AIMC Topic: Eukaryota

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Machine-learning predicts genomic determinants of meiosis-driven structural variation in a eukaryotic pathogen.

Nature communications Jun 10, 2021
Species harbor extensive structural variation underpinning recent adaptive evolution. However, the causality between genomic features and the induction of new rearrangements is poorly established. Here, we analyze a global set of telomere-to-telomere...
Chromosomes Arabidopsis Retroelements Crossing Over, Genetic Eukaryota Models, Genetic Genome INDEL Mutation Evolution, Molecular Genetic Variation Pedigree Genes, Duplicate Meiosis Sequence Inversion Polymorphism, Genetic Ascomycota Genome-Wide Association Study Genomics Polymorphism, Single Nucleotide Machine Learning Computer Simulation Phylogeny
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Identifying genomic islands with deep neural networks.

BMC genomics Jun 2, 2021
BACKGROUND: Horizontal gene transfer is the main source of adaptability for bacteria, through which genes are obtained from different sources including bacteria, archaea, viruses, and eukaryotes. This process promotes the rapid spread of genetic info...
Genomics Genomic Islands Eukaryota Gene Transfer, Horizontal Neural Networks, Computer
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Hereditary disease prediction in eukaryotic DNA: an adaptive signal processing approach.

Nucleosides, nucleotides & nucleic acids Jun 22, 2020
Hereditary disease prediction in eukaryotic DNA using signal processing approaches is an incredible work in bioinformatics. Researchers of various fields are trying to put forth a noninvasive approach to forecast the disease-related genes. As disease...
DNA Mutation Eukaryota Genetic Diseases, Inborn Neural Networks, Computer Algorithms Computational Biology Humans
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ProNA2020 predicts protein-DNA, protein-RNA, and protein-protein binding proteins and residues from sequence.

Journal of molecular biology Mar 4, 2020
The intricate details of how proteins bind to proteins, DNA, and RNA are crucial for the understanding of almost all biological processes. Disease-causing sequence variants often affect binding residues. Here, we described a new, comprehensive system...
Computational Biology Proteins DNA Software Animals Protein Binding Binding Sites Eukaryota Sequence Analysis, Protein Prokaryotic Cells RNA Protein Conformation Nucleic Acid Conformation Neural Networks, Computer Machine Learning Humans
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Machine learning for discovering missing or wrong protein function annotations : A comparison using updated benchmark datasets.

BMC bioinformatics Sep 23, 2019
BACKGROUND: A massive amount of proteomic data is generated on a daily basis, nonetheless annotating all sequences is costly and often unfeasible. As a countermeasure, machine learning methods have been used to automatically annotate new protein func...
Humans Cluster Analysis Molecular Sequence Annotation Machine Learning Proteomics Gene Ontology Eukaryota
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Designing Eukaryotic Gene Expression Regulation Using Machine Learning.

Trends in biotechnology Aug 17, 2019
Controlling the expression of genes is one of the key challenges of synthetic biology. Until recently fine-tuned control has been out of reach, particularly in eukaryotes owing to their complexity of gene regulation. With advances in machine learning...
Machine Learning Algorithms Genetic Engineering Synthetic Biology Eukaryotic Cells Models, Genetic Gene Expression Regulation Flow Cytometry Eukaryota Genetic Variation
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SignalP 5.0 improves signal peptide predictions using deep neural networks.

Nature biotechnology Feb 18, 2019
Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish ...
Biotechnology Eukaryota Sequence Analysis, Protein Protein Sorting Signals Archaeal Proteins Computational Biology Bacterial Proteins Amino Acid Sequence Neural Networks, Computer Software Algorithms
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Supervised machine learning outperforms taxonomy-based environmental DNA metabarcoding applied to biomonitoring.

Molecular ecology resources Aug 3, 2018
Biodiversity monitoring is the standard for environmental impact assessment of anthropogenic activities. Several recent studies showed that high-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) could overcome many limitations ...
Biomarkers Computer Simulation Bacteria Metagenomics DNA Barcoding, Taxonomic Environmental Monitoring RNA, Ribosomal Eukaryota Supervised Machine Learning Biodiversity
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Monitoring changes in the Gene Ontology and their impact on genomic data analysis.

GigaScience Aug 1, 2018
BACKGROUND: The Gene Ontology (GO) is one of the most widely used resources in molecular and cellular biology, largely through the use of "enrichment analysis." To facilitate informed use of GO, we present GOtrack (https://gotrack.msl.ubc.ca), which ...
Animals Humans Genomics Molecular Sequence Annotation Gene Ontology Eukaryota
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DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.

Methods (San Diego, Calif.) Jun 6, 2018
As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to r...
Semantics Computational Biology Gene Ontology Proteins Eukaryota Data Mining Sequence Analysis, Protein Humans Machine Learning Animals
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