ReviewTrends in biotechnology2024
Driving towards digital biomanufacturing by CHO genome-scale models.
Review in Trends in biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Highly multiplexed mammalian metabolic engineering with a shotgun approach.Nature biotechnology · 2026Article
- Improving recombinant protein productivity in CHO cells via multi-omics data integration.Bioresources and bioprocessing · 2026Review
- Causal AI digital twin for bioprocess bottleneck diagnosis via metabolic flexibility and rigidification maps.iScience · 2026Article
- Toward a 4D genome annotation of CHO cells for biomanufacturing.Trends in biotechnology · 2026Review
- An enzyme-specific protein language model for catalytic property prediction.Nature communications · 2026Article
- A community reconstruction of Chinese hamster metabolism and structural systems biology elucidate metabolic rewiring in lactate-free CHO cells.Cell systems · 2026Article
- Systematic data-driven genome-scale metabolic model reduction for bioprocess modeling: CHO culture case study.NPJ systems biology and applications · 2026Article
- Transcriptome-driven constraint-based modelling reveals metabolic targets for ovarian cancer.Cancer & metabolism · 2026Article
- Exploring CHO cell stability during prolonged passaging via eXplainable AI driven flux balance analysis.NPJ systems biology and applications · 2026Article
- Improving governance in the age of synthetic biology, artificial intelligence, and diverging threats.Frontiers in bioengineering and biotechnology · 2026Article
- A Hybrid Modeling Framework for Predictive Digital Twins of CHO Cell Culture.Computational and structural biotechnology journal · 2026Article
- A reconstruction of the mammalian secretory pathway identifies mechanisms regulating antibody production.Cell systems · 2025Article
- Redefining media blending mathematically: a systematic approach for screening of medium components.Applied microbiology and biotechnology · 2025Article
- AutoML-Driven Soft Sensors for Real-Time Monitoring of Amino Acids in Mammalian Perfusion Cultures.Biotechnology and bioengineering · 2025Article
- Deciphering the determinants of recombinant protein expression across the human secretome.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Flux Sampling Suggests Metabolic Signatures of High Antibody-Producing CHO Cells.Biotechnology and bioengineering · 2025Article
- Characterization and design of dipeptide media formulation for scalable therapeutic production.Applied microbiology and biotechnology · 2025Review
- Wheels turning: CHO cell modeling moves into a digital biomanufacturing era: Subtitle: CHO Metabolic Modeling.Computational and structural biotechnology journal · 2025Review
- Recent advances in culture medium design for enhanced production of monoclonal antibodies in CHO cells: A comparative study of machine learning and systems biology approaches.Biotechnology advancesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Genome-scale metabolic models (GEMs) of Chinese hamster ovary (CHO) cells are valuable for gaining mechanistic understanding of mammalian cell metabolism and cultures. We provide a comprehensive overview of past and present developments of CHO-GEMs and in silico methods within the flux balance analysis (FBA) framework, focusing on their practical utility in rational cell line development and bioprocess improvements. There are many opportunities for further augmenting the model coverage and establishing integrative models that account for different cellular processes and data for future applications. With supportive collaborative efforts by the research community, we envisage that CHO-GEMs will be crucial for the increasingly digitized and dynamically controlled bioprocessing pipelines, especially because they can be successfully deployed in conjunction with artificial intelligence (AI) and systems engineering algorithms.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.