CHO-omics review: the impact of current and emerging technologies on Chinese hamster ovary based bioproduction

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works

Massively parallel digital transcriptional profiling of single cells

Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353 · see citing works

Genome-scale CRISPR-Cas9 knockout screening in human cells

Shalem, O., Sanjana, N. E., Hartenian, E., Shi, X., Scott, D. A., Mikkelsen, T. S., Heckl, D., Ebert, B. L., Root, D. E., Doench, J. G., et al. (2014) · Science · doi:10.1126/science.1247005 · Cited by 5,234 · see citing works

Essentials of glycobiology

Wiederschain, G. Y. (2009) · Biochemistry (Moscow) · doi:10.1134/s0006297909090156 · Cited by 4,089 · see citing works

Correlation between Protein and mRNA Abundance in Yeast

Gygi, S. P., Rochon, Y., Franza, B. R., & Aebersold, R. (1999) · Molecular and Cellular Biology · doi:10.1128/mcb.19.3.1720 · Cited by 3,819 · see citing works

Metabolomics—the link between genotypes and phenotypes

Fiehn, O. (2002) · Plant Molecular Biology · doi:10.1023/a:1013713905833 · Cited by 3,445 · see citing works

Metabolomics — the link between genotypes and phenotypes

Fiehn, O. (2002) · Springer eBooks · doi:10.1007/978-94-010-0448-0_11 · Cited by 3,168 · see citing works

Genetic screens in human cells using the CRISPR-Cas9 system

Wang, T., Wei, J. J., Sabatini, D. M., & Lander, E. S. (2014) · Science · doi:10.1126/science.1246981 · Cited by 2,856 · see citing works

The molecular hallmarks of epigenetic control

Allis, C. D., & Jenuwein, T. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.59 · Cited by 2,809 · see citing works

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

MAQC Consortium, Shi, L., Shi, L., Reid, L. H., Jones, W. D., Shippy, R., Warrington, J. A., Baker, S. C., Collins, P. J., de Longueville, F., et al. (2006) · Nature Biotechnology · doi:10.1038/nbt1239 · Cited by 2,126 · see citing works

The mitochondrial genome: structure, transcription, translation and replication

Taanman, J.-W. (1999) · Biochimica et Biophysica Acta (BBA) - Bioenergetics · doi:10.1016/s0005-2728(98)00161-3 · Cited by 1,635 · see citing works

Precision mapping of the human O‐GalNAc glycoproteome through SimpleCell technology

Steentoft, C., Vakhrushev, S. Y., Joshi, H. J., Kong, Y., Vester-Christensen, M. B., Schjoldager, K. T.-B. G., Lavrsen, K., Dabelsteen, S., Pedersen, N. B., Marcos-Silva, L., et al. (2013) · The EMBO Journal · doi:10.1038/emboj.2013.79 · Cited by 1,410 · see citing works

Quantitative real-time RT-PCR – a perspective

Bustin, S. A., Benes, V, Nolan, T., & Pfaffl, M. W. (2005) · Journal of Molecular Endocrinology · doi:10.1677/jme.1.01755 · Cited by 1,321 · see citing works

A Multiplexed Single-Cell CRISPR Screening Platform Enables Systematic Dissection of the Unfolded Protein Response

Adamson, B., Norman, T. M., Jost, M., Cho, M. Y., Nuñez, J. K., Chen, Y., Villalta, J. E., Gilbert, L. A., Horlbeck, M. A., Hein, M. Y., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.048 · Cited by 1,193 · see citing works

Genome-Scale Reconstruction of the <i>Saccharomyces cerevisiae</i> Metabolic Network

Förster, J., Famili, I., Fu, P., Palsson, B. Ø., & Nielsen, J. (2003) · Genome Research · doi:10.1101/gr.234503 · Cited by 1,069 · see citing works

The Next-Generation Sequencing Revolution and Its Impact on Genomics

Koboldt, D. C., Steinberg, K. M., Larson, D. E., Wilson, R. K., & Mardis, E. R. (2013) · Cell · doi:10.1016/j.cell.2013.09.006 · Cited by 1,039 · see citing works

A community-driven global reconstruction of human metabolism

Thiele, I., Swainston, N., Fleming, R. M. T., Hoppe, A., Sahoo, S., Aurich, M. K., Haraldsdottir, H., Mo, M. L., Rolfsson, O., Stobbe, M. D., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2488 · Cited by 1,019 · see citing works

Isolation of Chinese hamster cell mutants deficient in dihydrofolate reductase activity

Urlaub, G., & Chasin, L. A. (1980) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.77.7.4216 · Cited by 876 · see citing works

The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line

Xu, X., Nagarajan, H., Lewis, N. E., Pan, S., Cai, Z., Liu, X., Chen, W., Xie, M., Wang, W., Hammond, S., et al. (2011) · Nature Biotechnology · doi:10.1038/nbt.1932 · Cited by 785 · see citing works

The BioMart community portal: an innovative alternative to large, centralized data repositories

Smedley, D., Haider, S., Durinck, S., Pandini, L., Provero, P., Allen, J., Arnaiz, O., Awedh, M. H., Baldock, R., Barbiera, G., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv350 · Cited by 755 · see citing works

Using Genome-scale Models to Predict Biological Capabilities

O’Brien, E. J., Monk, J. M., & Palsson, B. Ø. (2015) · Cell · doi:10.1016/j.cell.2015.05.019 · Cited by 709 · see citing works

Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning

Wang, B., Zhu, J., Pierson, E., Ramazzotti, D., & Batzoglou, S. (2017) · Nature Methods · doi:10.1038/nmeth.4207 · Cited by 706 · see citing works

Optimal and consistent protein glycosylation in mammalian cell culture

Hossler, P., Khattak, S. F., & Li, Z. J. (2009) · Glycobiology · doi:10.1093/glycob/cwp079 · Cited by 669 · see citing works

Characterization of Therapeutic Antibodies and Related Products

Beck, A., Wagner‐Rousset, E., Ayoub, D., DORSSELAER, A. V., & Cianférani, S. (2012) · Analytical Chemistry · doi:10.1021/ac3032355 · Cited by 588 · see citing works

Glycan labeling strategies and their use in identification and quantification

Ruhaak, L. R., Zauner, G., Hühn, C., Bruggink, C., Deelder, A. M., & Wuhrer, M. (2010) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-010-3532-z · Cited by 481 · see citing works

Overview of DNA Microarrays: Types, Applications, and Their Future

Bumgarner, R. E. (2013) · Current Protocols in Molecular Biology · doi:10.1002/0471142727.mb2201s101 · Cited by 467 · see citing works

HPLC-based analysis of serum N-glycans on a 96-well plate platform with dedicated database software

Royle, L., Campbell, M. P., Radcliffe, C. M., White, D. M., Harvey, D. J., Abrahams, J. L., Kim, Y., Henry, G. W., Shadick, N. A., Weinblatt, M. E., et al. (2007) · Analytical Biochemistry · doi:10.1016/j.ab.2007.12.012 · Cited by 466 · see citing works

Universal heteroplasmy of human mitochondrial DNA

Payne, B. A. I., Wilson, I., Yu‐Wai‐Man, P., Coxhead, J., Deehan, D. J., Horváth, R., Taylor, R. W., Samuels, D. C., Santibanez‐Koref, M., & Chinnery, P. F. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds435 · Cited by 396 · see citing works

Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome

Lewis, N. E., Liu, X., Li, Y., Nagarajan, H., Yerganian, G., O'Brien, E., Bordbar, A., Roth, A. M., Rosenbloom, J., Bian, C., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2624 · Cited by 380 · see citing works

The sugar code: functional lectinomics

Gabius, H. (2002) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/s0304-4165(02)00306-9 · Cited by 333 · see citing works

Precise determination of mitochondrial DNA copy number in human skeletal and cardiac muscle by a PCR-based assay: lack of change of copy number with age

Miller, F. J. (2003) · Nucleic Acids Research · doi:10.1093/nar/gng060 · Cited by 332 · see citing works

KEGG as a glycome informatics resource

Hashimoto, K., Goto, S., Kawano, S., Aoki-Kinoshita, K. F., Ueda, N., Hamajima, M., Kawasaki, T., & Kanehisa, M. I. (2005) · Glycobiology · doi:10.1093/glycob/cwj010 · Cited by 320 · see citing works

The art of CHO cell engineering: A comprehensive retrospect and future perspectives

Fischer, S., Handrick, R., & Otte, K. (2015) · Biotechnology Advances · doi:10.1016/j.biotechadv.2015.10.015 · Cited by 314 · see citing works

A study of monoclonal antibody‐producing CHO cell lines: What makes a stable high producer?

Chusainow, J., Yang, Y., Yeo, J. H. M., Toh, P. C., Asvadi, P., Wong, N. S. C., & Yap, M. G. S. (2008) · Biotechnology and Bioengineering · doi:10.1002/bit.22158 · Cited by 312 · see citing works

Pathways to the analysis of microarray data

Curtis, R. K., Orešič, M., & Vidal‐Puig, A. (2005) · Trends in biotechnology · doi:10.1016/j.tibtech.2005.05.011 · Cited by 308 · see citing works

Silencing of transgene transcription precedes methylation of promoter DNA and histone H3 lysine 9

Mutskov, V. J., & Felsenfeld, G. (2003) · The EMBO Journal · doi:10.1038/sj.emboj.7600013 · Cited by 297 · see citing works

Determination of glycosylation sites and site-specific heterogeneity in glycoproteins

An, H. J., Froehlich, J. W., & Lebrilla, C. B. (2009) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2009.07.022 · Cited by 282 · see citing works

Engineered CHO cells for production of diverse, homogeneous glycoproteins

Yang (2015) · Nature Biotechnology · doi:10.1038/nbt.3280 · Cited by 254 · see citing works

A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

Hefzi, H., Ang, K. S., Hanscho, M., Bordbar, A., Ruckerbauer, D. E., Lakshmanan, M., Orellana, C. A., Baycin‐Hizal, D., Huang, Y., Ley, D., et al. (2016) · Cell Systems · doi:10.1016/j.cels.2016.10.020 · Cited by 253 · see citing works

Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare

Suravajhala, P., Kogelman, L. J. A., & Kadarmideen, H. N. (2016) · Genetics Selection Evolution · doi:10.1186/s12711-016-0217-x · Cited by 219 · see citing works

Metabolomics: quantification of intracellular metabolite dynamics

Buchholz, A., Hurlebaus, J., Wandrey, C., & Takors, R. (2002) · Biomolecular Engineering · doi:10.1016/s1389-0344(02)00003-5 · Cited by 215 · see citing works

A mechanistic understanding of production instability in CHO cell lines expressing recombinant monoclonal antibodies

Kim, M., O’Callaghan, P. M., Droms, K. A., & James, D. C. (2011) · Biotechnology and Bioengineering · doi:10.1002/bit.23189 · Cited by 215 · see citing works

Challenges of glycosylation analysis and control: an integrated approach to producing optimal and consistent therapeutic drugs

Zhang, P., Woen, S., Wang, T., Liau, B., Zhao, S., Chen, C., Yang, Y., Song, Z., Wormald, M. R., Yu, C., et al. (2016) · Drug Discovery Today · doi:10.1016/j.drudis.2016.01.006 · Cited by 212 · see citing works

Glycan analysis of therapeutic glycoproteins

Zhang, L., Luo, S., & Zhang, B. (2016) · mAbs · doi:10.1080/19420862.2015.1117719 · Cited by 207 · see citing works

High-Throughput IgG Fc N-Glycosylation Profiling by Mass Spectrometry of Glycopeptides

Pučić‐Baković, M., Selman, M. H. J., Hoffmann, M., Rudan, I., Campbell, H., Deelder, A. M., Lauc, G., & Wuhrer, M. (2013) · Journal of Proteome Research · doi:10.1021/pr300887z · Cited by 204 · see citing works

Combined in silico modeling and metabolomics analysis to characterize fed‐batch CHO cell culture

Selvarasu, S., Ho, Y. S., Chong, W. P. K., Wong, N. S. C., Yusufi, F. N. K., Lee, Y. Y., Yap, M. G. S., & Lee, D. (2012) · Biotechnology and Bioengineering · doi:10.1002/bit.24445 · Cited by 202 · see citing works

Cell Biology: A Laboratory Handbook

Heintzmann, R. (2006) · Cited by 202 · see citing works

Characterizing DNA methylation alterations from The Cancer Genome Atlas

Weisenberger, D. J. (2014) · Journal of Clinical Investigation · doi:10.1172/jci69740 · Cited by 200 · see citing works

Accelerating genome editing in CHO cells using CRISPR Cas9 and CRISPy, a web-based target finding tool

Ronda, C., Pedersen, L. E., Hansen, H. G., Kallehauge, T. B., Betenbaugh, M. J., Nielsen, A. T., & Kildegaard, H. F. (2014) · Biotechnology and Bioengineering · doi:10.1002/bit.25233 · Cited by 195 · see citing works

Analysis of omics data with genome-scale models of metabolism

Hyduke, D. R., Lewis, N. E., & Palsson, B. Ø. (2012) · Molecular BioSystems · doi:10.1039/c2mb25453k · Cited by 181 · see citing works

Recombinase-Mediated Cassette Exchange (RMCE): Traditional Concepts and Current Challenges

Turan, S., Galla, M., Ernst, E., Qiao, J., Voelkel, C., Schiedlmeier, B., Zehe, C., & Bode, J. (2011) · Journal of Molecular Biology · doi:10.1016/j.jmb.2011.01.004 · Cited by 179 · see citing works

Proteomic analysis of Chinese hamster ovary cells

Baycin-Hizal, D., Tabb, D. L., Chaerkady, R., Chen, L., Lewis, N. E., Nagarajan, H., Sarkaria, V., Kumar, A., Wolozny, D., Colao, J., et al. (2012) · Journal of Proteome Research · doi:10.1021/pr300476w · Cited by 178 · see citing works

CHO Quasispecies—Implications for Manufacturing Processes

Wurm, F. M. (2013) · Processes · doi:10.3390/pr1030296 · Cited by 172 · see citing works

Rapid and Deep Proteomes by Faster Sequencing on a Benchtop Quadrupole Ultra-High-Field Orbitrap Mass Spectrometer

Kelstrup, C. D., Jersie-Christensen, R., Batth, T. S., Arrey, T. N., Kuehn, A., Kellmann, M., & Olsen, J. V. (2014) · Journal of Proteome Research · doi:10.1021/pr500985w · Cited by 170 · see citing works

Chinese hamster genome sequenced from sorted chromosomes

Brinkrolf, K., Rupp, O., Laux, H., Kollin, F., Ernst, W., Linke, B., Kofler, R., Romand, S., Hesse, F., Budach, W. E., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2645 · Cited by 166 · see citing works

Cell Engineering and Cultivation of Chinese Hamster Ovary (CHO) Cells

Ōmasa, T., Onitsuka, M., & Kim, W.-D. (2010) · Current Pharmaceutical Biotechnology · doi:10.2174/138920110791111960 · Cited by 165 · see citing works

Decreasing lactate level and increasing antibody production in Chinese Hamster Ovary cells (CHO) by reducing the expression of lactate dehydrogenase and pyruvate dehydrogenase kinases

Zhou, M., Crawford, Y., Ng, D., Tung, J. K., Pynn, A. F. J., Meier, A., Yuk, I. H. Y., Vijayasankaran, N., Leach, K., Joly, J. C., et al. (2011) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2011.03.003 · Cited by 156 · see citing works

Genetic characterization of CHO production host DG44 and derivative recombinant cell lines

Derouazi, M., Martinet, D., Schmutz, N. B., Flaction, R., Wicht, M., Bertschinger, M., Hacker, D. L., Beckmann, J. S., & Wurm, F. M. (2005) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2005.12.111 · Cited by 152 · see citing works

Comprehensive genome and epigenome characterization of CHO cells in response to evolutionary pressures and over time

Feichtinger, J., Hernández, I., Fischer, C., Hanscho, M., Auer, N., Hackl, M., Jadhav, V., Baumann, M., Krempl, P. M., Schmidl, C., et al. (2016) · Biotechnology and Bioengineering · doi:10.1002/bit.25990 · Cited by 148 · see citing works

Physiological and Pharmacological Control of BAK, BAX, and Beyond

Luna-Vargas, M. P. A., & Chipuk, J. E. (2016) · Trends in Cell Biology · doi:10.1016/j.tcb.2016.07.002 · Cited by 142 · see citing works

DNA methylation contributes to loss in productivity of monoclonal antibody-producing CHO cell lines

Yang, Y., Mariati, Chusainow, J., & Yap, M. G. S. (2010) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2010.04.004 · Cited by 139 · see citing works

Metabolic analysis of antibody producing CHO cells in fed‐batch production

Dean, J. T., & Reddy, P. (2013) · Biotechnology and Bioengineering · doi:10.1002/bit.24826 · Cited by 138 · see citing works

Lectins: a primer for histochemists and cell biologists

Manning, J. C., Romero, A., Habermann, F. A., García Caballero, G., Kaltner, H., & Gabius, H.-J. (2017) · Histochemistry and Cell Biology · doi:10.1007/s00418-016-1524-6 · Cited by 133 · see citing works

Metabolic flux analysis of CHO cell metabolism in the late non‐growth phase

Sengupta, N., Rose, S., & Morgan, J. A. (2010) · Biotechnology and Bioengineering · doi:10.1002/bit.22890 · Cited by 131 · see citing works

Promoter methylation and transgene copy numbers predict unstable protein production in recombinant chinese hamster ovary cell lines

Osterlehner, A., Simmeth, S., & Göpfert, U. (2011) · Biotechnology and Bioengineering · doi:10.1002/bit.23216 · Cited by 131 · see citing works

Probing isoform-specific functions of polypeptide GalNAc-transferases using zinc finger nuclease glycoengineered SimpleCells

Schjoldager, K. T.-B. G., Vakhrushev, S. Y., Kong, Y., Steentoft, C., Nudelman, A. S., Pedersen, N. B., Wandall, H. H., Mandel, U., Bennett, E., Levery, S. B., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1203563109 · Cited by 130 · see citing works

Flux balance analysis of CHO cells before and after a metabolic switch from lactate production to consumption

Martínez, V. S., Dietmair, S., Quek, L., Hodson, M. P., Gray, P. P., & Nielsen, L. K. (2012) · Biotechnology and Bioengineering · doi:10.1002/bit.24728 · Cited by 129 · see citing works

An 'omics approach towards CHO cell engineering

Datta, P., Linhardt, R. J., & Sharfstein, S. T. (2013) · Biotechnology and Bioengineering · doi:10.1002/bit.24841 · Cited by 129 · see citing works

fast G ap F ill : efficient gap filling in metabolic networks

Thiele, I., Vlassis, N. A., & Fleming, R. M. T. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu321 · Cited by 123 · see citing works

A Multi-Omics Analysis of Recombinant Protein Production in Hek293 Cells

Dietmair, S., Hodson, M. P., Quek, L., Timmins, N. E., Gray, P. P., & Nielsen, L. K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0043394 · Cited by 121 · see citing works

First CHO genome

Wurm, F. M., & Hacker, D. L. (2011) · Nature Biotechnology · doi:10.1038/nbt.1943 · Cited by 118 · see citing works

A single nutrient feed supports both chemically defined NS0 and CHO fed‐batch processes: Improved productivity and lactate metabolism

Ma, N., Ellet, J., Okediadi, C., Hermes, P., McCormick, E. L., & Casnocha, S. A. (2009) · Biotechnology Progress · doi:10.1002/btpr.238 · Cited by 112 · see citing works

Engineering CHO cell growth and recombinant protein productivity by overexpression of miR-7

Barron, N., Kumar, N., Sanchez, N., Doolan, P., Clarke, C., Meleady, P., O'Sullivan, F., & Clynes, M. (2011) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2010.12.005 · Cited by 110 · see citing works

Genome editing using FACS enrichment of nuclease-expressing cells and indel detection by amplicon analysis

Lonowski, L. A., Narimatsu, Y., Riaz, A., Delay, C. M., Yang, Z., Niola, F., Duda, K., Ober, E. A., Clausen, H., Wandall, H. H., et al. (2017) · Nature Protocols · doi:10.1038/nprot.2016.165 · Cited by 109 · see citing works

Applications of genome-scale metabolic network model in metabolic engineering

Kim, B., Kim, W. J., Kim, D. I., & Lee, S. Y. (2014) · Journal of Industrial Microbiology & Biotechnology · doi:10.1007/s10295-014-1554-9 · Cited by 104 · see citing works

Enhanced Mass Spectrometric Mapping of the Human GalNAc-type O-Glycoproteome with SimpleCells

Vakhrushev, S. Y., Steentoft, C., Vester-Christensen, M. B., Bennett, E., Clausen, H., & Levery, S. B. (2013) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o112.021972 · Cited by 102 · see citing works

ST3Gal-4 is the primary sialyltransferase regulating the synthesis of E-, P-, and L-selectin ligands on human myeloid leukocytes

Mondal, N., Buffone, A., Stolfa, G., Antonopoulos, A., Lau, J. T. Y., Haslam, S. M., Dell, A., & Neelamegham, S. (2014) · Blood · doi:10.1182/blood-2014-07-588590 · Cited by 101 · see citing works

Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation

Sheynkman, G., Shortreed, M. R., Cesnik, A. J., & Smith, L. M. (2016) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-071015-041722 · Cited by 99 · see citing works

Into the unknown: expression profiling without genome sequence information in CHO by next generation sequencing

Birzele, F., Schaub, J., Rust, W., Clemens, C., Baum, P., Kaufmann, H., Weith, A., Schulz, T. W., & Hildebrandt, T. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq116 · Cited by 98 · see citing works

Unraveling the Chinese hamster ovary cell line transcriptome by next-generation sequencing

Becker, J., Hackl, M., Rupp, O., Jakobi, T., Schneider, J., Szczepanowski, R., Bekel, T., Borth, N., Goesmann, A., Grillari, J., et al. (2011) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2011.09.014 · Cited by 98 · see citing works

Identification of cell culture conditions to control N‐glycosylation site‐occupancy of recombinant glycoproteins expressed in CHO cells

Gawlitzek, M., Estacio, M., Fürch, T., & Kiss, R. (2009) · Biotechnology and Bioengineering · doi:10.1002/bit.22348 · Cited by 97 · see citing works

A Markov chain model for N-linked protein glycosylation – towards a low-parameter tool for model-driven glycoengineering

Spahn, P. N., Hansen, A. H., Hansen, H. G., Arnsdorf, J., Kildegaard, H. F., & Lewis, N. E. (2015) · Metabolic Engineering · doi:10.1016/j.ymben.2015.10.007 · Cited by 96 · see citing works

Predicting cell-specific productivity from CHO gene expression

Clarke, C., Doolan, P., Barron, N., Meleady, P., O’Sullivan, F., Gammell, P., Melville, M. W., Leonard, M. W., & CLYNES, M. M. (2010) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2010.11.016 · Cited by 94 · see citing works

Sequencing the CHO DXB11 genome reveals regional variations in genomic stability and haploidy

Kaas, C. S., Kristensen, C., Betenbaugh, M. J., & Andersen, M. R. (2015) · BMC Genomics · doi:10.1186/s12864-015-1391-x · Cited by 93 · see citing works

LC‐MS‐based metabolic characterization of high monoclonal antibody‐producing Chinese hamster ovary cells

Chong, W. P. K., Thng, S. H., Hiu, A. P., Lee, D., Chan, E. C. Y., & Ho, Y. S. (2012) · Biotechnology and Bioengineering · doi:10.1002/bit.24580 · Cited by 92 · see citing works

Separation-based Glycoprofiling Approaches using Fluorescent Labels

Domann, P. J., Pardos-Pardos, A. C., Fernandes, D. L., Spencer, D. I. R., Radcliffe, C. M., Royle, L., Dwek, R. A., & Rudd, P. M. (2007) · PROTEOMICS · doi:10.1002/pmic.200700640 · Cited by 92 · see citing works

Chinese hamster genome database: An online resource for the CHO community at www.CHOgenome.org

Hammond, S., Kaplarevic, M., Borth, N., Betenbaugh, M. J., & Lee, K. H. (2011) · Biotechnology and Bioengineering · doi:10.1002/bit.24374 · Cited by 87 · see citing works

Dynamic mRNA and miRNA profiling of CHO‐K1 suspension cell cultures

Bort, J. A. H., Hackl, M., Höflmayer, H., Jadhav, V., Harreither, E., Kumar, N., Ernst, W., Grillari, J., & Borth, N. (2011) · Biotechnology Journal · doi:10.1002/biot.201100143 · Cited by 86 · see citing works

The GalNAc-type O-Glycoproteome of CHO Cells Characterized by the SimpleCell Strategy

Yang, Z., Halim, A., Narimatsu, Y., Joshi, H. J., Steentoft, C., Schjoldager, K. T.-B. G., Schulz, M. A., Sealover, N. R., Kayser, K. J., Bennett, E., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.041541 · Cited by 85 · see citing works

CHO microRNA engineering is growing up: Recent successes and future challenges

Jadhav, V., Hackl, M., Druz, A., Shridhar, S., Chung, C., Heffner, K. M., Kreil, D. P., Betenbaugh, M., Shiloach, J., Barron, N., et al. (2013) · Biotechnology Advances · doi:10.1016/j.biotechadv.2013.07.007 · Cited by 85 · see citing works

Death upon a Kiss: Mitochondrial Outer Membrane Composition and Organelle Communication Govern Sensitivity to BAK/BAX-Dependent Apoptosis

Renault, T. T., & Chipuk, J. E. (2013) · Chemistry & Biology · doi:10.1016/j.chembiol.2013.10.009 · Cited by 82 · see citing works

Association between a common mitochondrial DNA D-loop polycytosine variant and alteration of mitochondrial copy number in human peripheral blood cells

Liou, C.-W., Lin, T.-K., Chen, J.-B., Tiao, M.-M., Weng, S.-W., Chen, S.-D., Chuang, Y.-C., Chuang, J.-H., & Wang, P.-W. (2010) · Journal of Medical Genetics · doi:10.1136/jmg.2010.077552 · Cited by 79 · see citing works

Review of the literature examining the correlation among DNA microarray technologies

Yauk, C. L., & Berndt, M. L. (2007) · Environmental and Molecular Mutagenesis · doi:10.1002/em.20290 · Cited by 79 · see citing works

Genome-Scale Modeling of the Protein Secretory Machinery in Yeast

Feizi, A., Österlund, T., Petranović, D., Bordel, S., & Nielsen, J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063284 · Cited by 79 · see citing works

Fast Mitochondrial DNA Isolation from Mammalian cells for Next-Generation Sequencing

Quispe‐Tintaya, W., White, R. R., Popov, V. N., Vijg, J., & Maslov, A. Y. (2013) · BioTechniques · doi:10.2144/000114077 · Cited by 76 · see citing works

Genome-scale modeling and in silico analysis of mouse cell metabolic network

Selvarasu, S., Karimi, I. A., Ghim, G.-H., & Lee, D. (2009) · Molecular BioSystems · doi:10.1039/b912865d · Cited by 75 · see citing works

An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts

Shen, X., Shen, S., Li, J., Hu, Q., Nie, L., Tu, C., Wang, X., Orsburn, B. C., Wang, J., & Qu, J. (2017) · Journal of Proteome Research · doi:10.1021/acs.jproteome.7b00061 · Cited by 75 · see citing works

Large scale microarray profiling and coexpression network analysis of CHO cells identifies transcriptional modules associated with growth and productivity

Clarke, C., Doolan, P., Barron, N., Meleady, P., O’Sullivan, F., Gammell, P., Melville, M. W., Leonard, M. W., & CLYNES, M. M. (2011) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2011.07.011 · Cited by 74 · see citing works

Dynamic DNA Methylation and Histone Modifications Contribute to Lentiviral Transgene Silencing in Murine Embryonic Carcinoma Cells

He, J., Yang, Q. F., & Chang, L.-J. (2005) · Journal of Virology · doi:10.1128/jvi.79.21.13497-13508.2005 · Cited by 72 · see citing works

NMR-based metabolomics of mammalian cell and tissue cultures

Aranı́bar, N., Borys, M., Mackin, N. A., Ly, V. T., Abu‐Absi, N. R., Abu-Absi, S. F., Niemitz, M., Schilling, B. M., Li, Z. J., Brock, B. J., et al. (2011) · Journal of Biomolecular NMR · doi:10.1007/s10858-011-9490-8 · Cited by 70 · see citing works

High‐performance hybrid Orbitrap mass spectrometers for quantitative proteome analysis: Observations and implications

Williamson, J. C., Edwards, A. V. G., Verano‐Braga, T., Schwämmle, V., Kjeldsen, F., Jensen, O. N., & Larsen, M. R. (2016) · PROTEOMICS · doi:10.1002/pmic.201400545 · Cited by 70 · see citing works

Mechanisms underlying epigenetic and transcriptional heterogeneity in Chinese hamster ovary (CHO) cell lines

Veith, N., Ziehr, H., MacLeod, R. A. F., & Reamon-Buettner, S. M. (2016) · BMC Biotechnology · doi:10.1186/s12896-016-0238-0 · Cited by 68 · see citing works

The use of ‘Omics technology to rationally improve industrial mammalian cell line performance

Lewis, A. M., Abu‐Absi, N. R., Borys, M., & Li, Z. J. (2015) · Biotechnology and Bioengineering · doi:10.1002/bit.25673 · Cited by 67 · see citing works

Construction of BAC‐based physical map and analysis of chromosome rearrangement in chinese hamster ovary cell lines

Cao, Y., Kimura, S., Itoi, T., Honda, K., Ohtake, H., & Ōmasa, T. (2011) · Biotechnology and Bioengineering · doi:10.1002/bit.24347 · Cited by 67 · see citing works

MicroRNAs: tiny targets for engineering CHO cell phenotypes?

Barron, N., Sanchez, N., Kelly, P. S., & CLYNES, M. M. (2010) · Biotechnology Letters · doi:10.1007/s10529-010-0415-5 · Cited by 60 · see citing works

Cell line profiling to improve monoclonal antibody production

Kang, S., Ren, D., Xiao, G., Daris, K., Buck, L., Enyenihi, A. A., Zubarev, R. A., Bondarenko, P. V., & Deshpande, R. R. (2013) · Biotechnology and Bioengineering · doi:10.1002/bit.25141 · Cited by 60 · see citing works

Dynamic metabolic models of CHO cell cultures through minimal sets of elementary flux modes

Zamorano, F., Wouwer, A. V., Jungers, R. M., & Bastin, G. (2012) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2012.05.005 · Cited by 59 · see citing works

Simple Capillary Electrophoresis–Mass Spectrometry Method for Complex Glycan Analysis Using a Flow-Through Microvial Interface

Jayo, R. G., Thaysen-Andersen, M., Lindenburg, P. W., Haselberg, R., Hankemeier, T., Ramautar, R., & Chen, D. D. Y. (2014) · Analytical Chemistry · doi:10.1021/ac5010212 · Cited by 54 · see citing works

Identifying the CHO Secretome using Mucin-type O-Linked Glycosylation and Click-chemistry

Slade, P. G., Hajivandi, M., Bartel, C. M., & Gorfien, S. F. (2012) · Journal of Proteome Research · doi:10.1021/pr300810f · Cited by 51 · see citing works

Biosimilarity Versus Manufacturing Change: Two Distinct Concepts

Declerck, P. J., Rezk, M. F., & Rudd, P. M. (2015) · Pharmaceutical Research · doi:10.1007/s11095-015-1790-3 · Cited by 50 · see citing works

Optimizing eukaryotic cell hosts for protein production through systems biotechnology and genome‐scale modeling

Gutierrez, J. M., & Lewis, N. E. (2015) · Biotechnology Journal · doi:10.1002/biot.201400647 · Cited by 50 · see citing works

Databases and Associated Tools for Glycomics and Glycoproteomics

Lisacek, F., Mariethoz, J. A., Alocci, D., Rudd, P. M., Abrahams, J. L., Campbell, M. P., Packer, N. H., Ståhle, J., Widmalm, G., Mullen, E. H., et al. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-6493-2_18 · Cited by 49 · see citing works

Metabolomics profiling of extracellular metabolites in CHO-K1 cells cultured in different types of growth media

Saberi, S. E. M., Hashim, Y. Z. H.-Y., Mel, M., Amid, A., Raus, R. A., & Mohammed, V. P. (2012) · Cytotechnology · doi:10.1007/s10616-012-9508-4 · Cited by 48 · see citing works

Systems glycobiology for glycoengineering

Spahn, P. N., & Lewis, N. E. (2014) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2014.08.004 · Cited by 47 · see citing works

Systems Glycobiology: Integrating Glycogenomics, Glycoproteomics, Glycomics, and Other ‘Omics Data Sets to Characterize Cellular Glycosylation Processes

Bennun, S. V., Hızal, D. B., Heffner, K. M., Can, Ö., Zhang, H., & Betenbaugh, M. J. (2016) · Journal of Molecular Biology · doi:10.1016/j.jmb.2016.07.005 · Cited by 47 · see citing works

Compartment‐specific metabolomics for CHO reveals that ATP pools in mitochondria are much lower than in cytosol

Matuszczyk, J., Teleki, A., Pfizenmaier, J., & Takors, R. (2015) · Biotechnology Journal · doi:10.1002/biot.201500060 · Cited by 44 · see citing works

Systems-level modeling of cellular glycosylation reaction networks: O-linked glycan formation on natural selectin ligands

Liu, G., Marathe, D. D., Matta, K. L., & Neelamegham, S. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn515 · Cited by 44 · see citing works

A framework to quantify karyotype variation associated with CHO cell line instability at a single‐cell level

Baik, J. Y., & Lee, K. H. (2016) · Biotechnology and Bioengineering · doi:10.1002/bit.26231 · Cited by 44 · see citing works

The DNA methylation landscape of Chinese hamster ovary (CHO) DP-12 cells

Wippermann, A., Rupp, O., Brinkrolf, K., Hoffrogge, R., & Noll, T. (2015) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2015.02.014 · Cited by 42 · see citing works

Unstable expression of recombinant antibody during long-term culture of CHO cells is accompanied by histone H3 hypoacetylation

Paredes, V., Park, J., Jeong, Y., Yoon, J., & Baek, K. (2013) · Biotechnology Letters · doi:10.1007/s10529-013-1168-8 · Cited by 42 · see citing works

Using Gene Essentiality and Synthetic Lethality Information to Correct Yeast and CHO Cell Genome-Scale Models

Chowdhury, R., Chowdhury, A., & Maranas, C. D. (2015) · Metabolites · doi:10.3390/metabo5040536 · Cited by 42 · see citing works

Analysis of Monoclonal Antibody Sequence and Post-translational Modifications by Time-controlled Proteolysis and Tandem Mass Spectrometry

Zhang, L., English, A. M., Bai, D. L., Ugrin, S. A., Shabanowitz, J., Ross, M. M., Hunt, D. F., & Wang, W. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o115.056721 · Cited by 42 · see citing works

High-Throughput Lipidomic and Transcriptomic Analysis To Compare SP2/0, CHO, and HEK-293 Mammalian Cell Lines

Zhang, Y., Baycin‐Hizal, D., Kumar, A., Priola, J. J., Bahri, M., Heffner, K. M., Wang, M., Han, X., Bowen, M. A., & Betenbaugh, M. J. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.6b02984 · Cited by 42 · see citing works

Metabolic analysis of the synthesis of high levels of intracellular human SOD in Saccharomyces cerevisiae rhSOD 2060 411 SGA122

González, R., Andrews, B. A., Molitor, J., & Asenjo, J. A. (2003) · Biotechnology and Bioengineering · doi:10.1002/bit.10556 · Cited by 42 · see citing works

High-throughput profiling of nucleotides and nucleotide sugars to evaluate their impact on antibody N-glycosylation

Villiger, T. K., Steinhoff, R., Ivarsson, M., Solacroup, T., Stettler, M., Broly, H., Krismer, J., Pabst, M., Zenobi, R., Morbidelli, M., et al. (2016) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2016.04.039 · Cited by 41 · see citing works

Quantitative feature extraction from the Chinese hamster ovary bioprocess bibliome using a novel meta-analysis workflow

Golabgir, A., Gutierrez, J. M., Hefzi, H., Li, S., Palsson, B. Ø., Herwig, C., & Lewis, N. E. (2016) · Biotechnology Advances · doi:10.1016/j.biotechadv.2016.02.011 · Cited by 40 · see citing works

The Genetics of Somatic Mammalian Cells,

Puck, T. T. (1957) · Advances in biological and medical physics · doi:10.1016/b978-1-4832-3111-2.50006-7 · Cited by 40 · see citing works

Safer, Silencing-Resistant Lentiviral Vectors: Optimization of the Ubiquitous Chromatin-Opening Element through Elimination of Aberrant Splicing

Knight, S., Zhang, F., Müller-Kuller, U., Bokhoven, M., Gupta, A., Broughton, T., Sha, S., Antoniou, M. N., Brendel, C., Grez, M., et al. (2012) · Journal of Virology · doi:10.1128/jvi.00485-12 · Cited by 39 · see citing works

Combining mechanistic and data‐driven approaches to gain process knowledge on the control of the metabolic shift to lactate uptake in a fed‐batch CHO process

Zalai, D., Koczka, K., Párta, L., Wechselberger, P., Klein, T., & Herwig, C. (2015) · Biotechnology Progress · doi:10.1002/btpr.2179 · Cited by 39 · see citing works

Proteomic differences in recombinant CHO cells producing two similar antibody fragments

Sommeregger, W., Mayrhofer, P., Steinfellner, W., Reinhart, D., Henry, M. A., CLYNES, M. M., Meleady, P., & Kunert, R. (2016) · Biotechnology and Bioengineering · doi:10.1002/bit.25957 · Cited by 39 · see citing works

Global insights into the Chinese hamster and CHO cell transcriptomes

Vishwanathan, N., Yongky, A., Johnson, K. C., Fu, H., Jacob, N. M., Le, H., Yusufi, F. N. K., Lee, D., & Hu, W. (2014) · Biotechnology and Bioengineering · doi:10.1002/bit.25513 · Cited by 36 · see citing works

Analysis of genetic variation and potential applications in genome-scale metabolic modeling

Cardoso, J. (2015) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2015.00013 · Cited by 34 · see citing works

Unraveling Biochemical Pathways Affected by Mitochondrial Dysfunctions Using Metabolomic Approaches

Demine, S., Reddy, N., Renard, P., Raes, M. J., & Arnould, T. (2014) · Metabolites · doi:10.3390/metabo4030831 · Cited by 34 · see citing works

Transcriptomic changes in CHO cells after adaptation to suspension growth in protein-free medium analysed by a species-specific microarray

Shridhar, S., Klanert, G., Auer, N., Hernandez-Lopez, I., Kańduła, M. M., Hackl, M., Grillari, J., Stralis‐Pavese, N., Kreil, D. P., & Borth, N. (2017) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2017.03.012 · Cited by 34 · see citing works

mQTL.NMR: An Integrated Suite for Genetic Mapping of Quantitative Variations of 1H NMR-Based Metabolic Profiles

Hedjazi, L., Gauguier, D., Zalloua, P., Nicholson, J. K., Dumas, M., & Cazier, J. (2015) · Analytical Chemistry · doi:10.1021/acs.analchem.5b00145 · Cited by 31 · see citing works

Accumulative gene integration into a pre-determined site using Cre/loxP

Obayashi, H., Kawabe, Y., Makitsubo, H., Watanabe, R., Kameyama, Y., Huang, S., Takenouchi, Y., Itô, A., & Kamihira, M. (2011) · Journal of Bioscience and Bioengineering · doi:10.1016/j.jbiosc.2011.10.027 · Cited by 30 · see citing works

Quantitative definition and monitoring of the host cell protein proteome using iTRAQ – a study of an industrial mAb producing CHO‐S cell line

Chiverton, L. M., Evans, C. A., Pandhal, J., Landels, A. R., Rees, B., Levison, P. R., Wright, P. C., & Smales, C. M. (2016) · Biotechnology Journal · doi:10.1002/biot.201500550 · Cited by 30 · see citing works

Strategies to Insulate Lentiviral Vector-Expressed Transgenes

Ramezani, A., & Hawley, R. G. (2009) · Methods in molecular biology · doi:10.1007/978-1-60761-533-0_5 · Cited by 29 · see citing works

Establishment of a CpG island microarray for analyses of genome-wide DNA methylation in Chinese hamster ovary cells

Wippermann, A., Klausing, S., Rupp, O., Albaum, S. P., Büntemeyer, H., Noll, T., & Hoffrogge, R. (2013) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-013-5282-2 · Cited by 28 · see citing works

Protein Quantitative Trait Loci Identify Novel Candidates Modulating Cellular Response to Chemotherapy

Stark, A. L., Hause, R. J., Gorsic, L. K., Antao, N. N., Wong, S. S., Chung, S. H., Gill, D., Im, H. K., Myers, J. L., White, K. P., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004192 · Cited by 28 · see citing works

An omics approach to rational feed

Blondeel, E. J. M., Ho, R., Schulze, S. F., Sokolenko, S., Guillemette, S. R., Slivac, I., Durocher, Y., Guillemette, J. G., McConkey, B. J., Chang, D., et al. (2016) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2016.07.027 · Cited by 27 · see citing works

Ultra-deep next generation mitochondrial genome sequencing reveals widespread heteroplasmy in Chinese hamster ovary cells

Kelly, P. S., Clarke, C., Costello, A., Monger, C., Meiller, J., Dhiman, H., Borth, N., Betenbaugh, M. J., CLYNES, M. M., & Barron, N. (2017) · Metabolic Engineering · doi:10.1016/j.ymben.2017.02.001 · Cited by 27 · see citing works

Transcriptomic analysis of clonal growth rate variation during CHO cell line development

Doolan, P., Clarke, C., Kinsella, P., Breen, L., Meleady, P., Leonard, M. W., Zhang, L., CLYNES, M. M., Aherne, S. T., & Barron, N. (2013) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2013.04.014 · Cited by 27 · see citing works

GlycoBase and autoGU: Resources for Interpreting HPLC-Glycan Data

Campbell, M. P., Royle, L., & Rudd, P. M. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-2343-4_2 · Cited by 27 · see citing works

Segmented linear modeling of CHO fed‐batch culture and its application to large scale production

Yahia, B. B., Gourévitch, B., Malphettes, L., & Heinzle, E. (2016) · Biotechnology and Bioengineering · doi:10.1002/bit.26214 · Cited by 26 · see citing works

Multiplexing N‐glycan analysis by DNA analyzer

Feng, H., Li, P., Rui, G., Stray, J. E., Khan, S. H., Chen, S.-M., & Li, S. F. Y. (2017) · Electrophoresis · doi:10.1002/elps.201600404 · Cited by 22 · see citing works

Evaluating regulatory elements of human cytomegalovirus major immediate early gene for enhancing transgene expression levels in CHO K1 and HEK293 cells

Mariati, Ng, Y. K., Chao, S., Yap, M. G. S., & Yang, Y. (2010) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2010.02.022 · Cited by 21 · see citing works

Protein reference mapping of dihydrofolate reductase‐deficient CHO DG44 cell lines using 2‐dimensional electrophoresis

Lee, J. S., Park, H. J., Kim, Y. H., & Lee, G. M. (2010) · PROTEOMICS · doi:10.1002/pmic.200900430 · Cited by 19 · see citing works

Towards next generation CHO cell biology: Bioinformatics methods for RNA‐Seq‐based expression profiling

Monger, C., Kelly, P. S., Gallagher, C., CLYNES, M. M., Barron, N., & Clarke, C. (2015) · Biotechnology Journal · doi:10.1002/biot.201500107 · Cited by 18 · see citing works

Quantitative Trait Loci Mapping of the Mouse Plasma Proteome (pQTL)

Holdt, L. M., von Delft, A., Nicolaou, A., Baumann, S., Kostrzewa, M., Thiery, J., & Teupser, D. (2013) · Genetics · doi:10.1534/genetics.112.143354 · Cited by 18 · see citing works

Metabolomics breaks the silence

Thomas, G. H. (2001) · Trends in Microbiology · doi:10.1016/s0966-842x(01)02010-8 · Cited by 18 · see citing works

Transcriptome study and identification of potential marker genes related to the stable expression of recombinant proteins in CHO clones

Jamnikar, U., Nikolić, P., Belic, A., Blas, M., Gaser, D., Francky, A., Laux, H., Blejec, A., Baebler, Š., & Gruden, K. (2015) · BMC Biotechnology · doi:10.1186/s12896-015-0218-9 · Cited by 16 · see citing works

A hybrid approach identifies metabolic signatures of high‐producers for chinese hamster ovary clone selection and process optimization

Popp, O., Müller, D., Didzus, K., Paul, W., Lipsmeier, F., Kirchner, F., Niklas, J., Mauch, K., & Beaucamp, N. (2016) · Biotechnology and Bioengineering · doi:10.1002/bit.25958 · Cited by 15 · see citing works

2D-DIGE screening of high-productive CHO cells under glucose limitation—Basic changes in the proteome equipment and hints for epigenetic effects

Wingens, M., Gätgens, J., Schmidt, A., Albaum, S. P., Büntemeyer, H., Noll, T., & Hoffrogge, R. (2015) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2015.01.005 · Cited by 14 · see citing works

An automated RNA‐Seq analysis pipeline to identify and visualize differentially expressed genes and pathways in CHO cells

Chen, C., Le, H., & Goudar, C. T. (2015) · Biotechnology Progress · doi:10.1002/btpr.2137 · Cited by 12 · see citing works

Rapid Mitochondrial DNA Isolation Method for Direct Sequencing

Quispe‐Tintaya, W., White, R. R., Popov, V. N., Vijg, J., & Maslov, A. Y. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-2257-4_9 · Cited by 12 · see citing works

CD28 stimulation regulates its association with N-ethylmaleimide-sensitive fusion protein and other proteins involved in vesicle sorting

Heller, M., Watts, J. D., & Aebersold, R. H. (2001) · PROTEOMICS · doi:10.1002/1615-9861(200101)1:1 · Cited by 11 · see citing works

Quantitative analysis of the supernatant from host and transfected CHO cells using iTRAQ 8‐plex technique

Zhu, G., Sun, L., Albanetti, T., Linkous, T., Larkin, C. J., Schoner, R. G., McGivney, J. B., & Dovic̀hi, N. J. (2016) · Biotechnology and Bioengineering · doi:10.1002/bit.25991 · Cited by 10 · see citing works

Transcriptomic variation between different Chinese hamster ovary cell lines

Blas, M., Francky, A., Jamnikar, U., Gaser, D., Baebler, Š., Blejec, A., & Gruden, K. (2015) · Biotechnology Letters · doi:10.1007/s10529-015-1850-0 · Cited by 6 · see citing works

ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data

González, S., Clavijo, B., Rivarola, M., Moreno, P., Fernández, P. D. C., Dopazo, J., & Paniego, N. B. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1494-2 · Cited by 6 · see citing works

Cell culture media for recombinant protein expression in chinese hamster ovary (CHO) cells: history, key components, and optimization strategies

Ritacco, F. V., Wu, Y., & Khetan, A. (2018) · Biotechnology Progress · doi:10.1002/btpr.2706 · Cited by 263 · see citing works

Mammalian cell culture for production of recombinant proteins: a review of the critical steps in their biomanufacturing

O’Flaherty, R., Bergin, A., Flampouri, E., Mota, L. M., Obaidi, I., Quigley, A., Xie, Y., & Butler, M. (2020) · Biotechnology Advances · doi:10.1016/j.biotechadv.2020.107552 · Cited by 232 · see citing works

Recent advances in CHO cell line development for recombinant protein production

Tihanyi, B., & Nyitray, L. (2020) · Drug Discovery Today Technologies · doi:10.1016/j.ddtec.2021.02.003 · Cited by 201 · see citing works

Recombinant Antibody Production in CHO and NS0 Cells: Differences and Similarities

Dhara, V. G., Naik, H. M., Majewska, N. I., & Betenbaugh, M. J. (2018) · BioDrugs · doi:10.1007/s40259-018-0319-9 · Cited by 96 · see citing works

Critical challenges and advances in recombinant adeno‐associated virus (rAAV) biomanufacturing

Fu, Q., Polanco, A., Lee, Y. S., & Yoon, S. (2023) · Biotechnology and Bioengineering · doi:10.1002/bit.28412 · Cited by 82 · see citing works

Recent advancements, challenges, and practical considerations in the mass spectrometry-based analytics of protein biotherapeutics: A viewpoint from the biosimilar industry

Háda, V., Bagdi, A., Bihari, Z., Timári, S. B., Fizil, Á., & Szántay, C. (2018) · Journal of Pharmaceutical and Biomedical Analysis · doi:10.1016/j.jpba.2018.08.024 · Cited by 61 · see citing works

Mechanistic modeling and applications for CHO cell culture development and production

Sha, S., Huang, Z., Wang, Z., & Yoon, S. (2018) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2018.08.010 · Cited by 61 · see citing works

Serum-Free Medium for Recombinant Protein Expression in Chinese Hamster Ovary Cells

Li, W., Fan, Z., Lin, Y., & Wang, T. (2021) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2021.646363 · Cited by 58 · see citing works

Perfusion culture of Chinese Hamster Ovary cells for bioprocessing applications

MacDonald, M. A., Nöbel, M., Roche Recinos, D., Martínez, V. S., Schulz, B. L., Howard, C. B., Baker, K., Shave, E., Lee, Y. Y., Marcellin, E., et al. (2022) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2021.1998821 · Cited by 55 · see citing works

Stable isotope labeling approaches for NMR characterization of glycoproteins using eukaryotic expression systems

Yanaka, S., Yagi, H., Yogo, R., Yagi‐Utsumi, M., & Kato, K. (2018) · Journal of Biomolecular NMR · doi:10.1007/s10858-018-0169-2 · Cited by 53 · see citing works

Epigenetic regulation of gene expression in Chinese Hamster Ovary cells in response to the changing environment of a batch culture

Hernandez, I., Dhiman, H., Klanert, G., Jadhav, V., Auer, N., Hanscho, M., Baumann, M., Esteve‐Codina, A., Dabad, M., Gómez‐Garrido, J., et al. (2018) · Biotechnology and Bioengineering · doi:10.1002/bit.26891 · Cited by 52 · see citing works

The emerging role of cellular post-translational modifications in modulating growth and productivity of recombinant Chinese hamster ovary cells

Bryan, L. L. K., CLYNES, M. M., & Meleady, P. (2021) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107757 · Cited by 47 · see citing works

Genetic engineering approaches to improve posttranslational modification of biopharmaceuticals in different production platforms

Amann, T., Schmieder, V., Faustrup Kildegaard, H., Borth, N., & Andersen, M. R. (2019) · Biotechnology and Bioengineering · doi:10.1002/bit.27101 · Cited by 46 · see citing works

Recombinant therapeutic proteins degradation and overcoming strategies in CHO cells

Geng, S., Zhao, X., Zhang, X., Zhang, J., Mi, C., & Wang, T. (2024) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-024-13008-6 · Cited by 41 · see citing works

Glycoengineering Chinese hamster ovary cells: a short history

Donini, R., Haslam, S. M., & Kontoravdi, C. (2021) · Biochemical Society Transactions · doi:10.1042/bst20200840 · Cited by 37 · see citing works

Proteomic Landscape of Adeno-Associated Virus (AAV)-Producing HEK293 Cells

Strasser, L., Boi, S., Guapo, F., Donohue, N., Barron, N., Rainbow-Fletcher, A., & Bones, J. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222111499 · Cited by 33 · see citing works

Nutrient supplementation strategy improves cell concentration and longevity, monoclonal antibody production and lactate metabolism of Chinese hamster ovary cells

Pérez-Rodriguez, S., Ramírez-Lira, M. D. J., Trujillo-Roldán, M. A., & Valdez-Cruz, N. A. (2020) · Bioengineered · doi:10.1080/21655979.2020.1744266 · Cited by 32 · see citing works

The Expression Pattern of the Phosphoproteome Is Significantly Changed During the Growth Phases of Recombinant CHO Cell Culture

Kaushik, P., Henry, M. A., CLYNES, M. M., & Meleady, P. (2018) · Biotechnology Journal · doi:10.1002/biot.201700221 · Cited by 32 · see citing works

Using Metabolomics to Identify Cell Line-Independent Indicators of Growth Inhibition for Chinese Hamster Ovary Cell-Based Bioprocesses

Alden, N., Raju, R., McElearney, K., Lambropoulos, J., Kshirsagar, R., Gilbert, A., & Lee, K. (2020) · Metabolites · doi:10.3390/metabo10050199 · Cited by 32 · see citing works

A Metabolomics Approach to Increasing Chinese Hamster Ovary (CHO) Cell Productivity

Yao, G., Aron, K. L., Borys, M., Li, Z. J., Pendse, G., & Lee, K. (2021) · Metabolites · doi:10.3390/metabo11120823 · Cited by 29 · see citing works

The use of site-specific recombination and cassette exchange technologies for monoclonal antibody production in Chinese Hamster ovary cells: retrospective analysis and future directions

Srirangan, K., Loignon, M., & Durocher, Y. (2020) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2020.1768043 · Cited by 29 · see citing works

How to train your cell - Towards controlling phenotypes by harnessing the epigenome of Chinese hamster ovary production cell lines

Marx, N., Eisenhut, P., Weinguny, M., Klanert, G., & Borth, N. (2022) · Biotechnology Advances · doi:10.1016/j.biotechadv.2022.107924 · Cited by 29 · see citing works

Data-driven and model-guided systematic framework for media development in CHO cell culture

Hong, J. K., Choi, D., Park, S., Silberberg, Y. R., Shozui, F., Nakamura, E., Kayahara, T., & Lee, D. (2022) · Metabolic Engineering · doi:10.1016/j.ymben.2022.07.003 · Cited by 26 · see citing works

Metabolic trends of Chinese hamster ovary cells in biopharmaceutical production under batch and fed‐batch conditions

Rish, A. J., Drennen, J. K., & Anderson, C. A. (2021) · Biotechnology Progress · doi:10.1002/btpr.3220 · Cited by 25 · see citing works

Generation of reference cell lines, media, and a process platform for CHO cell biomanufacturing

Cordova, L. T., Dahodwala, H., Elliott, K. S., Baik, J., Odenewelder, D. C., Nmagu, D., Skelton, B. A., Uy, L., Klaubert, S. R., Synoground, B. F., et al. (2022) · Biotechnology and Bioengineering · doi:10.1002/bit.28290 · Cited by 25 · see citing works

Improved secretion of glycoproteins using an N-glycan-restricted passport sequence tag recognized by cargo receptor

Yagi, H., Yagi‐Utsumi, M., Honda, R., Ohta, Y., Saito, T., Nishio, M., Ninagawa, S., Suzuki, K., Anzai, T., Kamiya, Y., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15192-1 · Cited by 25 · see citing works

Increased growth rate and productivity following stable depletion of miR-7 in a mAb producing CHO cell line causes an increase in proteins associated with the Akt pathway and ribosome biogenesis

Coleman, O., Suda, S., Meiller, J., Henry, M. A., Riedl, M., Barron, N., CLYNES, M. M., & Meleady, P. (2019) · Journal of Proteomics · doi:10.1016/j.jprot.2019.01.003 · Cited by 21 · see citing works

Restoration of DNA repair mitigates genome instability and increases productivity of Chinese hamster ovary cells

Spahn, P. N., Zhang, X., Hu, Q., Lu, H., Hamaker, N. K., Hefzi, H., Li, S., Kuo, C., Huang, Y., Lee, J. C., et al. (2021) · Biotechnology and Bioengineering · doi:10.1002/bit.28016 · Cited by 21 · see citing works

Identifying metabolic features and engineering targets for productivity improvement in CHO cells by integrated transcriptomics and genome-scale metabolic model

Huang, Z., & Yoon, S. (2020) · Biochemical Engineering Journal · doi:10.1016/j.bej.2020.107624 · Cited by 20 · see citing works

Combining lipoic acid to methylene blue reduces the Warburg effect in CHO cells: From TCA cycle activation to enhancing monoclonal antibody production

Montégut, L., Martínez-Basilio, P. C., Moreira, J. D. V., Schwartz, L. H., & Jolicœur, M. (2020) · PLoS ONE · doi:10.1371/journal.pone.0231770 · Cited by 19 · see citing works

Proteogenomic Annotation of Chinese Hamsters Reveals Extensive Novel Translation Events and Endogenous Retroviral Elements

Li, S., Cha, S. W., Heffner, K., Hızal, D. B., Bowen, M. A., Chaerkady, R., Cole, R. N., Tejwani, V., Kaushik, P., Henry, M. A., et al. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00935 · Cited by 18 · see citing works

Proteomic Profiling of IgG1 Producing CHO Cells Using LC/LC-SPS-MS3: The Effects of Bioprocessing Conditions on Productivity and Product Quality

Strasser, L., Farrell, A., Ho, J. T. C., Scheffler, K., Cook, K., Pankert, P., Mowlds, P., Viner, R., Karger, B. L., & Bones, J. (2021) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2021.569045 · Cited by 17 · see citing works

Gene editing in CHO cells to prevent proteolysis and enhance glycosylation: Production of HIV envelope proteins as vaccine immunogens

Li, S. W., Wright, M., Healey, J. F., Hutchinson, J. M., O’Rourke, S. M., Mesa, K. A., Lollar, P., & Berman, P. W. (2020) · PLoS ONE · doi:10.1371/journal.pone.0233866 · Cited by 17 · see citing works

De novo assembly and annotation of the CHOZN® GS −/− genome supports high‐throughput genome‐scale screening

Kretzmer, C., Narasimhan, R. L., Lal, R. D., Balassi, V., Ravellette, J., Manjunath, A. K. K., Koshy, J. J., Viano, M., Torre, S., Zanda, V. M., et al. (2022) · Biotechnology and Bioengineering · doi:10.1002/bit.28226 · Cited by 15 · see citing works

Proteomics insight into the production of monoclonal antibody

Xu, N., Ou, J., Si, Y., Goh, K. Y., Flanigan, D. D., Han, X., Yang, Y., Yang, S., Zhou, L., & Liu, X. (2019) · Biochemical Engineering Journal · doi:10.1016/j.bej.2019.02.022 · Cited by 15 · see citing works

Cell culture bioprocessing — the road taken and the path forward

O’Brien, S. A., & Hu, W. (2020) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2020.100663 · Cited by 15 · see citing works

CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines

Lin, D., Yalamanchili, H. B., Zhang, X., Lewis, N. E., Alves, C. S., de Groot, J. C. W., Arnsdorf, J., Bjørn, S. P., Wulff, T., Voldborg, B. G. R., et al. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008498 · Cited by 15 · see citing works

Wheels turning: CHO cell modeling moves into a digital biomanufacturing era

Ranpura, S. A., Maralingannavar, V., Gheorghe, A.-G., Ma, E., Morrissey, J., Betenbaugh, M. J., & Demirhan, D. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.06.035 · Cited by 13 · see citing works

The potential of emerging sub-omics technologies for CHO cell engineering

Jerabek, T., Keysberg, C., & Otte, K. (2022) · Biotechnology Advances · doi:10.1016/j.biotechadv.2022.107978 · Cited by 14 · see citing works

Effects and mechanisms of animal-free hydrolysates on recombination protein yields in CHO cells

Du, Q.-J., Zhang, X., Wang, T., & Wang, X. (2022) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-022-12229-x · Cited by 14 · see citing works

Cystine and tyrosine feed reduces oxidative and ER stress in CHO cells

Shibafuji, Y., Nagao, N., & Yohda, M. (2023) · Biotechnology Journal · doi:10.1002/biot.202200638 · Cited by 13 · see citing works

‘Omics driven discoveries of gene targets for apoptosis attenuation in CHO cells

Orellana, C. A., Martínez, V. S., MacDonald, M. A., Henry, M. N., Gillard, M., Gray, P. P., Nielsen, L. K., Mahler, S. M., & Marcellin, E. (2020) · Biotechnology and Bioengineering · doi:10.1002/bit.27548 · Cited by 13 · see citing works

High throughput, efficacious gene editing & genome surveillance in Chinese hamster ovary cells

Huhn, S. C., Ou, Y., Kumar, A., Liu, R., & Du, Z. (2019) · PLoS ONE · doi:10.1371/journal.pone.0218653 · Cited by 13 · see citing works

LncRNA analysis of mAb producing CHO clones reveals marker and engineering potential

Novak, N., Baumann, M., Friss, A. F., Cairns, V. R., DeMaria, C., & Borth, N. (2023) · Metabolic Engineering · doi:10.1016/j.ymben.2023.05.003 · Cited by 12 · see citing works

Removal of Cell Clusters from Cho Suspension Cultures Based on Large-Particle Trapping Effect in Spiral Inertial Microfluidics

Kwon, T., Jeon, H., Hamel, J. P., & Han, J. (2023) · Separation and Purification Technology · doi:10.1016/j.seppur.2023.125162 · Cited by 12 · see citing works

From Observational to Actionable: Rethinking Omics in Biologics Production

Masson, H. O., Karottki, K. J. L. C., Tat, J., Hefzi, H., & Lewis, N. E. (2023) · Trends in biotechnology · doi:10.1016/j.tibtech.2023.03.009 · Cited by 11 · see citing works

In pursuit of a minimal CHO genome: Establishment of large-scale genome deletions

Jerabek, T., Weiß, L., Fahrion, H., Zeh, N., Raab, N., Lindner, B., Fischer, S., & Otte, K. (2023) · New Biotechnology · doi:10.1016/j.nbt.2023.12.007 · Cited by 10 · see citing works

A pooled CRISPR/AsCpf1 screen using paired gRNAs to induce genomic deletions in Chinese hamster ovary cells

Schmieder, V., Novak, N., Dhiman, H., Ly, N. N., Serafimova, E., Klanert, G., Baumann, M., Kildegaard, H. F., & Borth, N. (2021) · Biotechnology Reports · doi:10.1016/j.btre.2021.e00649 · Cited by 10 · see citing works

Recombinant antibodies aggregation and overcoming strategies in CHO cells

Xu, T., Zhang, J., Wang, T., & Wang, X. (2022) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-022-11977-0 · Cited by 10 · see citing works

Process intensification in biopharmaceutical process development and production – an industrial perspective

Schaub, J., Ankenbauer, A., Habicher, T., Löffler, M., Maguire, N., Monteil, D. T., Püngel, S., Stepper, L., Stiefel, F., Thoma, J., et al. (2023) · Physical Sciences Reviews · doi:10.1515/psr-2022-0113 · Cited by 10 · see citing works

Enhancing recombinant protein and viral vector production in mammalian cells by targeting the YTHDF readers of N6‐methyladenosine in mRNA

Lao, N. T., & Barron, N. (2023) · Biotechnology Journal · doi:10.1002/biot.202200451 · Cited by 9 · see citing works

HEK-omics: The promise of omics to optimize HEK293 for recombinant adeno-associated virus (rAAV) gene therapy manufacturing

Gurazada, S. G. R., Kennedy, H. M., Braatz, R. D., Mehrman, S. J., Polson, S. W., & Rombel, I. T. (2025) · Biotechnology Advances · doi:10.1016/j.biotechadv.2024.108506 · Cited by 8 · see citing works

Spatial Proteomics Reveals Differences in the Cellular Architecture of Antibody-Producing CHO and Plasma Cell–Derived Cells

Kretz, R., Walter, L., Raab, N., Zeh, N., Gauges, R., Otte, K., Fischer, S., & Stoll, D. (2022) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2022.100278 · Cited by 8 · see citing works

A novel dynamic flux balance analysis for modeling CHO cell fed-batch cultures with pH and temperature shifts

Ghodba, A., Richelle, A., McCready, C., Ricardez‐Sandoval, L., & Budman, H. M. (2025) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2025.08.010 · Cited by 8 · see citing works

Validation and identification of reference genes in Chinese hamster ovary cells for Fc-fusion protein production

Ma, X., Zhang, L., Zhang, L., Wang, C., Guo, X., Yu, Y., Wang, L., Li, X., & Ma, N. (2020) · Experimental Biology and Medicine · doi:10.1177/1535370220914058 · Cited by 8 · see citing works

Comparative Analysis of HEK293 Genomic Variability

Smesnik, G., Virgolini, N., Toth, M., Dürauer, A., & Borth, N. (2025) · Biotechnology and Bioengineering · doi:10.1002/bit.70105 · Cited by 8 · see citing works

Low intensity mechanical signals promote proliferation in a cell-specific manner: Tailoring a non-drug strategy to enhance biomanufacturing yields

Chan, M. E., Ashdown, C. P., Strait, L., Pasumarthy, S., Hassan, A., Crimarco, S., Singh, C., Patel, V. S., Pagnotti, G. M., Khan, O., et al. (2024) · Mechanobiology in Medicine · doi:10.1016/j.mbm.2024.100080 · Cited by 7 · see citing works

Comparative RNA-Seq of Ten Phaeodactylum tricornutum Accessions: Unravelling Criteria for Robust Strain Selection from a Bioproduction Point of View

Toustou, C., Boulogne, I., Gonzalez, A., & Bardor, M. (2024) · Marine Drugs · doi:10.3390/md22080353 · Cited by 7 · see citing works

Anti-PD-L1 × anti-CD3 bispecific T-cell engager-armed T cells can overcome immunosuppression and redirect T cells to kill breast cancer cells expressing PD-L1

Luangwattananun, P., Sangsuwannukul, T., Supimon, K., Thuwajit, C., Chieochansin, T., Sa-nguanraksa, D., Samarnthai, N., O‐charoenrat, P., Junking, M., & Yenchitsomanus, P. (2023) · International Immunopharmacology · doi:10.1016/j.intimp.2023.111012 · Cited by 6 · see citing works

Optimization of the intron sequences combined with the CMV promoter increases recombinant protein expression in CHO cells

Xu, T., Wang, Y., Yuan, J.-J., Mi, C., Geng, S., Wang, X., & Wang, T. (2025) · Scientific Reports · doi:10.1038/s41598-025-87941-5 · Cited by 6 · see citing works

Accelerating biopharmaceutical cell line selection with label-free multimodal nonlinear optical microscopy and machine learning

Shi, J., Ho, A., Snyder, C. E., Chaney, E. J., Sorrells, J. E., Alex, A., Talaban, R. V., Spillman, D. R., Marjanović, M., Doan, M., et al. (2025) · Communications Biology · doi:10.1038/s42003-025-07596-w · Cited by 6 · see citing works

Omics and CRISPR in CHO bioproduction: a state-of-the-art review

Sorourian, S., Behzad‐Behbahani, A., Dehbidi, G. R., Zare, F., Farajnia, S., Najafi, H., & Safari, F. (2024) · Biotechnology and Bioprocess Engineering · doi:10.1007/s12257-024-00026-4 · Cited by 6 · see citing works

A proteomics approach to decipher a sticky CHO situation

Kumar, S., Kumar, A., Huhn, S. C., Devine, L. R., Cole, R. N., Du, Z., & Betenbaugh, M. J. (2022) · Biotechnology and Bioengineering · doi:10.1002/bit.28108 · Cited by 6 · see citing works

Evaluation of site-specific methylation of the CMV promoter and its role in CHO cell productivity of a recombinant monoclonal antibody

Dahodwala, H., Amenyah, S., Nicoletti, S., Henry, M. N., Lees‐Murdock, D. J., & Sharfstein, S. T. (2022) · Antibody Therapeutics · doi:10.1093/abt/tbac010 · Cited by 6 · see citing works

Ouantitative Proteomic Analysis of Cellular Responses to a Designed Amino Acid Feed in a Monoclonal Antibody Producing Chinese Hamster Ovary Cell Line

Torkashvand, F., Mahboudi, F., Vossoughi, M., Fatemi, E., Basri, S. M. M., Basri, S. M. M., & Vaziri, B. (2018) · Iranian Biomedical Journal · doi:10.29252/.22.6.385 · Cited by 6 · see citing works

Metabolomic characterization of monoclonal antibody‐producing Chinese hamster lung (CHL)‐YN cells in glucose‐controlled serum‐free fed‐batch operation

Sukwattananipaat, P., Kuroda, H., Yamano, N., & Ōmasa, T. (2024) · Biotechnology and Bioengineering · doi:10.1002/bit.28777 · Cited by 5 · see citing works

Exploitation of the ribosomal protein L10 R98S mutation to enhance recombinant protein production in mammalian cells

Verbelen, B., Girardi, T., Sulima, S. O., Vereecke, S., Verstraete, P., Verbeeck, J., Royaert, J., Cinque, S., Montanaro, L., Penzo, M., et al. (2022) · Engineering in Life Sciences · doi:10.1002/elsc.202100124 · Cited by 4 · see citing works

Creation and filtering of a recurrent spectral library of CHO cell metabolites and media components

Telu, K. H., Marupaka, R., Andriamaharavo, N. R., Simón‐Manso, Y., Liang, Y., Mirokhin, Y. A., Bukhari, T. H., Preston, R. J., Kashi, L., Kelman, Z., et al. (2021) · Biotechnology and Bioengineering · doi:10.1002/bit.27661 · Cited by 4 · see citing works

Rapid Antibody Glycoengineering in CHO Cells Via RNA Interference and CGE-LIF N-Glycomics

Kotidis, P., Marbiah, M. M., Donini, R., Gómez, I. A., del Val, I. J., Haslam, S. M., Polizzi, K. M., & Kontoravdi, C. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1685-7_7 · Cited by 4 · see citing works

Synthetic enhancers including TFREs improve transgene expression in CHO cells

Liu, H.-N., Wang, X.-Y., Zou, Y., Wu, W.-B., Lin, Y., Ji, B.-Y., & Wang, T. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26901 · Cited by 4 · see citing works

La bioproduction des anticorps monoclonaux

Joubert, S., Dodelet, V. C., Béliard, R., & Durocher, Y. (2019) · médecine/sciences · doi:10.1051/medsci/2019219 · Cited by 4 · see citing works

Meta-analysis of RNA-Seq datasets allows a better understanding of P. tricornutum cellular biology, a requirement to improve the production of Biologics

Boulogne, I., Toustou, C., & Bardor, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-87620-5 · Cited by 3 · see citing works

Biotherapeutic Products, Cellular Factories, and Multiomics Integration in Metabolic Engineering

Anh, N. H., Min, J. E., Kim, S. J., & Long, N. P. (2020) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2020.0112 · Cited by 3 · see citing works

Automated instant labeling chemistry workflow for real-time monitoring of monoclonal antibody N -glycosylation

Gyorgypal, A., Potter, O. G., Chaturvedi, A., Powers, D. N., & Chundawat, S. P. S. (2023) · Reaction Chemistry & Engineering · doi:10.1039/d2re00568a · Cited by 3 · see citing works

Novel Data‐Driven Mechanistic Modeling of Untargeted Metabolome Data Reveals Feed Component Effects in CHO Cell Bioprocess Using Column Generation‐Based EFMs

Mäkinen, M., Zacharouli, M., Särnlund, S., Jiang, Y., & Chotteau, V. (2025) · Biotechnology Journal · doi:10.1002/biot.70008 · Cited by 3 · see citing works

Selection of high-producing clones by a relative titer predictive model using image analysis

Tao, W., Ahmed, W., Guo, M., Mohsin, A., Wu, B. F., & Li, R. (2021) · Annals of Translational Medicine · doi:10.21037/atm-21-2822 · Cited by 3 · see citing works

Biological systems for therapeutic protein production

Behera, B. K. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-18748-3.00004-4 · Cited by 2 · see citing works

Metabolic and Process Engineering to Control Glycan Structures for Biopharmaceuticals Produced in Cultured Mammalian Cells

Pranomphon, R., Tejwani, V., Dahodwala, H., Yamabhai, M., & Sharfstein, S. T. (2024) · Springer eBooks · doi:10.1007/978-3-031-62007-2_6 · Cited by 2 · see citing works

MediaAssist: database to support the design and optimization of cell culture medium

Thakar, K. J., Madhugiri, I., Gadgil, C. J., & Gadgil, M. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf982 · Cited by 2 · see citing works

Enhancing CHO by Systems Biotechnology

Borth, N., & Hu, W. (2018) · Biotechnology Journal · doi:10.1002/biot.201800077 · Cited by 2 · see citing works

Production of an anti-TNFα antibody in murine myeloma cells by perfusion culture

Bueno-Soler, A., Palacios-Oliva, J., Dorvignit, D., Quintana-Cantillo, A., Ramirez, Y., Tomas-Pompa, J. S., Solazabal-Armstrong, J. A., Ruiz-Ramirez, I., de Acosta, C. M., Boggiano-Ayo, T., et al. (2022) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-022-12052-4 · Cited by 1 · see citing works

Computational Efforts for the Development and Scale-up of Antibody-Producing Cell Culture Processes

Möller, J., & Pörtner, R. (2021) · Cell engineering · doi:10.1007/978-3-030-79871-0_15 · Cited by 1 · see citing works

Restoration of deficient DNA Repair Genes Mitigates Genome Instability and Increases Productivity of Chinese Hamster Ovary CellsPreprint

Spahn, P. N., Zhang, X., Hu, Q., Hamaker, N. K., Hefzi, H., Li, S., Kuo, C., Huang, Y., Lee, J., Ly, P., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.07.425558 · Cited by 1 · see citing works

Genomic Analysis And Engineering Of Chinese Hamster Ovary Cells For Improved Therapeutic Protein Production

O’Brien, S. A. (2020) · University of Minnesota Digital Conservancy (University of Minnesota)

Quantifying the Impact of Media Supplementation on Cell Growth and Product Yield in Chinese Hamster Ovary (CHO) Cells

Combe, M. (2020) · DalSpace (Dalhousie University)

沖縄における経済と企業経営に関する一考察(報告2,三大学共同シンポジュウム「地域づくりを考える」)

村上, 了. (2006)

An insight in the recent advancements in upstream processing for the formulation of media

Mahapatra, S., Singh, J., Verma, G., & Dwivedi, V. (2025) · AIP conference proceedings · doi:10.1063/5.0272847

STABILON enhances recombinant protein expression by mitigating proteolytic degradation in CHO cells

Li, J., Zhao, Y.-R., Sun, Q.-L., Han, Z., Wang, Y., Guo, X. H., Wang, T., & Wang, T. (2025) · Biochemical Engineering Journal · doi:10.1016/j.bej.2025.109988

Thrombomodulin is essential for recombinant Fc-fusion protein production in Chinese hamster ovary cells via multiple signaling pathways

Ma, X., Wang, N., Yan, Q., Li, S., Hu, G., Zhao, L., Xiao, R., Wang, M., & Ma, N. (2025) · Journal of Biological Engineering · doi:10.1186/s13036-025-00576-y

Comparative omics profiling reveals differences in biomass, energy production, and vesicle transport between CHO and fast-growing CHL-YN cells

Tsunoda, Y., Arishima, R., Boronina, T. N., Cole, R. N., Yamano, N., Betenbaugh, M. J., & Ōmasa, T. (2025) · Scientific Reports · doi:10.1038/s41598-025-23503-z

AntibodyPlus enzyme fusion protein cell line development using a novel multidimensional screening of productivity, purity, and specific activity

Wang, Y., Ma, L., Tam, W., Zheng, W., Lee, D., Yu, Q., & Feng, L. (2025) · Biochemical Engineering Journal · doi:10.1016/j.bej.2025.110030

STABILON Enhances Recombinant Protein Expression Stability and Underlying Mechanism in CHO CellsPreprint

Li, J., Zhao, Y., Sun, Q., Han, Z., Wang, Y., Guo, X. H., Wang, X., & Wang, T. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5475071

Whole-genome DNA methylation analysis of Chinese hamster ovary cells undergoing media adaptation

Roy, S., Sandhu, J. K., Huang, L., Wong, A., Wan, G. X., Lyko, F., Igwe, E. I., & Böhl, F. (2026) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2026.1716758

Compréhension de la croissance des cellules de mammifères dans des environnements contraints et mécanismes de sécrétion

Coulet, M. (2023) · doi:10.70675/d4a2360dz9a7ez4593z8c7dz3ef1deed9f73

Machine learning‐assisted clone selection for intensified cell culture processes

Wolnick, N., Schmitt, J., Siltanen, C. A., Armstrong, J., Hendrick, S., Atchley, A., & Downey, B. J. (2026) · Biotechnology Progress · doi:10.1002/btpr.88519

Biochemical and functional benchmarking of plant protein hydrolysates in serum-reduced adherent CHO-K1 cell culture

Compeau, F., Yalkin, G., Mortamais, P., & Lutomski, D. (2026) · Biotechnology Reports · doi:10.1016/j.btre.2026.e00968

Improving recombinant protein productivity in CHO cells via multi-omics data integration

Shen, Y., Shi, L., Zhang, X., Guo, X., Dong, W.-H., & Wang, T. (2026) · Bioresources and Bioprocessing · doi:10.1186/s40643-026-01123-3

Improving recombinant protein productivity in CHO cells via multi-omics data integration

Shen, Y., Shi, L., Zhang, X., Guo, X., Dong, W.-H., & Wang, T. (2026) · Bioresources and Bioprocessing · doi:10.1186/s40643-026-01123-3

Application of Multi-Omics Techniques for Bioprocess Design and Optimization in Chinese Hamster Ovary Cells

Farrell, A., McLoughlin, N., Milne, J. J., Marison, I. W., & Bones, J. (2014) · Journal of Proteome Research · doi:10.1021/pr500219b · Cited by 63 · see citing works

Application of System Biology Tools for the Design of Improved Chinese Hamster Ovary Cell Expression Platforms

(2016) · Journal of Bioprocessing & Biotechniques · doi:10.4172/2155-9821.1000284 · Cited by 4 · see citing works

The emerging CHO systems biology era: harnessing the ‘omics revolution for biotechnology

Kildegaard, H. F., Baycin-Hizal, D., Lewis, N. E., & Betenbaugh, M. J. (2013) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2013.02.007 · Cited by 165 · see citing works

REVIEW An ‘Omics Approach Towards CHO

Engineering, C., Datta, P., Linhardt, R. J., & Sharfstein, S. T. (2015)