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The application of neural differential equations to enzymatic time-series
Thesis (MSc)--Stellenbosch University, 2025.
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| Format: | Thesis |
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Stellenbosch : Stellenbosch University
2025
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| _version_ | 1867613780582596608 |
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| access_status_str | Open Access |
| author | Heusdens, Danica Aimee |
| author2 | Rohwer, Johann |
| author_browse | Heusdens, Danica Aimee Rohwer, Johann |
| author_facet | Rohwer, Johann Heusdens, Danica Aimee |
| author_sort | Heusdens, Danica Aimee |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2025. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/132433 |
| institution | Stellenbosch University (South Africa) |
| last_indexed | 2026-06-10T12:41:35.119Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/132433 The application of neural differential equations to enzymatic time-series Heusdens, Danica Aimee Rohwer, Johann Stellenbosch University. Faculty of Science. Centre for Bioinformatics & Computational Biology. Enzymatic analysis Differential equations -- Data processing Neural networks (Computer science) -- Mathematical models Time-series analysis -- Data processing Saccharomyces cerevisiae Enzyme kinetics UCTD Thesis (MSc)--Stellenbosch University, 2025. Heusdens, D. A. 2025. The Application of Neural Differential Equations to Enzymatic Time-Series. Unpublished masters thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/1fb7a419-ca41-4aca-a096-aa7e4c0d8708 ENGLISH ABSTRACT: The aim of this thesis was to explore machine-learning models for parameter estimation in enzymatic systems, with focus on phosphoglycerate mutase (PGM) and enolase (ENO) in Saccharomyces cerevisiae. This thesis proposes a combination model of neural differential equations (NDE) and Hamiltonian Monte Carlo simulation (HMC). By utilizing time-series data obtained from the laboratory and processing it using the EnzymeML framework, this study demonstrated the combination of NDE-HMC and how it can enhance the accuracy of parameter estimation while reducing the computational demands compared to an HMC-only approach. This study employed the Catalax framework to train and validate the NDE, with the utilization of optimization algorithms such as L-BFGS and Nelder-Mead. The results show an improvement in computational efficiency and goodness of fit metrics for the NDE-HMC model compared to that of the HMC-only model. This thesis established a foundation for the utilization of machine-learning models to estimate enzyme kinetic parameters in biochemical reaction systems. AFRIKAANSE OPSOMMING: Geen opsomming beskikbaar. Masters 2025-06-06T12:34:07Z 2025-06-06T12:34:07Z 2025-03 Thesis https://scholar.sun.ac.za/handle/10019.1/132433 Stellenbosch University viii, 74 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Enzymatic analysis Differential equations -- Data processing Neural networks (Computer science) -- Mathematical models Time-series analysis -- Data processing Saccharomyces cerevisiae Enzyme kinetics UCTD Heusdens, Danica Aimee The application of neural differential equations to enzymatic time-series |
| title | The application of neural differential equations to enzymatic time-series |
| title_full | The application of neural differential equations to enzymatic time-series |
| title_fullStr | The application of neural differential equations to enzymatic time-series |
| title_full_unstemmed | The application of neural differential equations to enzymatic time-series |
| title_short | The application of neural differential equations to enzymatic time-series |
| title_sort | application of neural differential equations to enzymatic time series |
| topic | Enzymatic analysis Differential equations -- Data processing Neural networks (Computer science) -- Mathematical models Time-series analysis -- Data processing Saccharomyces cerevisiae Enzyme kinetics UCTD |
| url | https://scholar.sun.ac.za/handle/10019.1/132433 |
| work_keys_str_mv | AT heusdensdanicaaimee theapplicationofneuraldifferentialequationstoenzymatictimeseries AT heusdensdanicaaimee applicationofneuraldifferentialequationstoenzymatictimeseries |