Evidence map›Paper›PMID 27399702›Full record

ArticleSensors (Basel, Switzerland)2016

Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications.

Arjun Verma, Brian E Fratto, Vladimir Privman, Evgeny Katz

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Arjun VermaDepartment of Physics, Clarkson University, Potsdam, NY 13699, USA. vermaa@clarkson.edu.
Brian E FrattoDepartment of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY 13699, USA. frattobe@clarkson.edu.
Vladimir PrivmanDepartment of Physics, Clarkson University, Potsdam, NY 13699, USA. privman@clarkson.edu.
Evgeny KatzDepartment of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY 13699, USA. ekatz@clarkson.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

Indexed as

biomolecular computingbiosensorflow systemnoise reductionsignal processing

Identifiers

PMID27399702
PMCPMC4969838

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.