ArticleBioinformatics (Oxford, England)2018
CNEFinder: finding conserved non-coding elements in genomes.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- Review
- Article
- Giant transposons promote strain heterogeneity in a major fungal pathogen.bioRxiv : the preprint server for biology · 2025Article
- Horizontal transfers between fungal Fusarium species contributed to successive outbreaks of coffee wilt disease.PLoS biology · 2024Article
- A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024Review
- Systematic identification of cargo-mobilizing genetic elements reveals new dimensions of eukaryotic diversity.Nucleic acids research · 2024Article
- Pan-evolutionary and regulatory genome architecture delineated by an integrated macro- and microsynteny approach.Nature protocols · 2024Review
- Conserved Noncoding Elements Evolve Around the Same Genes Throughout Metazoan Evolution.Genome biology and evolution · 2024Article
- CNEr: A toolkit for exploring extreme noncoding conservation.PLoS computational biology · 2019Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Conserved non-coding elements (CNEs) represent an enigmatic class of genomic elements which, despite being extremely conserved across evolution, do not encode for proteins. Their functions are still largely unknown. Thus, there exists a need to systematically investigate their roles in genomes. Towards this direction, identifying sets of CNEs in a wide range of organisms is an important first step. Currently, there are no tools published in the literature for systematically identifying CNEs in genomes. Results: We fill this gap by presenting CNEFinder; a tool for identifying CNEs between two given DNA sequences with user-defined criteria. The results presented here show the tool's ability of identifying CNEs accurately and efficiently. CNEFinder is based on a k-mer technique for computing maximal exact matches. The tool thus does not require or compute whole-genome alignments or indexes, such as the suffix array or the Burrows Wheeler Transform (BWT), which makes it flexible to use on a wide scale. Availability and implementation: Free software under the terms of the GNU GPL (https://github.com/lorrainea/CNEFinder).
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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.