Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning
We report a versatile platform based on an array of porous silicon (PSi) thin films that can identify analytes based on their physical and chemical properties without the use of specific capture agents. The ability of this system to reproducibly classify, quantify, and discriminate three proteins se...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Biosensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-6374/13/9/879 |
| _version_ | 1797581022845468672 |
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| author | Simon J. Ward Tengfei Cao Xiang Zhou Catie Chang Sharon M. Weiss |
| author_facet | Simon J. Ward Tengfei Cao Xiang Zhou Catie Chang Sharon M. Weiss |
| author_sort | Simon J. Ward |
| collection | DOAJ |
| description | We report a versatile platform based on an array of porous silicon (PSi) thin films that can identify analytes based on their physical and chemical properties without the use of specific capture agents. The ability of this system to reproducibly classify, quantify, and discriminate three proteins separately is demonstrated by probing the reflectance of PSi array elements with a unique combination of pore size and buffer pH, and by analyzing the optical signals using machine learning. Protein identification and discrimination are reported over a concentration range of two orders of magnitude. This work represents a significant first step towards a low-cost, simple, versatile, and robust sensor platform that is able to detect biomolecules without the added expense and limitations of using capture agents. |
| first_indexed | 2024-03-10T22:59:13Z |
| format | Article |
| id | doaj.art-4bf0ab8b5db94a7ab37dc9b9566c75a4 |
| institution | Directory Open Access Journal |
| issn | 2079-6374 |
| language | English |
| last_indexed | 2024-03-10T22:59:13Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biosensors |
| spelling | doaj.art-4bf0ab8b5db94a7ab37dc9b9566c75a42023-11-19T09:47:35ZengMDPI AGBiosensors2079-63742023-09-0113987910.3390/bios13090879Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine LearningSimon J. Ward0Tengfei Cao1Xiang Zhou2Catie Chang3Sharon M. Weiss4Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USAInterdisciplinary Material Science Program, Vanderbilt University, Nashville, TN 37235, USADepartment of Chemistry, Vanderbilt University, Nashville, TN 37235, USADepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USADepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USAWe report a versatile platform based on an array of porous silicon (PSi) thin films that can identify analytes based on their physical and chemical properties without the use of specific capture agents. The ability of this system to reproducibly classify, quantify, and discriminate three proteins separately is demonstrated by probing the reflectance of PSi array elements with a unique combination of pore size and buffer pH, and by analyzing the optical signals using machine learning. Protein identification and discrimination are reported over a concentration range of two orders of magnitude. This work represents a significant first step towards a low-cost, simple, versatile, and robust sensor platform that is able to detect biomolecules without the added expense and limitations of using capture agents.https://www.mdpi.com/2079-6374/13/9/879biosensingporous siliconsensor arraymachine learningdimensionality reductionpoint-of-care |
| spellingShingle | Simon J. Ward Tengfei Cao Xiang Zhou Catie Chang Sharon M. Weiss Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning Biosensors biosensing porous silicon sensor array machine learning dimensionality reduction point-of-care |
| title | Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning |
| title_full | Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning |
| title_fullStr | Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning |
| title_full_unstemmed | Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning |
| title_short | Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning |
| title_sort | protein identification and quantification using porous silicon arrays optical measurements and machine learning |
| topic | biosensing porous silicon sensor array machine learning dimensionality reduction point-of-care |
| url | https://www.mdpi.com/2079-6374/13/9/879 |
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