AIMC Topic: Archaea

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Effect of sequence padding on the performance of deep learning models in archaeal protein functional prediction.

Scientific reports
The use of raw amino acid sequences as input for deep learning models for protein functional prediction has gained popularity in recent years. This scheme obliges to manage proteins with different lengths, while deep learning models require same-shap...

Machine-learning approach expands the repertoire of anti-CRISPR protein families.

Nature communications
The CRISPR-Cas are adaptive bacterial and archaeal immunity systems that have been harnessed for the development of powerful genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechani...

Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

Microbiome
BACKGROUND: Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene t...

Changes in bacterial and archaeal communities during the concentration of brine at the graduation towers in Ciechocinek spa (Poland).

Extremophiles : life under extreme conditions
This study evaluates the changes in bacterial and archaeal community structure during the gradual evaporation of water from the brine (extracted from subsurface Jurassic deposits) in the system of graduation towers located in Ciechocinek spa, Poland....

SILVA, RDP, Greengenes, NCBI and OTT - how do these taxonomies compare?

BMC genomics
BACKGROUND: A key step in microbiome sequencing analysis is read assignment to taxonomic units. This is often performed using one of four taxonomic classifications, namely SILVA, RDP, Greengenes or NCBI. It is unclear how similar these are and how to...

Microbial community redundancy in anaerobic digestion drives process recovery after salinity exposure.

Water research
Anaerobic digestion of high-salinity wastewaters often results in process inhibition due to the susceptibility of the methanogenic archaea. The ability of the microbial community to deal with increased salinity levels is of high importance to ensure ...

MicrO: an ontology of phenotypic and metabolic characters, assays, and culture media found in prokaryotic taxonomic descriptions.

Journal of biomedical semantics
BACKGROUND: MicrO is an ontology of microbiological terms, including prokaryotic qualities and processes, material entities (such as cell components), chemical entities (such as microbiological culture media and medium ingredients), and assays. The o...

Pre_GI: a global map of ontological links between horizontally transferred genomic islands in bacterial and archaeal genomes.

Database : the journal of biological databases and curation
The Predicted Genomic Islands database (Pre_GI) is a comprehensive repository of prokaryotic genomic islands (islands, GIs) freely accessible at http://pregi.bi.up.ac.za/index.php. Pre_GI, Version 2015, catalogues 26 744 islands identified in 2407 ba...

Deepdefense: annotation of immune systems in prokaryotes using deep learning.

GigaScience
BACKGROUND: Due to a constant evolutionary arms race, archaea and bacteria have evolved an abundance and diversity of immune responses to protect themselves against phages. Since the discovery and application of CRISPR-Cas adaptive immune systems, nu...

iDeLUCS: a deep learning interactive tool for alignment-free clustering of DNA sequences.

Bioinformatics (Oxford, England)
SUMMARY: We present an interactive Deep Learning-based software tool for Unsupervised Clustering of DNA Sequences (iDeLUCS), that detects genomic signatures and uses them to cluster DNA sequences, without the need for sequence alignment or taxonomic ...