Evidence map›Paper›PMID 25487098›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2015

Chemical master equation closure for computer-aided synthetic biology.

Patrick Smadbeck, Yiannis N Kaznessis

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2015. 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

2 authors.

Patrick SmadbeckDepartment of Chemical Engineering and Materials Science, University of Minnesota, 253 Amundson Hall, 421 Washington Ave SE, Minneapolis, MN, 55455-0531A, USA.
Yiannis N Kaznessis

Funding

Lactic Acid Bacteria that Detect & Inhibit Enterococci in the Mammalian GI TractR01GM111358 · NIGMS · UNIVERSITY OF MINNESOTA · PI DUNNY, GARY M, KAZNESSIS, YIANNIS · 2014 to 2017
$1.4M
Multiscale Models for Synthetic BiologyR01GM086865 · NIGMS · UNIVERSITY OF MINNESOTA · PI KAZNESSIS, YIANNIS · 2009 to 2010
$497k
NIGMS NIH HHS GM086865NIGMS NIH HHS R01 GM086865NIGMS NIH HHS R01 GM111358
6 · The paper itself

Abstract

With inexpensive DNA synthesis technologies, we can now construct biological systems by quickly piecing together DNA sequences. Synthetic biology is the promising discipline that focuses on the construction of these new biological systems. Synthetic biology is an engineering discipline, and as such, it can benefit from mathematical modeling. This chapter focuses on mathematical models of biological systems. These models take the form of chemical reaction networks. The importance of stochasticity is discussed and methods to simulate stochastic reaction networks are reviewed. A closure scheme solution is also presented for the master equation of chemical reaction networks. The master equation is a complete model of randomly evolving molecular populations. Because of its ambitious character, the master equation remained unsolved for all but the simplest of molecular interaction networks for over 70 years. With the first complete solution of chemical master equations, a wide range of experimental observations of biomolecular interactions may be mathematically conceptualized. We anticipate that models based on the closure scheme described herein may assist in rationally designing synthetic biological systems.

Indexed as

Computer SimulationModels, TheoreticalSynthetic Biology

Identifiers

PMID25487098
PMCPMC4820257

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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.