ArticlePloS one2016
SeqFeatR for the Discovery of Feature-Sequence Associations.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed.
- A single residue in influenza virus H2 hemagglutinin enhances the breadth of the B cell response elicited by H2 vaccination.Nature medicine · 2022Article
- Vaccination in a humanized mouse model elicits highly protective PfCSP-targeting anti-malarial antibodies.Immunity · 2021Article
- Bioinformatics Research on Drug Sensitivity Prediction.Frontiers in pharmacology · 2021Review
- Mutations in Hepatitis D Virus Allow It to Escape Detection by CD8Gastroenterology · 2019Article
- Improvement of antibody functionality by structure-guided paratope engraftment.Nature communications · 2019Article
- Differential escape of HCV from CD8Journal of viral hepatitis · 2019Article
- Complete functional mapping of infection- and vaccine-elicited antibodies against the fusion peptide of HIV.PLoS pathogens · 2018Article
- Genotypic Prediction of Co-receptor Tropism of HIV-1 Subtypes A and C.Scientific reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Specific selection pressures often lead to specifically mutated genomes. The open source software SeqFeatR has been developed to identify associations between mutation patterns in biological sequences and specific selection pressures ("features"). For instance, SeqFeatR has been used to discover in viral protein sequences new T cell epitopes for hosts of given HLA types. SeqFeatR supports frequentist and Bayesian methods for the discovery of statistical sequence-feature associations. Moreover, it offers novel ways to visualize results of the statistical analyses and to relate them to further properties. In this article we demonstrate various functions of SeqFeatR with real data. The most frequently used set of functions is also provided by a web server. SeqFeatR is implemented as R package and freely available from the R archive CRAN (http://cran.r-project.org/web/packages/SeqFeatR/index.html). The package includes a tutorial vignette. The software is distributed under the GNU General Public License (version 3 or later). The web server URL is https://seqfeatr.zmb.uni-due.de.
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Registered trials
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.