P
Pakpoom Subsoontorn
Researcher at Naresuan University
Publications - 15
Citations - 1066
Pakpoom Subsoontorn is an academic researcher from Naresuan University. The author has contributed to research in topics: Recombinase & Synthetic biology. The author has an hindex of 8, co-authored 15 publications receiving 915 citations. Previous affiliations of Pakpoom Subsoontorn include California Institute of Technology & University of Cambridge.
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Journal ArticleDOI
Amplifying Genetic Logic Gates
TL;DR: The single-layer digital logic architecture developed here enables engineering of amplifying logic gates to control transcription rates within and across diverse organisms.
Journal ArticleDOI
Rewritable digital data storage in live cells via engineered control of recombination directionality.
TL;DR: A rewriteable recombinase addressable data (RAD) module that reliably stores digital information within a chromosome is demonstrated that does not require cell-specific cofactors and should be useful in extending computing and control methods to the study and engineering of many biological systems.
Journal ArticleDOI
The diagnostic accuracy of isothermal nucleic acid point-of-care tests for human coronaviruses: A systematic review and meta-analysis.
TL;DR: In this paper, the authors conducted a systematic review of point-of-care point of care (POCT) tests based on reverse transcription loop-mediated isothermal amplification (RT-LAMP) to diagnose coronaviruses.
Journal ArticleDOI
Ensemble Bayesian analysis of bistability in a synthetic transcriptional switch.
TL;DR: It is demonstrated that programmable in vitro biochemical circuits can serve as a testing ground for evaluating methods for the design and analysis of more complex biochemical systems such as living cells.
Proceedings ArticleDOI
Kids making AI: Integrating Machine Learning, Gamification, and Social Context in STEM Education
Bawornsak Sakulkueakulsuk,Sivada Witoon,Potiwat Ngarmkajornwiwat,Pornpen Pataranutapom,Werasak Surareungchai,Pat Pataranutaporn,Pakpoom Subsoontorn +6 more
TL;DR: An agricultural based AI challenge that fostered students to learn the process of creating machine learning models in the form of a game with the emphasis on the Four P's of Creative Learning.