CYPminer: an automated cytochrome P450 identification, classification, and data analysis tool for genome data sets across kingdoms

Autor: Carl E. Cerniglia, Seong Won Nho, Dong-Heon Baek, Mark Hart, Young-Chang Kim, Wenjun Wang, Jung-Whan Chon, Jae Hyun Kim, John B. Sutherland, Seong-Jae Kim, Ohgew Kweon, Dongryeoul Bae, Sung-Kwan Kim
Jazyk: angličtina
Rok vydání: 2020
Předmět:
CYP co-occurrence network
Data analysis
Cytochrome P450
Computational biology
Bacterial genome size
CYP identification
urologic and male genital diseases
lcsh:Computer applications to medicine. Medical informatics
Biochemistry
Genome
digestive system
DNA sequencing
Automation
User-Computer Interface
03 medical and health sciences
Cytochrome P-450 Enzyme System
Structural Biology
Databases
Genetic
Cluster Analysis
Gene Regulatory Networks
heterocyclic compounds
Cluster analysis
Molecular Biology
lcsh:QH301-705.5
Phylogeny
030304 developmental biology
0303 health sciences
biology
030306 microbiology
Applied Mathematics
Fungi
Genome project
respiratory system
Computer Science Applications
enzymes and coenzymes (carbohydrates)
CYP classification
Pan-CYPome
lcsh:Biology (General)
biology.protein
lcsh:R858-859.7
Identification (biology)
DNA microarray
Software
Python
Zdroj: BMC Bioinformatics, Vol 21, Iss 1, Pp 1-11 (2020)
BMC Bioinformatics
ISSN: 1471-2105
DOI: 10.1186/s12859-020-3473-2
Popis: Background Cytochrome P450 monooxygenases (termed CYPs or P450s) are hemoproteins ubiquitously found across all kingdoms, playing a central role in intracellular metabolism, especially in metabolism of drugs and xenobiotics. The explosive growth of genome sequencing brings a new set of challenges and issues for researchers, such as a systematic investigation of CYPs across all kingdoms in terms of identification, classification, and pan-CYPome analyses. Such investigation requires an automated tool that can handle an enormous amount of sequencing data in a timely manner. Results CYPminer was developed in the Python language to facilitate rapid, comprehensive analysis of CYPs from genomes of all kingdoms. CYPminer consists of two procedures i) to generate the Genome-CYP Matrix (GCM) that lists all occurrences of CYPs across the genomes, and ii) to perform analyses and visualization of the GCM, including pan-CYPomes (pan- and core-CYPome), CYP co-occurrence networks, CYP clouds, and genome clustering data. The performance of CYPminer was evaluated with three datasets from fungal and bacterial genome sequences. Conclusions CYPminer completes CYP analyses for large-scale genomes from all kingdoms, which allows systematic genome annotation and comparative insights for CYPs. CYPminer also can be extended and adapted easily for broader usage.
Databáze: OpenAIRE
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