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Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning.

ABSTRACT: 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.

SUBMITTER: Ward SJ

PROVIDER: S-EPMC10526835 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning.

Ward Simon J SJ Cao Tengfei T Zhou Xiang X Chang Catie C Weiss Sharon M SM

Biosensors 20230909 9

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 ide ...[more]

PMID: 37754113

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