Agnostic material classification using differential de Bruijn graphs of DNA imprints
Cox, R. M.; Ansari, Z. T.; Johnson, C. D.; Marcotte, E. M.; Ellington, A.; Bhadra, S.
Show abstract
The wide variety of physical and chemical properties in materials makes the study of unknown substances challenging. We have previously proposed a theoretical framework for agnostic material characterization based on using nucleic acid imprints of the materials and then analyzing material-specific patterns of derived sequences. Here we demonstrate an experimental and computational pipeline that can agnostically identify and distinguish varied materials based on DNA k-mer imprints and validate the ability of these imprints to distinguish closely related materials. This work lays the foundation for expansion of purely agnostic sensing technologies for the unbiased characterization and categorization of a much wider variety of biotic and abiotic materials.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.