Evidence map›Paper›PMID 25999345›Full record

ArticleNucleic acids research2015

Primerize: automated primer assembly for transcribing non-coding RNA domains.

Siqi Tian, Joseph D Yesselman, Pablo Cordero, Rhiju Das

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Quantifying MgbioRxiv : the preprint server for biology · 2026
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  10. Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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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

4 authors.

Siqi TianDepartments of Biochemistry, Stanford University, Stanford CA 94305, USA.
Joseph D YesselmanDepartments of Biochemistry, Stanford University, Stanford CA 94305, USA.
Pablo CorderoProgram in Biomedical Informatics, Stanford University, Stanford CA 94305, USA.
Rhiju DasDepartments of Biochemistry, Stanford University, Stanford CA 94305, USA Program in Biomedical Informatics, Stanford University, Stanford CA 94305, USA Department of Physics, Stanford University, Stanford CA 94305, USA rhiju@stanford.edu.

Funding

Non-coding RNA Structure through a Mutate-and-Map StrategyR01GM102519 · NIGMS · STANFORD UNIVERSITY · PI DAS, RHIJU · 2012 to 2016
$1.5M
NIGMS NIH HHS R01 GM102519NIGMS NIH HHS R01 R01GM102519
6 · The paper itself

Abstract

Customized RNA synthesis is in demand for biological and biotechnological research. While chemical synthesis and gel or chromatographic purification of RNA is costly and difficult for sequences longer than tens of nucleotides, a pipeline of primer assembly of DNA templates, in vitro transcription by T7 RNA polymerase and kit-based purification provides a cost-effective and fast alternative for preparing RNA molecules. Nevertheless, designing template primers that optimize cost and avoid mispriming during polymerase chain reaction currently requires expert inspection, downloading specialized software or both. Online servers are currently not available or maintained for the task. We report here a server named Primerize that makes available an efficient algorithm for primer design developed and experimentally tested in our laboratory for RNA domains with lengths up to 300 nucleotides. Free access: http://primerize.stanford.edu.

Indexed as

SoftwareAlgorithmsDNA PrimersInternetNucleic Acid ConformationPolymerase Chain ReactionRNA, UntranslatedSequence Analysis, DNATemplates, GeneticTranscription, GeneticDNA PrimersRNA, Untranslated

Identifiers

PMID25999345
PMCPMC4489279

What OpenQuestion holds

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LicenceCC BY-NC
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.