ArticleJournal of nucleic acids2013
Comparative (computational) analysis of the DNA methylation status of trinucleotide repeat expansion diseases.
Article in Journal of nucleic acids, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Comparative analysis of weka-based classification algorithms on medical diagnosis datasets.Technology and health care : official journal of the European Society for Engineering and Medicine · 2023Article
- Cardiovascular Research in Friedreich Ataxia: Unmet Needs and Opportunities.JACC. Basic to translational science · 2022Review
- Myotonic Dystrophy-A Progeroid Disease?Frontiers in neurology · 2018Article
- Systematic evaluation of supervised classifiers for fecal microbiota-based prediction of colorectal cancer.Oncotarget · 2017Article
- Genomics and Machine Learning for Taxonomy Consensus: The Mycobacterium tuberculosis Complex Paradigm.PloS one · 2015Article
- Muscle wasting in myotonic dystrophies: a model of premature aging.Frontiers in aging neuroscience · 2015Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Previous studies have examined DNA methylation in different trinucleotide repeat diseases. We have combined this data and used a pattern searching algorithm to identify motifs in the DNA surrounding aberrantly methylated CpGs found in the DNA of patients with one of the three trinucleotide repeat (TNR) expansion diseases: fragile X syndrome (FRAXA), myotonic dystrophy type I (DM1), or Friedreich's ataxia (FRDA). We examined sequences surrounding both the variably methylated (VM) CpGs, which are hypermethylated in patients compared with unaffected controls, and the nonvariably methylated CpGs which remain either always methylated (AM) or never methylated (NM) in both patients and controls. Using the J48 algorithm of WEKA analysis, we identified that two patterns are all that is necessary to classify our three regions CCGG∗ which is found in VM and not in AM regions and AATT∗ which distinguished between NM and VM + AM using proportional frequency. Furthermore, comparing our software with MEME software, we have demonstrated that our software identifies more patterns than MEME in these short DNA sequences. Thus, we present evidence that the DNA sequence surrounding CpG can influence its susceptibility to be de novo methylated in a disease state associated with a trinucleotide repeat.
Identifiers
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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 Socratic graph.