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Eukaryota

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Machine learning for discovering missing or wrong protein function annotations : A comparison using updated benchmark datasets.

BMC bioinformatics
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...

Hereditary disease prediction in eukaryotic DNA: an adaptive signal processing approach.

Nucleosides, nucleotides & nucleic acids
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...

ProNA2020 predicts protein-DNA, protein-RNA, and protein-protein binding proteins and residues from sequence.

Journal of molecular biology
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...

Identifying genomic islands with deep neural networks.

BMC genomics
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...

SubLocEP: a novel ensemble predictor of subcellular localization of eukaryotic mRNA based on machine learning.

Briefings in bioinformatics
MOTIVATION: mRNA location corresponds to the location of protein translation and contributes to precise spatial and temporal management of the protein function. However, current assignment of subcellular localization of eukaryotic mRNA reveals import...

Tiara: deep learning-based classification system for eukaryotic sequences.

Bioinformatics (Oxford, England)
MOTIVATION: With a large number of metagenomic datasets becoming available, eukaryotic metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear and organellar genomes is an essential step toward a better understanding ...

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
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 ...

Machine learning-aided scoring of synthesis difficulties for designer chromosomes.

Science China. Life sciences
Designer chromosomes are artificially synthesized chromosomes. Nowadays, these chromosomes have numerous applications ranging from medical research to the development of biofuels. However, some chromosome fragments can interfere with the chemical syn...