Evidence map›Paper›PMID 32486951›Full record

ArticleJournal of the Royal Society, Interface2020

A domain-level DNA strand displacement reaction enumerator allowing arbitrary non-pseudoknotted secondary structures.

Stefan Badelt, Casey Grun, Karthik V Sarma, Brian Wolfe, Seung Woo Shin, Erik Winfree

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Catalyst-based biomolecular logic gates.Catalysts (Basel, Switzerland) · 2022
    Article
  4. Article
  5. Chemical Reaction Networks' Programming for Solving Equations.Current issues in molecular biology · 2022
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. A strand graph semantics for DNA-based computation.Theoretical computer science · 2016
    Article
  12. 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

6 authors.

Stefan BadeltCalifornia Institute of Technology, Pasadena, CA, USA.
Casey GrunWyss Institute, Harvard University, Boston, MA, USA.
Karthik V SarmaDavid Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Brian WolfeCalifornia Institute of Technology, Pasadena, CA, USA.
Seung Woo ShinCalifornia Institute of Technology, Pasadena, CA, USA.
Erik WinfreeCalifornia Institute of Technology, Pasadena, CA, USA.

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007205 · NIGMS · YALE UNIVERSITY · PI KAZMIERCZAK, BARBARA I · 1985 to 2019
$42.9M
UCLA-Caltech Medical Scientist Training ProgramT32GM008042 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AJIJOLA, OLUJIMI A, DAWSON, DAVID WAYNE · 1985 to 2023
$29.9M
Development of a Multimodal Deep Learning Model for the Generation of Cancer Probability Maps and Imaging Biomarkers for Prostate Cancer using Multiparametric MRIF30CA210329 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SARMA, KARTHIK VENKATARAMAN · 2016 to 2022
$173k
NCI NIH HHS F30 CA210329NIGMS NIH HHS T32 GM007205
6 · The paper itself

Abstract

Information technologies enable programmers and engineers to design and synthesize systems of startling complexity that nonetheless behave as intended. This mastery of complexity is made possible by a hierarchy of formal abstractions that span from high-level programming languages down to low-level implementation specifications, with rigorous connections between the levels. DNA nanotechnology presents us with a new molecular information technology whose potential has not yet been fully unlocked in this way. Developing an effective hierarchy of abstractions may be critical for increasing the complexity of programmable DNA systems. Here, we build on prior practice to provide a new formalization of 'domain-level' representations of DNA strand displacement systems that has a natural connection to nucleic acid biophysics while still being suitable for formal analysis. Enumeration of unimolecular and bimolecular reactions provides a semantics for programmable molecular interactions, with kinetics given by an approximate biophysical model. Reaction condensation provides a tractable simplification of the detailed reactions that respects overall kinetic properties. The applicability and accuracy of the model is evaluated across a wide range of engineered DNA strand displacement systems. Thus, our work can serve as an interface between lower-level DNA models that operate at the nucleotide sequence level, and high-level chemical reaction network models that operate at the level of interactions between abstract species.

Indexed as

DNANanotechnologyBiophysical PhenomenaKineticsProgramming LanguagesDNAchemical reaction networksdynamic DNA nanotechnologymolecular programming

Identifiers

PMID32486951
PMCPMC7328391

What OpenQuestion holds

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LicenceCC BY
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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.