SERS-based ssDNA composition analysis with inhomogeneous peak broadening and reservoir computing
Abstract
Surface-enhanced Raman spectroscopy employed in conjunction with post-processing machine learning methods is a promising technique for effective data analysis, allowing one to enhance the molecular and chemical composition analysis of information rich DNA molecules. In this work, we report on a room temperature inhomogeneous broadening as a function of the increased adenine concentration and employ this feature to develop one-dimensional and two dimensional chemical composition classification models of 200 long single stranded DNA sequences. Afterwards, we develop a reservoir computing chemical composition classification scheme of the same molecules and demonstrate enhanced performance that does not rely on manual feature identification.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 10, 2022
- Source ID
- 10.1063/5.0075528
Entities
People
- Phuong H L Nguyen
- Piya Pal
- Pulak Sarangi
- Shimon Rubin
- Yeshaiahu Fainman
Organizations
- ASML (United States)
- Defense Advanced Research Projects Agency
- National Science Foundation
- Office of Naval Research
- United States Department of Energy
- University of California, San Diego