ArticleNucleic acids research2011
Genome-wide analysis of mobile genetic element insertion sites.
Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 45 citations in OpenAlex.
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- Inpactor2: a software based on deep learning to identify and classify LTR-retrotransposons in plant genomes.Briefings in bioinformatics · 2023Article
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- Retrotransposons in Plant Genomes: Structure, Identification, and Classification through Bioinformatics and Machine Learning.International journal of molecular sciences · 2019Review
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- Single genome retrieval of context-dependent variability in mutation rates for human germline.BMC genomics · 2017Article
- LINE-1-like retrotransposons contribute to RNA-based gene duplication in dicots.Scientific reports · 2016Article
- Genome wide occurrence and insertion preferences of INGI/RIME and SLACS CRE transposable elements inMobile genetic elements · 2016Article
- T-lex2: genotyping, frequency estimation and re-annotation of transposable elements using single or pooled next-generation sequencing data.Nucleic acids research · 2015Article
- Identification and characterization of MGEs and their insertion sites in theMobile genetic elements · 2013Article
- Distribution of MGEs and their insertion sites in the Macaca mulatta genome.Mobile genetic elements · 2012Article
- DNA structural properties in the classification of genomic transcription regulation elements.Bioinformatics and biology insights · 2012Article
- Detecting motifs and patterns at mobile genetic element insertion site.Bioinformation · 2012Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mobile genetic elements (MGEs) account for a significant fraction of eukaryotic genomes and are implicated in altered gene expression and disease. We present an efficient computational protocol for MGE insertion site analysis. ELAN, the suite of tools described here uses standard techniques to identify different MGEs and their distribution on the genome. One component, DNASCANNER analyses known insertion sites of MGEs for the presence of signals that are based on a combination of local physical and chemical properties. ISF (insertion site finder) is a machine-learning tool that incorporates information derived from DNASCANNER. ISF permits classification of a given DNA sequence as a potential insertion site or not, using a support vector machine. We have studied the genomes of Homo sapiens, Mus musculus, Drosophila melanogaster and Entamoeba histolytica via a protocol whereby DNASCANNER is used to identify a common set of statistically important signals flanking the insertion sites in the various genomes. These are used in ISF for insertion site prediction, and the current accuracy of the tool is over 65%. We find similar signals at gene boundaries and splice sites. Together, these data are suggestive of a common insertion mechanism that operates in a variety of eukaryotes.
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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.