TY - JOUR
T1 - Nonlinear manipulation and analysis of large DNA datasets
AU - Cui, Meiying
AU - Zhao, Xueping
AU - Reddavide, Francesco V.
AU - Gaillez, Michelle Patino
AU - Heiden, Stephan
AU - Mannocci, Luca
AU - Thompson, Michael
AU - Zhang, Yixin
N1 - Publisher Copyright:
© 2022 The Author(s).
PY - 2022/8/26
Y1 - 2022/8/26
N2 - Information processing functions are essential for organisms to perceive and react to their complex environment, and for humans to analyze and rationalize them. While our brain is extraordinary at processing complex information, winner-take-all, as a type of biased competition is one of the simplest models of lateral inhibition and competition among biological neurons. It has been implemented as DNA-based neural networks, for example, to mimic pattern recognition. However, the utility of DNA-based computation in information processing for real biotechnological applications remains to be demonstrated. In this paper, a biased competition method for nonlinear manipulation and analysis of mixtures of DNA sequences was developed. Unlike conventional biological experiments, selected species were not directly subjected to analysis. Instead, parallel computation among a myriad of different DNA sequences was carried out to reduce the information entropy. The method could be used for various oligonucleotide-encoded libraries, as we have demonstrated its application in decoding and data analysis for selection experiments with DNA-encoded chemical libraries against protein targets.
AB - Information processing functions are essential for organisms to perceive and react to their complex environment, and for humans to analyze and rationalize them. While our brain is extraordinary at processing complex information, winner-take-all, as a type of biased competition is one of the simplest models of lateral inhibition and competition among biological neurons. It has been implemented as DNA-based neural networks, for example, to mimic pattern recognition. However, the utility of DNA-based computation in information processing for real biotechnological applications remains to be demonstrated. In this paper, a biased competition method for nonlinear manipulation and analysis of mixtures of DNA sequences was developed. Unlike conventional biological experiments, selected species were not directly subjected to analysis. Instead, parallel computation among a myriad of different DNA sequences was carried out to reduce the information entropy. The method could be used for various oligonucleotide-encoded libraries, as we have demonstrated its application in decoding and data analysis for selection experiments with DNA-encoded chemical libraries against protein targets.
UR - http://www.scopus.com/inward/record.url?scp=85141892047&partnerID=8YFLogxK
U2 - 10.1093/nar/gkac672
DO - 10.1093/nar/gkac672
M3 - Article
C2 - 35947747
AN - SCOPUS:85141892047
SN - 0305-1048
VL - 50
SP - 8974
EP - 8985
JO - Nucleic Acids Research
JF - Nucleic Acids Research
IS - 15
ER -