@inproceedings{f8ccf6e1a1e84dfead43a85479773c71,
title = "GPU Based Composite Elements Discovery in Large DNADatasets",
abstract = "Composite elements play an important role in the regulation of transcription. Existing methods for the revealing of potential composite elements are usually based on assessment of the significance of the mutual presence of the predicted transcription factor binding sites using weight matrices or other methods trained on samples of binding sites of known transcription factors. Thus, such methods essentially depend on the completeness of training samples and information on existing TFs. We have proposed a method for de novo discovery of potential composite elements, which does not require preliminary information about the localization of potential TFBS. Using the proposed approach, context signals are identified in the ChIP-Seq dataset, which can correspond to potential composite elements.",
keywords = "ChIP-Seq, composite elements, oligonucleotide motifs, transcription regulation",
author = "Oleg Vishnevsky and Andrey Bocharnikov and Nikolay Kolchanov",
year = "2020",
month = jul,
doi = "10.1109/CSGB51356.2020.9214777",
language = "English",
series = "Proceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "135--138",
booktitle = "Proceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020",
address = "United States",
note = "2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020 ; Conference date: 06-07-2020 Through 10-07-2020",
}