公开(公告)号：US11790280B2

公开(公告)日：2023-10-17

申请号：US17378988

申请日：2021-07-19

Applicant: BROWN UNIVERSITY

Inventor： Brenda Rubenstein ,  Jacob Karl Rosenstein ,  Christopher Arcadia ,  Shui Ling Chen ,  Amanda Doris Dombroski ,  Joseph D. Geiser ,  Eamonn Kennedy ,  Eunsuk Kim ,  Kady M. Oakley ,  Sherief Reda ,  Christopher Rose ,  Jason Kelby Sello ,  Hokchhay Tann ,  Peter Weber

IPC: G06N99/00

CPC classification number: G06N99/007

Abstract: The invention provides methods for computing with chemicals by encoding digital data into a plurality of chemicals to obtain a dataset; translating the dataset into a chemical form; reading the data set; querying the dataset by performing an operation to obtain a perceptron; and analyzing the perceptron for identifying chemical structure and/or concentration of at least one of the chemicals, thereby developing a chemical computational language. The invention demonstrates a workflow for representing abstract data in synthetic metabolomes. Also presented are several demonstrations of kilobyte-scale image data sets stored in synthetic metabolomes, recovered at >99% accuracy.

公开(公告)号：US11093865B2

公开(公告)日：2021-08-17

申请号：US17253013

申请日：2019-06-20

Applicant: BROWN UNIVERSITY

Inventor： Brenda Rubenstein ,  Jacob Karl Rosenstein ,  Christopher Arcadia ,  Shui Ling Chen ,  Amanda Doris Dombroski ,  Joseph D. Geiser ,  Eamonn Kennedy ,  Eunsuk Kim ,  Kady M. Oakley ,  Sherief Reda ,  Christopher Rose ,  Jason Kelby Sello ,  Hokchhay Tann ,  Peter Weber

IPC: G06N99/00

Abstract: The invention provides methods for computing with chemicals by encoding digital data into a plurality of chemicals to obtain a dataset; translating the dataset into a chemical form; reading the data set; querying the dataset by performing an operation to obtain a perceptron; and analyzing the perceptron for identifying chemical structure and/or concentration of at least one of the chemicals, thereby developing a chemical computational language. The invention demonstrates a workflow for representing abstract data in synthetic metabolomes. Also presented are several demonstrations of kilobyte-scale image data sets stored in synthetic metabolomes, recovered at >99% accuracy.