Analysis of time-course gene expression profiles to study regulation of cell growth in fed-batch bioreactors
Tài liệu tham khảo
Matasci, 2008, Recombinant therapeutic protein production in cultivated mammalian cells: current status and future prospects, Drug Discov. Today: Technol., 5, e37, 10.1016/j.ddtec.2008.12.003
Zhu, 2012, Mammalian cell protein expression for biopharmaceutical production, Biotechnol. Adv., 30, 1158, 10.1016/j.biotechadv.2011.08.022
Walsh, 2010, Biopharmaceutical benchmarks 2010, Nat. Biotechnol., 28, 917, 10.1038/nbt0910-917
Wurm, 2004, Production of recombinant protein therapeutics in cultivated mammalian cells, Nat. Biotechnol., 22, 1393, 10.1038/nbt1026
Birch, 2006, Antibody production, Adv. Drug Deliv. Rev., 58, 671, 10.1016/j.addr.2005.12.006
Hacker, 2009, 25 years of recombinant proteins from reactor-grown cells—where do we go from here?, Biotechnol. Adv., 27, 1023, 10.1016/j.biotechadv.2009.05.008
Shukla, 2010, Recent advances in large-scale production of monoclonal antibodies and related proteins, Trends Biotechnol., 28, 253, 10.1016/j.tibtech.2010.02.001
Wuest, 2012, Genomics in mammalian cell culture bioprocessing, Biotechnol. Adv., 30, 629, 10.1016/j.biotechadv.2011.10.010
Castro-Melchor, 2012, Transcriptome data analysis for cell culture processes, 27
Stoughton, 2005, Applications of DNA microarrays in biology, Annu. Rev. Biochem., 74, 53, 10.1146/annurev.biochem.74.082803.133212
Sebastiani, 2003, Statistical challenges in functional genomics, Stat. Sci., 33
Hastie, 2004, Efficient quadratic regularization for expression arrays, Biostatistics, 5, 329, 10.1093/biostatistics/kxh010
Chun, 2010, Sparse partial least squares regression for simultaneous dimension reduction and variable selection, J. R. Stat. Soc.: Ser. B (Stat. Methodol.), 72, 3, 10.1111/j.1467-9868.2009.00723.x
Boulesteix, 2007, Partial least squares: a versatile tool for the analysis of high-dimensional genomic data, Brief. Bioinform., 8, 32, 10.1093/bib/bbl016
Zhang, 2009, Penalized orthogonal-components regression for large p small n data, Electron. J. Stat., 3, 781, 10.1214/09-EJS354
Tibshirani, 1996, Regression shrinkage and selection via the lasso, J. R. Stat. Soc.: Ser. B (Methodol.), 58, 267
Zou, 2006, Sparse principal component analysis, J. Comput. Graph. Stat., 15, 265, 10.1198/106186006X113430
Alter, 2000, Singular value decomposition for genome-wide expression data processing and modeling, Proc. Natl. Acad. Sci., 97, 10101, 10.1073/pnas.97.18.10101
Johnson, 2007, Adjusting batch effects in microarray expression data using empirical Bayes methods, Biostatistics, 8, 118, 10.1093/biostatistics/kxj037
Leek, 2010, Tackling the widespread and critical impact of batch effects in high-throughput data, Nat. Rev. Genet., 11, 733, 10.1038/nrg2825
Imbeaud, 2005, Towards standardization of RNA quality assessment using user-independent classifiers of microcapillary electrophoresis traces, Nucleic Acids Res., 33, e56, 10.1093/nar/gni054
Irizarry, 2003, Exploration, normalization, and summaries of high density oligonucleotide array probe level data, Biostatistics, 4, 249, 10.1093/biostatistics/4.2.249
Irizarry, 2002, Summaries of affymetrix GeneChip probe level data, Nucleic Acids Res., 31, e15, 10.1093/nar/gng015
Bolstad, 2003, A comparison of normalization methods for high density oligonucleotide array data based on variance and bias, Bioinformatics, 19, 185, 10.1093/bioinformatics/19.2.185
Gautier, 2004, Affy—analysis of affymetrix GeneChip data at the probe level, Bioinformatics., 20, 307, 10.1093/bioinformatics/btg405
Quackenbush, 2002, Microarray data normalization and transformation, Nat. Genet., 32, 496, 10.1038/ng1032
Schaub, 2010, CHO gene expression profiling in biopharmaceutical process analysis and design, Biotechnol. Bioeng., 105, 431, 10.1002/bit.22549
Charaniya, 2009, Mining transcriptome data for function–trait relationship of hyper productivity of recombinant antibody, Biotechnol. Bioeng., 102, 1654, 10.1002/bit.22210
Price, 2006, Principal components analysis corrects for stratification in genome-wide association studies, Nat. Genet., 38, 904, 10.1038/ng1847
Krämer, 2013, Causal analysis approaches in ingenuity pathway analysis (IPA), Bioinformatics, 30, 523, 10.1093/bioinformatics/btt703
Lutsenko, 2010, Human copper homeostasis: a network of interconnected pathways, Curr. Opin. Chem. Biol., 14, 211, 10.1016/j.cbpa.2010.01.003
van den, 2010, Posttranslational regulation of copper transporters, JBIC J. Biol. Inorg. Chem., 15, 37, 10.1007/s00775-009-0592-7
Huster, 2007, High copper selectively alters lipid metabolism and cell cycle machinery in the mouse model of Wilson disease, J. Biol. Chem., 282, 8343, 10.1074/jbc.M607496200
Huster, 2007, Wilson disease: not just a copper disorder. Analysis of a Wilson disease model demonstrates the link between copper and lipid metabolism, Mol. Biosyst., 3, 816, 10.1039/b711118p
Ralle, 2010, Wilson disease at a single cell level: intracellular copper trafficking activates compartment-specific responses in hepatocytes, J. Biol. Chem., 285, 30875, 10.1074/jbc.M110.114447
Itoh, 2008, Novel role of antioxidant-1 (Atox1) as a copper-dependent transcription factor involved in cell proliferation, J. Biol. Chem., 283, 9157, 10.1074/jbc.M709463200
Rawson, 2003, The SREBP pathway—insights from Insigs and insects, Nat. Rev. Mol. Cell Biol., 4, 631, 10.1038/nrm1174
Sato, 2010, Sterol metabolism and SREBP activation, Arch. Biochem. Biophys., 501, 177, 10.1016/j.abb.2010.06.004
Owen, 2012, Insulin stimulation of SREBP-1c processing in transgenic rat hepatocytes requires p70 S6-kinase, Proc. Natl. Acad. Sci., 109, 16184, 10.1073/pnas.1213343109
Sengupta, 2010, Regulation of the mTOR complex 1 pathway by nutrients, growth factors, and stress, Mol. Cell, 40, 310, 10.1016/j.molcel.2010.09.026
Dodd, 2012, Leucine and mTORC1: a complex relationship, Am. J. Physiol.–Endocrinol. Metabol., 302, E1329, 10.1152/ajpendo.00525.2011
Tai, 2006, A multivariate empirical Bayes statistic for replicated microarray time course data, Ann. Stat., 34, 2387, 10.1214/009053606000000759
