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Richard E. Higgs

dblp:69/3762 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene expression analysis
differential expression analysis
0.812024
SeedMatchR: identify off-target effects mediated by siRNA seed regions in RNA-seq experiments · Bioinform. 2024
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.812024
SeedMatchR: identify off-target effects mediated by siRNA seed regions in RNA-seq experiments · Bioinform. 2024

Methods — techniques the papers use, named apart from their topics

seed match annotation · 0.8differential expression analysis · 0.8
YearPublicationVenuePosition
2024 SeedMatchR: identify off-target effects mediated by siRNA seed regions in RNA-seq experiments
abstract
MOTIVATION: On-target gene knockdown, using siRNA, ideally results from binding fully complementary regions in mRNA transcripts to induce direct cleavage. Off-target siRNA gene knockdown can occur through several modes, one being a seed-mediated mechanism mimicking miRNA gene regulation. Seed-mediated off-target effects occur when the ∼8 nucleotides at the 5' end of the guide strand, called a seed region, bind the 3' untranslated regions of mRNA, causing reduced translation. Experiments using siRNA knockdown paired with RNA-seq can be used to detect siRNA sequences with off-target effects driven by the seed region. However, there are limited computational tools designed specifically for detecting siRNA off-target effects mediated by the seed region in differential gene expression experiments. RESULTS: SeedMatchR is an R package developed to provide users a single, unified resource for detecting and visualizing seed-mediated off-target effects of siRNA using RNA-seq experiments. SeedMatchR is designed to extend current differential expression analysis tools, such as DESeq2, by annotating results with predicted seed matches. Using publicly available data, we demonstrate the ability of SeedMatchR to detect cumulative changes in differential gene expression attributed to siRNA seed region activity. AVAILABILITY: SeedMatchR is available on CRAN. Documentation and example workflows are available through the SeedMatchR GitHub page at https://github.com/tacazares/SeedMatchR.
Tareian A. Cazares, Richard E. Higgs, Jibo Wang, Hatice Gulcin Ozer
Bioinform.2