, 10.1093/jnci/djs261 Liu, 2012, Seventeen-gene signature from enriched Her2/Neu mammary tumor-initiating cells predicts clinical outcome for human HER2+:ERα-breast cancer, Proc Natl Acad Sci U S A, 109, 5832, 10.1073/pnas.1201105109 Bild, 2006, Oncogenic pathway signatures in human cancers as a guide to targeted therapies, Nature, 439, 353, 10.1038/nature04296 Ein-Dor, 2005, Outcome signature genes in breast cancer: is there a unique set?, Bioinformatics, 21, 171, 10.1093/bioinformatics/bth469 Fan, 2006, Concordance among gene-expression-based predictors for breast cancer, N Engl J Med, 355, 560, 10.1056/NEJMoa052933 Abba, 2010, Breast cancer biomarker discovery in the functional genomic age: a systematic review of 42 gene expression signatures, Biomark Insights, 5, 103, 10.4137/BMI.S5740 Gentleman, 2004, Bioconductor: open software development for computational biology and bioinformatics, Genome Biol, 5, R80, 10.1186/gb-2004-5-10-r80 Huang, 2009, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources, Nat Protoc, 4, 44, 10.1038/nprot.2008.211 Huang, 2009, Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists, Nucleic Acids Res, 37, 1, 10.1093/nar/gkn923 Cerami, 2011, Pathway Commons, a web resource for biological pathway data, Nucleic Acids Res, 39, D685, 10.1093/nar/gkq1039 Kamburov, 2009, ConsensusPathDB – a database for integrating human functional interaction networks, Nucleic Acids Res, 37, D623, 10.1093/nar/gkn698 Kamburov, 2011, ConsensusPathDB: toward a more complete picture of cell biology, Nucleic Acids Res, 39, D712, 10.1093/nar/gkq1156 Schadt, 2009, A network view of disease and compound screening, Nat Rev Drug Discov, 8, 286, 10.1038/nrd2826 Lowe, 2010, Network biology as a new approach to drug discovery, Curr Opin Drug Discov Dev, 13, 524 Harrold, 2013, Network-based approaches in drug discovery and early development, Clin Pharmacol Ther, 94, 651, 10.1038/clpt.2013.176 Pavlopoulos, 2011, Using graph theory to analyze biological networks, BioData Min, 4, 10, 10.1186/1756-0381-4-10 Liu, 2013, Observability of complex systems, Proc Natl Acad Sci U S A, 110, 2460, 10.1073/pnas.1215508110 Mason, 2007, Graph theory and networks in biology, IET Syst Biol, 1, 89, 10.1049/iet-syb:20060038 Huang, 2001, Genomics, complexity and drug discovery: insights from Boolean network models of cellular regulation, Pharmacogenomics, 2, 203, 10.1517/14622416.2.3.203 Fernandez, 2011, Genetic algorithm optimization in drug design QSAR: Bayesian-regularized genetic neural networks (BRGNN) and genetic algorithm-optimized support vectors machines (GA-SVM), Mol Divers, 15, 269, 10.1007/s11030-010-9234-9 Chuang, 2007, Network-based classification of breast cancer metastasis, Mol Syst Biol, 3, 140, 10.1038/msb4100180 Csermely, 2013, Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review, Pharmacol Ther, 138, 333, 10.1016/j.pharmthera.2013.01.016 Chen, 2012, Personal omics profiling reveals dynamic molecular and medical phenotypes, Cell, 148, 1293, 10.1016/j.cell.2012.02.009 Loscalzo, 2011, Systems biology and the future of medicine, Wiley Interdiscip Rev Syst Biol Med, 3, 619, 10.1002/wsbm.144 Hoops, 2006, COPASI – a COmplex PAthway SImulator, Bioinformatics, 22, 3067, 10.1093/bioinformatics/btl485 Funahashi, 2008, CellDesigner 3.5: a versatile modeling tool for biochemical networks, Proc IEEE, 96, 1254, 10.1109/JPROC.2008.925458 Bordbar, 2014, Constraint-based models predict metabolic and associated cellular functions, Nat Rev Genet, 15, 107, 10.1038/nrg3643 Barua, 2013, Modeling the effect of APC truncation on destruction complex function in colorectal cancer cells, PLoS Comput Biol, 9, e1003217, 10.1371/journal.pcbi.1003217 Klinger, 2013, Network quantification of EGFR signaling unveils potential for targeted combination therapy, Mol Syst Biol, 9, 673, 10.1038/msb.2013.29 Kirouac, 2013, Computational modeling of ERBB2-amplified breast cancer identifies combined ErbB2/3 blockade as superior to the combination of MEK and AKT inhibitors, Sci Signal, 6, ra68, 10.1126/scisignal.2004008 Orton, 2009, Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway, BMC Syst Biol, 3, 100, 10.1186/1752-0509-3-100 Zhang, 2014, Proteogenomic characterization of human colon and rectal cancer, Nature, 513, 382, 10.1038/nature13438 Budinska, 2013, Gene expression patterns unveil a new level of molecular heterogeneity in colorectal cancer, J Pathol, 231, 63, 10.1002/path.4212 Borisov, 2009, Systems-level interactions between insulin-EGF networks amplify mitogenic signaling, Mol Syst Biol, 5, 256, 10.1038/msb.2009.19 Folger, 2011, Predicting selective drug targets in cancer through metabolic networks, Mol Syst Biol, 7, 501, 10.1038/msb.2011.35 Thiele, 2013, A community-driven global reconstruction of human metabolism, Nat Biotechnol, 31, 419, 10.1038/nbt.2488 Yuneva, 2012, The metabolic profile of tumors depends on both the responsible genetic lesion and tissue type, Cell Metab, 15, 157, 10.1016/j.cmet.2011.12.015 Caro, 2012, Metabolic signatures uncover distinct targets in molecular subsets of diffuse large B cell lymphoma, Cancer Cell, 22, 547, 10.1016/j.ccr.2012.08.014 Regierer, 2013, Future of medicine: models in predictive diagnostics and personalized medicine, Adv Biochem Eng Biotechnol, 133, 15 Aston, 2015 Al-Lazikani, 2012, Combinatorial drug therapy for cancer in the post-genomic era, Nat Biotechnol, 30, 679, 10.1038/nbt.2284 Kühn, 2012, The Virtual Patient system: modeling cancer using deep sequencing technologies for personalized cancer treatment, J Verbraucherschutz Leb, 7, 55, 10.1007/s00003-011-0755-7 Wierling, 2012, Prediction in the face of uncertainty: a Monte Carlo-based approach for systems biology of cancer treatment, Mutat Res, 746, 163, 10.1016/j.mrgentox.2012.01.005 Wierling, 2007, Resources, standards and tools for systems biology, Brief Funct Genomic Proteomic, 6, 240, 10.1093/bfgp/elm027 Henderson, 2014, Personalised medicine approaches for colon cancer driven by genomics and systems medicine: OncoTrack, Biotechnol J, 9, 1104, 10.1002/biot.201400109 Kravaris, 2013, Advances and selected recent developments in state and parameter estimation, Comput Chem Eng, 51, 111, 10.1016/j.compchemeng.2012.06.001 Röhr, 2013, High-throughput miRNA and mRNA sequencing of paired colorectal normal, tumor and metastasis tissues and bioinformatic modeling of miRNA-1 therapeutic applications, PLoS ONE, 8, e67461, 10.1371/journal.pone.0067461 Kola, 2004, Can the pharmaceutical industry reduce attrition rates?, Nat Rev Drug Discov, 3, 711, 10.1038/nrd1470 Hood, 2014, Demystifying disease, democratizing health care, Sci Transl Med, 6, 225ed5, 10.1126/scitranslmed.3008665 Zazzu, 2013, IT Future of Medicine: from molecular analysis to clinical diagnosis and improved treatment, New Biotechnol, 30, 362, 10.1016/j.nbt.2012.11.002