Molecular computing approaches
Abstract
Molecular approaches exploit structural properties built deep into DNA by millions of years of evolution on Earth to code and/or extract some significant features from raw datasets for the purpose of extreme dimensionality reduction and solution efficiency. After describing the deep structure, it is leveraged to render several variations of this theme. They can be used obviously with genomic data, but perhaps surprisingly, with ordinary abiotic data just as well. Two major families of techniques of this kind are reviewed, namely genomic and pmeric coordinate systems for dimensionality reduction and data analysis.
Publication Title
Dimensionality Reduction in Data Science
Recommended Citation
Garzon, M., & Mainali, S. (2022). Molecular computing approaches. Dimensionality Reduction in Data Science, 145-167. https://doi.org/10.1007/978-3-031-05371-9_7
