PoMeLo: a systematic computational approach to predicting metabolic loss in pathogen genomes
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
PoMeLo: a systematic computational approach to predicting metabolic loss in pathogen genomes ; volume:25 ; number:1 ; day:30 ; month:1 ; year:2024 ; pages:1-13 ; date:12.2024
BMC bioinformatics ; 25, Heft 1 (30.1.2024), 1-13, 12.2024
- Creator
-
Glascock, Abigail
Waltari, Eric
Dudas, Gytis
Wong, Joan
Ahyong, Vida
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s12859-024-05640-w
- URN
-
urn:nbn:de:101:1-2024041011333223079797
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:50 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Glascock, Abigail
- Waltari, Eric
- Dudas, Gytis
- Wong, Joan
- Ahyong, Vida
- SpringerLink (Online service)
Other Objects (12)
CaPSID: A bioinformatics platform for computational pathogen sequence identification in human genomes and transcriptomes
Metabolic properties of the human pathogen Enterococcus faecalis V583 investigated by computational modelling
Genetic analysis of ancient pathogen genomes from historic pandemics
Hybrid selection for sequencing pathogen genomes from clinical samples
Mining herbaria for plant pathogen genomes : back to the future
Computational investigations into the evolution of mitochondrial genomes
Computational evaluation of TIS annotation for prokaryotic genomes
Metabolic classification of microbial genomes using functional probes
Computational Approaches for Analyzing Ancient Genomes and Modern Metagenomes
Paired analysis of host and pathogen genomes identifies determinants of human tuberculosis
Mining cancer genomes for change-of-metabolic-function mutations
Predicting synthetic rescues in metabolic networks
CaPSID: A bioinformatics platform for computational pathogen sequence identification in human genomes and transcriptomes
Metabolic properties of the human pathogen Enterococcus faecalis V583 investigated by computational modelling
Genetic analysis of ancient pathogen genomes from historic pandemics
Hybrid selection for sequencing pathogen genomes from clinical samples
Mining herbaria for plant pathogen genomes : back to the future
Computational investigations into the evolution of mitochondrial genomes
Computational evaluation of TIS annotation for prokaryotic genomes
Metabolic classification of microbial genomes using functional probes
Computational Approaches for Analyzing Ancient Genomes and Modern Metagenomes
Paired analysis of host and pathogen genomes identifies determinants of human tuberculosis
Mining cancer genomes for change-of-metabolic-function mutations
Predicting synthetic rescues in metabolic networks
CaPSID: A bioinformatics platform for computational pathogen sequence identification in human genomes and transcriptomes
Metabolic properties of the human pathogen Enterococcus faecalis V583 investigated by computational modelling
Genetic analysis of ancient pathogen genomes from historic pandemics
Hybrid selection for sequencing pathogen genomes from clinical samples
Mining herbaria for plant pathogen genomes : back to the future
Computational investigations into the evolution of mitochondrial genomes
Computational evaluation of TIS annotation for prokaryotic genomes
Metabolic classification of microbial genomes using functional probes
Computational Approaches for Analyzing Ancient Genomes and Modern Metagenomes
Paired analysis of host and pathogen genomes identifies determinants of human tuberculosis
Mining cancer genomes for change-of-metabolic-function mutations