Academic Journal
Automating the amino acid identification in elliptical dichroism spectrometer with Machine Learning
| Τίτλος: | Automating the amino acid identification in elliptical dichroism spectrometer with Machine Learning |
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| Συγγραφείς: | Ridhanya Sree Balamurugan, Yusuf Asad, Tommy Gao, Dharmakeerthi Nawarathna, Umamaheswara Rao Tida, Dali Sun |
| Πηγή: | PLoS One PLoS ONE, Vol 20, Iss 1, p e0317130 (2025) |
| Στοιχεία εκδότη: | Public Library of Science (PLoS), 2025. |
| Έτος έκδοσης: | 2025 |
| Θεματικοί όροι: | Light, Dichroism, Science, Medical Biochemistry, Circular dichroism, Biochemistry, Absorption, Machine Learning, Automation, Machine learning, Methods, Chomatographic analysis, Amino Acids, Mass spectrometry, Circular dichroism/methods, Theory and Algorithms, Circular Dichroism, Methodology, and Proteins, Pharmacy and Pharmaceutical Sciences, Mechanization, Amino acids, Medicine, Health aspects, Peptides, Algorithms, Research Article |
| Περιγραφή: | Amino acid identification is crucial across various scientific disciplines, including biochemistry, pharmaceutical research, and medical diagnostics. However, traditional methods such as mass spectrometry require extensive sample preparation and are time-consuming, complex and costly. Therefore, this study presents a pioneering Machine Learning (ML) approach for automatic amino acid identification by utilizing the unique absorption profiles from an Elliptical Dichroism (ED) spectrometer. Advanced data preprocessing techniques and ML algorithms to learn patterns from the absorption profiles that distinguish different amino acids were investigated to prove the feasibility of this approach. The results show that ML can potentially revolutionize the amino acid analysis and detection paradigm. |
| Τύπος εγγράφου: | Article Other literature type |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | English |
| ISSN: | 1932-6203 |
| DOI: | 10.1371/journal.pone.0317130 |
| Σύνδεσμος πρόσβασης: | https://pubmed.ncbi.nlm.nih.gov/39823430 https://doaj.org/article/6669965921f5422ba8c7811b387cde3a |
| Rights: | CC BY URL: http://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
| Αριθμός Καταχώρησης: | edsair.doi.dedup.....f03fb0f1fc33e4dbdf92b7ce71044f97 |
| Βάση Δεδομένων: | OpenAIRE |
| ISSN: | 19326203 |
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| DOI: | 10.1371/journal.pone.0317130 |