Evidence map›Paper›PMID 24933274›Full record

ArticleACS synthetic biology2014

Rule-based design of synthetic transcription factors in eukaryotes.

Oliver Purcell, Jean Peccoud, Timothy K Lu

Open access · greenAbstract read
In one paragraph

Article in ACS synthetic biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact, top 88% of its field
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

11 citing papers in PubMed, 0 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Oliver PurcellDepartment of Electrical Engineering & Computer Science and Department of Biological Engineering, Massachusetts Institute of Technology , 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States of America.
Jean Peccoud
Timothy K Lu
Massachusetts Institute of Technology · USVirginia Tech · US

Funding

High-Throughput Nanoscale Approaches to Studying and Inhibiting Amyloid ToxicityDP2OD008435 · OD · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LU, TIMOTHY · 2011 to 2011
$2.4M
NIH HHS 1DP2OD008435NIH HHS DP2 OD008435
6 · The paper itself

Abstract

To design and build living systems, synthetic biologists have at their disposal an increasingly large library of naturally derived and synthetic parts. These parts must be combined together in particular orders, orientations, and spacings to achieve desired functionalities. These structural constraints can be viewed as grammatical rules describing how to assemble parts together into larger functional units. Here, we develop a grammar for the design of synthetic transcription factors (sTFs) in eukaryotic cells and implement it within GenoCAD, a Computer-Aided Design (CAD) software for synthetic biology. Knowledge derived from experimental evidence was captured in this grammar to guide the user to create designer transcription factors that should operate as intended. The grammar can be easily updated and refined as our experience with using sTFs in different contexts increases. In combination with grammars that define other synthetic systems, we anticipate that this work will enable the more reliable, efficient, and automated design of synthetic cells with rich functionalities.

Indexed as

Computer-Aided DesignProtein EngineeringProtein Structure, TertiaryRecombinant ProteinsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSoftwareSynthetic BiologyTranscription FactorsRecombinant ProteinsSaccharomyces cerevisiae ProteinsTranscription Factorseukaryotic transcription factorGenoCADgrammarSaccharomyces cerevisiaesynthetic transcription factor

Identifiers

PMID24933274
PMCPMC4097980
OpenAlexW2239034927

What OpenQuestion holds

Textmetadata
LicenceTDM
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.