Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 470

The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.

FEELnc: a tool for long non-coding RNA annotation and its application to the dog transcriptome

Open access
Wucher, Valentin, Legeai, Fabrice, Hédan, Benoît, Rizk, Guillaume, Lagoutte, Lætitia, Leeb, Tosso, Jagannathan, Vidhya, Cadieu, Edouard, David, Audrey, Lohi, Hannes, Cirera, Susanna, Fredholm, Merete, Botherel, Nadine, Leegwater, Peter A.J., Le Béguec, Céline, Fieten, Hille, Johnson, Jeremy, Alföldi, Jessica, André, Catherine, Lindblad-Toh, Kerstin, Hitte, Christophe, Derrien, Thomas·2017·Nucleic Acids Research

Abstract

Whole transcriptome sequencing (RNA-seq) has become a standard for cataloguing and monitoring RNA populations. One of the main bottlenecks, however, is to correctly identify the different classes of RNAs among the plethora of reconstructed transcripts, particularly those that will be translated (mRNAs) from the class of long non-coding RNAs (lncRNAs). Here, we present FEELnc (FlExible Extraction of LncRNAs), an alignment-free program that accurately annotates lncRNAs based on a Random Forest model trained with general features such as multi k-mer frequencies and relaxed open reading frames. Benchmarking versus five state-of-the-art tools shows that FEELnc achieves similar or better classification performance on GENCODE and NONCODE data sets. The program also provides specific modules that enable the user to fine-tune classification accuracy, to formalize the annotation of lncRNA classes and to identify lncRNAs even in the absence of a training set of non-coding RNAs. We used FEELnc on a real data set comprising 20 canine RNA-seq samples produced by the European LUPA consortium to substantially expand the canine genome annotation to include 10 374 novel lncRNAs and 58 640 mRNA transcripts. FEELnc moves beyond conventional coding potential classifiers by providing a standardized and complete solution for annotating lncRNAs and is freely available at https://github.com/tderrien/FEELnc.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/nar/gkw1306

Cites

74 of 74 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 74 references

Cited by

See all 470

Metadata

Authors
Wucher, V., Legeai, F., Hédan, B., Rizk, G., Lagoutte, L., Leeb, T., Jagannathan, V., Cadieu, E., David, A., Lohi, H., Cirera, S., Fredholm, M., Botherel, N., Leegwater, P. A. J., Le Béguec, C., Fieten, H., Johnson, J., Alföldi, J., André, C., Lindblad-Toh, K., Hitte, C., & Derrien, T.
Venue
Nucleic Acids Research
Published
2017-01-03
Volume
45
Issue
8
Pages
gkw1306
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
OpenAlex
W2571489439
Cited by
470
References
74
FWCI
15.80
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: FEELnc: a tool for long non-coding RNA annotation and its application to the dog transcriptome. https://app.cochat.ai/papers/10.1093/nar/gkw1306
The paper
Wucher, V., Legeai, F., Hédan, B., Rizk, G., Lagoutte, L., Leeb, T., Jagannathan, V., Cadieu, E., David, A., Lohi, H., Cirera, S., Fredholm, M., Botherel, N., Leegwater, P. A. J., Le Béguec, C., Fieten, H., Johnson, J., Alföldi, J., André, C., . . . Derrien, T. (2017). FEELnc: a tool for long non-coding RNA annotation and its application to the dog transcriptome. Nucleic Acids Research. https://doi.org/10.1093/nar/gkw1306

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.