Year: 2025
Type: article
Abstract: DNAInsight, a unified computational platform that integrates deep neural networks for DNA sequence classification with motif discovery algorithms to identify functional elements in genomic sequences.The rapid growth of genomic data requires efficient computational methods for sequence classification and the discovery of regulatory elements.Our system employs k-mer frequency-based feature extraction combined with a deep neural network design to obtain resilient DNA sequence classification across a wide range of taxonomic groups.We illustrate how this method effectively extracts sequence composition patterns without involving intricate alignment protocols.DNAInsight also incorporates two complementary motif discovery methods Expectation-Maximization (EM) and Gibbs sampling to detect conserved sequence patterns that can be indicative of transcription factor binding sites or other functional features.This study responds to the urgent requirement for combined tools that span sequence-level pattern identification and functional element detection, providing information on genomic structure-function correlations.The open-source aspect of DNAInsight promotes community-driven refinements and modifications for given research environments
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4414815098
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