AIMC Topic: Sequence Analysis, DNA

Clear Filters Showing 91 to 100 of 274 articles

An approach using ddRADseq and machine learning for understanding speciation in Antarctic Antarctophilinidae gastropods.

Scientific reports Apr 19, 2021
Sampling impediments and paucity of suitable material for molecular analyses have precluded the study of speciation and radiation of deep-sea species in Antarctica. We analyzed barcodes together with genome-wide single nucleotide polymorphisms obtain...
Antarctic Regions Genetic Speciation Gene Expression Regulation Gastropoda Machine Learning Animals Ecosystem Phylogeny Gene Expression Profiling Sequence Analysis, DNA
View on PubMed DOI

Improving protein domain classification for third-generation sequencing reads using deep learning.

BMC genomics Apr 9, 2021
BACKGROUND: With the development of third-generation sequencing (TGS) technologies, people are able to obtain DNA sequences with lengths from 10s to 100s of kb. These long reads allow protein domain annotation without assembly, thus can produce impor...
Humans Sequence Analysis, DNA Protein Domains High-Throughput Nucleotide Sequencing Software Algorithms Deep Learning
View on PubMed DOI

SeqEnhDL: sequence-based classification of cell type-specific enhancers using deep learning models.

BMC research notes Mar 19, 2021
OBJECTIVE: To address the challenge of computational identification of cell type-specific regulatory elements on a genome-wide scale.
Neural Networks, Computer Deep Learning Sequence Analysis, DNA DNA Enhancer Elements, Genetic
View on PubMed DOI

Prioritizing non-coding regions based on human genomic constraint and sequence context with deep learning.

Nature communications Mar 8, 2021
Elucidating functionality in non-coding regions is a key challenge in human genomics. It has been shown that intolerance to variation of coding and proximal non-coding sequence is a strong predictor of human disease relevance. Here, we integrate into...
Humans Deep Learning Genomics Genetic Variation Genome, Human DNA, Intergenic Sequence Analysis, DNA Whole Genome Sequencing
View on PubMed DOI

DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers.

Genomics, proteomics & bioinformatics Feb 11, 2021
The establishment of a landscape of enhancers across human cells is crucial to deciphering the mechanism of gene regulation, cell differentiation, and disease development. High-throughput experimental approaches, which contain successfully reported e...
Chromatin Sequence Analysis, DNA Enhancer Elements, Genetic Humans Neural Networks, Computer Software
View on PubMed DOI

Use of machine learning to identify a T cell response to SARS-CoV-2.

Cell reports. Medicine Jan 16, 2021
The identification of SARS-CoV-2-specific T cell receptor (TCR) sequences is critical for understanding T cell responses to SARS-CoV-2. Accordingly, we reanalyze publicly available data from SARS-CoV-2-recovered patients who had low-severity disease ...
Humans Machine Learning COVID-19 SARS-CoV-2 Amino Acid Sequence T-Lymphocytes Sequence Analysis, DNA Receptors, Antigen, B-Cell High-Throughput Nucleotide Sequencing Receptors, Antigen, T-Cell Cluster Analysis Principal Component Analysis Complementarity Determining Regions
View on PubMed DOI

iPTT(2 L)-CNN: A Two-Layer Predictor for Identifying Promoters and Their Types in Plant Genomes by Convolutional Neural Network.

Computational and mathematical methods in medicine Jan 5, 2021
A promoter is a short DNA sequence near to the start codon, responsible for initiating transcription of a specific gene in genome. The accurate recognition of promoters has great significance for a better understanding of the transcriptional regulati...
Genome, Plant DNA, Plant TATA Box Species Specificity Promoter Regions, Genetic Databases, Nucleic Acid Sequence Analysis, DNA Zea mays Neural Networks, Computer Computational Biology
View on PubMed DOI

A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification.

International journal of molecular sciences Nov 28, 2020
Essential genes contain key information of genomes that could be the key to a comprehensive understanding of life and evolution. Because of their importance, studies of essential genes have been considered a crucial problem in computational biology. ...
Area Under Curve Species Specificity Deep Learning Sequence Analysis, DNA Genes, Essential Algorithms Reproducibility of Results Neural Networks, Computer
View on PubMed DOI

Predicting 3D genome folding from DNA sequence with Akita.

Nature methods Oct 12, 2020
In interphase, the human genome sequence folds in three dimensions into a rich variety of locus-specific contact patterns. Cohesin and CTCF (CCCTC-binding factor) are key regulators; perturbing the levels of either greatly disrupts genome-wide foldin...
Chromosomal Proteins, Non-Histone Sequence Analysis, DNA Humans DNA-Binding Proteins Genome, Human Cohesins Neural Networks, Computer Gene Expression Regulation Cell Cycle Proteins Models, Genetic CCCTC-Binding Factor
View on PubMed DOI

Keeping up with the genomes: efficient learning of our increasing knowledge of the tree of life.

BMC bioinformatics Sep 21, 2020
BACKGROUND: It is a computational challenge for current metagenomic classifiers to keep up with the pace of training data generated from genome sequencing projects, such as the exponentially-growing NCBI RefSeq bacterial genome database. When new ref...
Algorithms Sequence Analysis, DNA Humans Genome, Bacterial Bacteria Machine Learning Bayes Theorem Metagenome Gastrointestinal Microbiome Metagenomics
View on PubMed DOI
Popular Topics
Recent Journals