AIMC Topic: Eukaryota

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Improved ontology for eukaryotic single-exon coding sequences in biological databases.

Database : the journal of biological databases and curation Jan 1, 2018
Efficient extraction of knowledge from biological data requires the development of structured vocabularies to unambiguously define biological terms. This paper proposes descriptions and definitions to disambiguate the term 'single-exon gene'. Eukaryo...
Exons Open Reading Frames Databases, Genetic Base Sequence Protein Isoforms Gene Ontology Eukaryota
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SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification.

BMC bioinformatics Dec 15, 2016
BACKGROUND: snoReport uses RNA secondary structure prediction combined with machine learning as the basis to identify the two main classes of small nucleolar RNAs, the box H/ACA snoRNAs and the box C/D snoRNAs. Here, we present snoReport 2.0, which s...
Eukaryota Molecular Sequence Data RNA, Small Nucleolar Vertebrates Computational Biology Humans Animals Support Vector Machine Base Sequence
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Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

BMC bioinformatics Dec 15, 2016
BACKGROUND: MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays...
Animals Genomics Computational Biology Machine Learning Computer Simulation Eukaryota Genome MicroRNAs Plants Nucleic Acid Conformation Humans
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Comparison of module detection algorithms in protein networks and investigation of the biological meaning of predicted modules.

BMC bioinformatics Mar 18, 2016
BACKGROUND: It is generally acknowledged that a functional understanding of a biological system can only be obtained by an understanding of the collective of molecular interactions in form of biological networks. Protein networks are one particular n...
Humans Eukaryota Cluster Analysis Algorithms Gene Ontology Animals Protein Interaction Mapping
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TPpred3 detects and discriminates mitochondrial and chloroplastic targeting peptides in eukaryotic proteins.

Bioinformatics (Oxford, England) Jun 16, 2015
MOTIVATION: Molecular recognition of N-terminal targeting peptides is the most common mechanism controlling the import of nuclear-encoded proteins into mitochondria and chloroplasts. When experimental information is lacking, computational methods can...
Eukaryota Sequence Analysis, Protein Mitochondrial Proteins Chloroplast Proteins Chloroplasts Support Vector Machine Mitochondria Protein Transport Software Peptides Machine Learning
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An improved Artificial Protozoa Optimizer for CNN architecture optimization.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
In this paper, we propose a novel neural architecture search (NAS) method called MAPOCNN, which leverages an enhanced version of the Artificial Protozoa Optimizer (APO) to optimize the architecture of Convolutional Neural Networks (CNNs). The APO is ...
Algorithms Deep Learning Eukaryota Neural Networks, Computer
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VirDetect-AI: a residual and convolutional neural network-based metagenomic tool for eukaryotic viral protein identification.

Briefings in bioinformatics Nov 22, 2024
This study addresses the challenging task of identifying viruses within metagenomic data, which encompasses a broad array of biological samples, including animal reservoirs, environmental sources, and the human body. Traditional methods for virus ide...
Genome, Viral Viruses Viral Proteins Computational Biology Metagenomics Eukaryota Metagenome Humans Neural Networks, Computer Artificial Intelligence Convolutional Neural Networks
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Spatio-temporal changes of small protist and free-living bacterial communities in a temperate dimictic lake: insights from metabarcoding and machine learning.

FEMS microbiology ecology Jul 12, 2024
Microbial communities, which include prokaryotes and protists, play an important role in aquatic ecosystems and influence ecological processes. To understand these communities, metabarcoding provides a powerful tool to assess their taxonomic composit...
Temperature Ecosystem Lakes Machine Learning DNA Barcoding, Taxonomic Eukaryota Microbiota Biodiversity Seasons Spatio-Temporal Analysis Bacteria
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IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning.

GigaScience Jan 2, 2024
BACKGROUND: The virome obtained through virus-like particle enrichment contains a mixture of prokaryotic and eukaryotic virus-derived fragments. Accurate identification and classification of these elements are crucial to understanding their roles and...
Genome, Viral Viruses Eukaryota Deep Learning Computational Biology Prokaryotic Cells Virome Humans Software
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The dynamic trophic architecture of open-ocean protist communities revealed through machine-guided metatranscriptomics.

Proceedings of the National Academy of Sciences of the United States of America Feb 15, 2022
Intricate networks of single-celled eukaryotes (protists) dominate carbon flow in the ocean. Their growth, demise, and interactions with other microorganisms drive the fluxes of biogeochemical elements through marine ecosystems. Mixotrophic protists ...
Plankton Eukaryota Food Chain Oceans and Seas Machine Learning Gene Expression Profiling Models, Biological
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