Evidence map›Paper›PMID 41890811›Full record

ArticleBioinformatics advances2026

SIREN: suite for intelligent RNAi design and evaluation of nucleotide sequences.

Pablo Vargas-Mejía, Julio Vega-Arreguín

Abstract read
In one paragraph

Article in Bioinformatics advances, 2026. 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. Review
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.

Pablo Vargas-MejíaLaboratorio de Ciencias AgroGenómicas, Escuela Nacional de Estudios Superiores Unidad León, UNAM, 37684, León, México.ORCID https://orcid.org/0000-0002-0360-1894
Julio Vega-ArreguínLaboratorio de Ciencias AgroGenómicas, Escuela Nacional de Estudios Superiores Unidad León, UNAM, 37684, León, México.ORCID https://orcid.org/0000-0002-4509-4122

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: RNA interference (RNAi) is a powerful tool for gene silencing across research, therapeutics, and agriculture. However, designing long double-stranded RNAs (dsRNAs) remains challenging because each dsRNA produces many small interfering RNAs (siRNAs), which can collectively introduce substantial off-target effects. Existing tools often lack the ability to account for cumulative off-target interactions, to incorporate thermodynamic modeling, or to accept custom transcriptome inputs, limiting their applicability and accuracy. Results: Here, we present SIREN, an open-source pipeline designed to streamline RNAi construct design. SIREN integrates siRNA generation, thermodynamically informed off-target prediction, scoring of dsRNA candidates based on cumulative off-target effects, and primer design for Availability and implementation: SIREN is implemented in Python and available under an open-source license at https://github.com/pablovargasmejia/SIREN.

Identifiers

PMID41890811
PMCPMC13012889

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.