John A. Morgan
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
Publications
111
Citations
4,972
Est. group size
~4
Recurring co-author estimate
Active years
53
Publishing since 1974
John A. Morgan's research focuses on understanding how plants, algae, and cyanobacteria manage their internal chemistry (metabolism), using computational and experimental methods to trace how molecules flow through metabolic pathways. This work supports applications like engineering microorganisms to produce useful compounds such as amino acids and biofuels. Some more recent work also touches on machine learning methods, including neural networks for solving mathematical equations and statistical approaches to experimental design.
Publication output was highest around 2017-2020 and has slowed considerably in recent years, averaging about 2 publications per year over the last 5 years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Deep Neural Network for Solving Differential Equations Motivated by Legendre-Galerkin Approximation
International Journal of Numerical Analysis and Modeling · 2024
- Metabolic flux analysis of secondary metabolism in plants
Metabolic Engineering Communications · 2020
- Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models
Annual Review of Plant Biology · 2020
- Combining Random Mutagenesis and Metabolic Engineering for Enhanced Tryptophan Production in <i>Synechocystis</i> sp. Strain PCC 6803
Applied and Environmental Microbiology · 2020
- Green Chemistry: The Oxidation of Benzaldehyde Using Atmospheric Oxygen and N-heterocyclic Carbenes as Catalysts
2020
- Combining isotopically non-stationary metabolic flux analysis with proteomics to unravel the regulation of the Calvin-Benson-Bassham cycle in Synechocystis sp. PCC 6803
Metabolic Engineering · 2019
- Cost-Aware Learning for Improved Identifiability with Multiple Experiments
2019
- Glycogen Synthesis and Metabolite Overflow Contribute to Energy Balancing in Cyanobacteria
Cell Reports · 2018
- On the Sample Complexity of Learning from a Sequence of Experiments.
arXiv (Cornell University) · 2018
- Overproduction of Aromatic Amino Acids from Cyanobacteria
Purdue e-Pubs (Purdue University) · 2018
- Cost-Aware Learning for Improved Identifiability with Multiple Experiments
arXiv (Cornell University) · 2018
- Decision letter: Effects of microcompartmentation on flux distribution and metabolic pools in Chlamydomonas reinhardtii chloroplasts
2018
- Cost-Aware Rademacher Complexity of Multiple Experiments
arXiv (Cornell University) · 2018
- Decision letter: Effects of microcompartmentation on flux distribution and metabolic pools in Chlamydomonas reinhardtii chloroplasts
2018
- Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii
PLoS ONE · 2017
- The Plant Journal×4
- Nature Communications×3
- Nature Chemical Biology×3
- Metabolic Engineering×3
- arXiv (Cornell University)×3
- Alekhya Govindaraju
Biochemistry, Genetics and Molecular Biology · Indiana University
- Doraiswami Ramkrishna
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- Birgit E. Alber
Biochemistry, Genetics and Molecular Biology · The Ohio State University
- Christopher Chukwudi Okonkwo
Biochemistry, Genetics and Molecular Biology · The Ohio State University
- James B. McKinlay
Biochemistry, Genetics and Molecular Biology · Indiana University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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