Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.
Sign Up to like & getrecommendations! Published in 2017 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-6753-7_6
Abstract: The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences… read more here.
Keywords: hidden markov; markov model; organizing hidden; biological sequence ... See more keywords
Representation learning applications in biological sequence analysis
Sign Up to like & getrecommendations! Published in 2021 at "Computational and Structural Biotechnology Journal"
DOI: 10.1016/j.csbj.2021.05.039
Abstract: Although remarkable advances have been reported in high-throughput sequencing, the ability to aptly analyze a substantial amount of rapidly generated biological (DNA/RNA/protein) sequencing data remains a critical hurdle. To tackle this issue, the application of… read more here.
Keywords: sequence analysis; representation learning; biological sequence;
An introduction to deep learning on biological sequence data: examples and solutions
Sign Up to like & getrecommendations! Published in 2017 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btx531
Abstract: Motivation Deep neural network architectures such as convolutional and long shortâterm memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms… read more here.
Keywords: deep learning; biology; biological sequence; introduction deep ... See more keywords
SECLAF: a webserver and deep neural network design tool for hierarchical biological sequence classification
Sign Up to like & getrecommendations! Published in 2018 at "Bioinformatics"
DOI: 10.1093/bioinformatics/bty116
Abstract: Summary Artificial intelligence tools are gaining more and more ground each year in bioinformatics. Learning algorithms can be taught for specific tasks by using the existing enormous biological databases, and the resulting models can be… read more here.
Keywords: classification; ontology; seclaf webserver; biological sequence ... See more keywords
MpBsmi: A new algorithm for the recognition of continuous biological sequence pattern based on index structure
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DOI: 10.1371/journal.pone.0195601
Abstract: A significant approach for the discovery of biological regulatory rules of genes, protein and their inheritance relationships is the extraction of meaningful patterns from biological sequence data. The existing algorithms of sequence pattern discovery, like… read more here.
Keywords: index; sequence pattern; new algorithm; biological sequence ... See more keywords
Information Theory for Biological Sequence Classification: A Novel Feature Extraction Technique Based on Tsallis Entropy
Sign Up to like & getrecommendations! Published in 2022 at "Entropy"
DOI: 10.3390/e24101398
Abstract: In recent years, there has been an exponential growth in sequencing projects due to accelerated technological advances, leading to a significant increase in the amount of data and resulting in new challenges for biological sequence… read more here.
Keywords: information; tsallis entropy; biological sequence; information theory ... See more keywords