Molecular Computing for Construction of Smart Biosensors from Deoxyribonucleic Acid–Based Logic Gates

2018 ◽  
pp. 273-294
Author(s):  
Bradley I. Harding ◽  
Joanne MacDonald
Keyword(s):  
Deoxyribonucleic Acid ◽  
Logic Gates ◽  
Molecular Computing

scholarly journals AI in Measurement Science

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Chao Liu ◽  
Jiashu Sun
Keyword(s):  
Analytical Chemistry ◽  
Biomarker Discovery ◽  
Biological Systems ◽  
Measurement Data ◽  
Logic Gates ◽  
Molecular Computing ◽  
Annual Review ◽  
Complex Nature ◽  
Publication Date ◽  
Measurement Science

Measurement of biological systems containing biomolecules and bioparticles is a key task in the fields of analytical chemistry, biology, and medicine. Driven by the complex nature of biological systems and unprecedented amounts of measurement data, artificial intelligence (AI) in measurement science has rapidly advanced from the use of silicon-based machine learning (ML) for data mining to the development of molecular computing with improved sensitivity and accuracy. This review presents an overview of fundamental ML methodologies and discusses their applications in disease diagnostics, biomarker discovery, and imaging analysis. We next provide the working principles of molecular computing using logic gates and arithmetical devices, which can be employed for in situ detection, computation, and signal transduction for biological systems. This review concludes by summarizing the strengths and limitations of AI-involved biological measurement in fundamental and applied research. Expected final online publication date for the Annual Review of Analytical Chemistry, Volume 14 is June 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Engineering calcium signaling of astrocytes for neural–molecular computing logic gates

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael Taynnan Barros ◽  
Phuong Doan ◽  
Meenakshisundaram Kandhavelu ◽  
Brendan Jennings ◽  
Sasitharan Balasubramaniam
Keyword(s):  
Time Slot ◽  
Logic Gates ◽  
Boolean Logic ◽  
Molecular Computing ◽  
Learning Platform ◽  
Input Signals ◽  
Reinforced Learning ◽  
Wet Lab ◽  
Flow Through ◽  
New Generation

AbstractThis paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of $$\hbox {Ca}^{2+}$$ Ca 2 + ion flows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical compounds, we show that both AND and OR gates can be implemented by controlling $$\hbox {Ca}^{2+}$$ Ca 2 + signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize the $$\hbox {Ca}^{2+}$$ Ca 2 + activated level and time slot of input signals $$T_b$$ T b into the gate. This design platform caters for any size and connectivity of the cell population, by taking into consideration the delay and noise produced from the signalling between the cells. To validate the effectiveness of the reinforced learning platform, a $$\hbox {Ca}^{2+}$$ Ca 2 + signalling simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation show that an optimum value for both the $$\hbox {Ca}^{2+}$$ Ca 2 + activated level and time slot of input signals $$T_b$$ T b is required to achieve up to 90% accuracy for both the AND and OR gates. Our method can be used as the basis for future Neural–Molecular Computing chips, constructed from engineered astrocyte cells, which can form the basis for a new generation of brain implants.

Nanocell logic gates for molecular computing

2002 ◽  
Vol 1 (2) ◽  
pp. 100-109 ◽  
Author(s):  
J.M. Tour ◽  
W.L. Van Zandt ◽  
C.P. Husband ◽  
S.M. Husband ◽  
L.S. Wilson ◽  
...  
Keyword(s):  
Logic Gates ◽  
Molecular Computing

Improvement of Single-Electron Digital Logic Gates by Utilizing Input Discretizers

2016 ◽  
Vol E99.C (2) ◽  
pp. 285-292 ◽  
Author(s):  
Tran THI THU HUONG ◽  
Hiroshi SHIMADA ◽  
Yoshinao MIZUGAKI
Keyword(s):  
Logic Gates ◽  
Single Electron ◽  
Digital Logic

MICROBIAL COMMUNITY DURING BIOREMEDIATION EXPERIMENTAL ON OIL SPILL IN COASTAL OF PARI ISLAND

2011 ◽  
Vol 3 (1) ◽  
Author(s):  
Lies Indah Sutiknowati
Keyword(s):  
Oil Spill ◽  
Deoxyribonucleic Acid ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Gas Chromatography Mass Spectrometry ◽  
Oil Degradation ◽  
Sequence Determination ◽  
Blast Search ◽  
Degrading Bacteria ◽  
Gradient Gel Electrophoresis

There is an information how to identify hydrocarbon degrading bacteria for bioremediation of marine oil spill. We have Bioremediation treatment for degradation of oil spill on Pari island and need two kind of experiment there are tanks experiment (sampling 0 to 90 days) and semi enclosed system (sampling 0 to 150 days). Biostimulation with nutrients (N and P) was done to analyze biodegradation of hydrocarbon compounds. Experiment design using fertilizer Super IB and Linstar will stimulate bacteria can degrade oil, n-alkane, and alkane as poly aromatic hydrocarbon. The bacteria communities were monitored and analyzed by Denaturing Gradient Gel Electrophoresis (DGGE) and Clone Library; oil chemistry was analyzed by Gas Chromatography Mass Spectrometry (GCMS). DNA (deoxyribonucleic acid) was extracted from colonies of bacteria and sequence determination of the 16S rDNA was amplified by primers U515f and U1492r. Strains had been sequence and had similarity about 90-99% to their closest taxa by homology Blast search and few of them suspected as new species. The results showed that fertilizers gave a significant effect on alkane, PAH and oil degradation in tanks experiment but not in the field test. Dominant of the specific bacteria on this experiment were Alcanivorax, Marinobacter and Prosthecochloris. Keywords: Bioremediation, Biostimulation, DGGE, PAH, Pari Island

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