ArticleMolecular systems biology2011
Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism.
Article in Molecular systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.
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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.
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Who cites it
107 citing papers in PubMed, 295 citations in OpenAlex.
- Integrative Proteomics and Genome-Scale Modeling Elucidate Metabolic Flux Shifts inInternational journal of molecular sciences · 2026Article
- Nutrient control enables metabolic reconstruction ofbioRxiv : the preprint server for biology · 2026Article
- Predictive Algal Systems Biology: Integrating Omics, Genome-Scale Metabolic Models, and Machine Learning.Bioengineering (Basel, Switzerland) · 2026Review
- Constraint-based metabolic modeling reveals metabolic properties underpinning the unprecedented growth of Chlorella ohadii.The New phytologist · 2025Article
- Unveiling organ-specific metabolism ofProceedings of the National Academy of Sciences of the United States of America · 2025Article
- BioModTool: from biomass composition data to structured biomass objective functions for genome-scale metabolic models.Bioinformatics advances · 2025Article
- Charting the state of GEMs in microalgae: progress, challenges, and innovations.Frontiers in plant science · 2025Review
- Mixotrophic growth of a ubiquitous marine diatom.Science advances · 2024Article
- Proteomics and constraint-based modelling reveal enzyme kinetic properties of Chlamydomonas reinhardtii on a genome scale.Nature communications · 2023Article
- The Special and General Mechanism of Cyanobacterial Harmful Algal Blooms.Microorganisms · 2023Review
- Optimization of nutrient utilization efficiency and productivity for algal cultures under light and dark cycles using genome-scale model process control.NPJ systems biology and applications · 2023Article
- Microalgal co-cultivation -recent methods, trends in omic-studies, applications, and future challenges.Frontiers in bioengineering and biotechnology · 2023Review
- Metabolic network reconstruction ofFrontiers in microbiology · 2023Review
- Integration of physiologically relevant photosynthetic energy flows into whole genome models of light-driven metabolism.The Plant journal : for cell and molecular biology · 2022Article
- Review
- Data Management and Modeling in Plant Biology.Frontiers in plant science · 2021Review
- Article
- Modeling of nitrogen fixation and polymer production in the heterotrophic diazotrophMetabolic engineering communications · 2020Article
- Introns mediate post-transcriptional enhancement of nuclear gene expression in the green microalga Chlamydomonas reinhardtii.PLoS genetics · 2020Article
- Biochemical Characteristics and a Genome-Scale Metabolic Model of an Indian Euryhaline Cyanobacterium with High Polyglucan Content.Metabolites · 2020Article
47 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology.
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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.