AIMC Topic: Sequence Analysis, DNA

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Cross-species regulatory sequence activity prediction.

PLoS computational biology Jul 20, 2020
Machine learning algorithms trained to predict the regulatory activity of nucleic acid sequences have revealed principles of gene regulation and guided genetic variation analysis. While the human genome has been extensively annotated and studied, mod...
Species Specificity Quantitative Trait Loci Sequence Analysis, DNA Models, Statistical Mutation Gene Expression Regulation Genome, Human Hepatocytes Genetic Variation Epigenomics Models, Genetic Databases, Genetic Mice Genomics Computational Biology Humans Algorithms Neural Networks, Computer Machine Learning Animals Software
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Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping.

Nature communications Jul 15, 2020
Predicting effects of gene regulatory elements (GREs) is a longstanding challenge in biology. Machine learning may address this, but requires large datasets linking GREs to their quantitative function. However, experimental methods to generate such d...
Deep Learning Computational Biology Escherichia coli Sequence Analysis, DNA Phenotype Binding Sites Gene Knockout Techniques Genome, Bacterial Ribosomes High-Throughput Nucleotide Sequencing Datasets as Topic Molecular Sequence Annotation Regulatory Sequences, Nucleic Acid
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A supervised learning framework for chromatin loop detection in genome-wide contact maps.

Nature communications Jul 9, 2020
Accurately predicting chromatin loops from genome-wide interaction matrices such as Hi-C data is critical to deepening our understanding of proper gene regulation. Current approaches are mainly focused on searching for statistically enriched dots on ...
Humans Databases, Genetic Organ Specificity K562 Cells Genome Chromatin Sequence Analysis, DNA Supervised Machine Learning Species Specificity
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Evaluation of marker selection methods and statistical models for chronological age prediction based on DNA methylation.

Legal medicine (Tokyo, Japan) Jul 1, 2020
In forensic investigation, retrieving biological information from DNA evidence is a promising field of interest. One of the applications is on the estimation of the age of the donor based on DNA methylation. A large number of studies focused on age p...
Aged, 80 and over Young Adult CpG Islands DNA Methylation Adult Models, Statistical Forensic Genetics Linear Models Middle Aged Algorithms Sequence Analysis, DNA Forecasting Male Humans Female Aging Aged Machine Learning
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Predicting host taxonomic information from viral genomes: A comparison of feature representations.

PLoS computational biology May 26, 2020
The rise in metagenomics has led to an exponential growth in virus discovery. However, the majority of these new virus sequences have no assigned host. Current machine learning approaches to predicting virus host interactions have a tendency to focus...
Algorithms Databases, Factual Computational Biology Support Vector Machine Phylogeny Bacteria Metagenomics Linear Models Sequence Analysis, DNA Genome, Viral Area Under Curve Caudovirales Viruses Nucleotides
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FF-QuantSC: accurate quantification of fetal fraction by a neural network model.

Molecular genetics & genomic medicine Apr 13, 2020
BACKGROUND: Noninvasive prenatal testing (NIPT) is one of the most commonly employed clinical measures for screening of fetal aneuploidy. Fetal Fraction (ff) has been demonstrated to be one of the key factors affecting the performance of NIPT. Accura...
Noninvasive Prenatal Testing Female Adult Sensitivity and Specificity Sequence Analysis, DNA Neural Networks, Computer Software Pregnancy Humans
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Machine Learning Techniques for Classifying the Mutagenic Origins of Point Mutations.

Genetics Mar 19, 2020
There is increasing interest in developing diagnostics that discriminate individual mutagenic mechanisms in a range of applications that include identifying population-specific mutagenesis and resolving distinct mutation signatures in cancer samples....
Point Mutation Ethylnitrosourea Animals Sequence Analysis, DNA Mice Machine Learning Mutagens Nucleotide Motifs
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Machine Learning-Guided Prediction of Antigen-Reactive In Silico Clonotypes Based on Changes in Clonal Abundance through Bio-Panning.

Biomolecules Mar 8, 2020
c-Met is a promising target in cancer therapy for its intrinsic oncogenic properties. However, there are currently no c-Met-specific inhibitors available in the clinic. Antibodies blocking the interaction with its only known ligand, hepatocyte growth...
Machine Learning Avian Proteins Animals Single-Chain Antibodies Chickens Antigens Sequence Analysis, DNA Cloning, Molecular
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Second-Generation Sequencing with Deep Reinforcement Learning for Lung Infection Detection.

Journal of healthcare engineering Feb 22, 2020
Recently, deep reinforcement learning, associated with medical big data generated and collected from medical Internet of Things, is prospective for computer-aided diagnosis and therapy. In this paper, we focus on the application value of the second-g...
Humans Diagnosis, Computer-Assisted Lung Diseases Prospective Studies Deep Learning Gene Expression Profiling Sequence Analysis, DNA
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iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks.

BMC genomics Dec 24, 2019
BACKGROUND: Enhancers are non-coding DNA fragments which are crucial in gene regulation (e.g. transcription and translation). Having high locational variation and free scattering in 98% of non-encoding genomes, enhancer identification is, therefore, ...
Neural Networks, Computer Sequence Analysis, DNA Enhancer Elements, Genetic
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