Evidence map›Paper›PMID 25296327›Full record

ArticleBiophysical journal2014

Sequence-dependent biophysical modeling of DNA amplification.

Karthikeyan Marimuthu, Chaoran Jing, Raj Chakrabarti

Abstract read
In one paragraph

Article in Biophysical journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Karthikeyan MarimuthuDepartment of Chemical Engineering and Center for Advanced Process Decision-making, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Chaoran JingDivision of Fundamental Research, PMC Advanced Technology, Mt. Laurel, New Jersey.
Raj ChakrabartiDepartment of Chemical Engineering and Center for Advanced Process Decision-making, Carnegie Mellon University, Pittsburgh, Pennsylvania; Division of Fundamental Research, PMC Advanced Technology, Mt. Laurel, New Jersey. Electronic address: raj@pmc-group.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A theoretical framework for prediction of the dynamic evolution of chemical species in DNA amplification reactions, for any specified sequence and operating conditions, is reported. Using the polymerase chain reaction (PCR) as an example, we developed a sequence- and temperature-dependent kinetic model for DNA amplification using first-principles biophysical modeling of DNA hybridization and polymerization. We compare this kinetic model with prior PCR models and discuss the features of our model that are essential for quantitative prediction of DNA amplification efficiency for arbitrary sequences and operating conditions. Using this model, the kinetics of PCR is analyzed. The ability of the model to distinguish between the dynamic evolution of distinct DNA sequences in DNA amplification reactions is demonstrated. The kinetic model is solved for a typical PCR temperature protocol to motivate the need for optimization of the dynamic operating conditions of DNA amplification reactions. It is shown that amplification efficiency is affected by dynamic processes that are not accurately represented in the simplified models of DNA amplification that form the basis of conventional temperature cycling protocols. Based on this analysis, a modified temperature protocol that improves PCR efficiency is suggested. Use of this sequence-dependent kinetic model in a control theoretic framework to determine the optimal dynamic operating conditions of DNA amplification reactions, for any specified amplification objective, is discussed.

Indexed as

Models, BiologicalBase SequenceDNADNA NucleotidyltransferasesKineticsNucleic Acid HybridizationPolymerase Chain ReactionTemperatureDNADNA Nucleotidyltransferases

Identifiers

PMID25296327
PMCPMC4190609

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.