Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

An environmental perspective on large-scale genome clustering based on metabolic capabilities.

Bioinformatics (Oxford, England) - 15 Aug 2008

Kastenmüller Gabi, Gasteiger Johann, Mewes Hans-Werner

Abstract excerpt

MOTIVATION: In principle, an organism's ability to survive in a speci.c environment, is an observable result of the organism's regulatory and metabolic capabilities. Nonetheless, current knowledge about the global relation of the metabolisms and the niches of organisms is still limited. RESULTS:...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biological Evolution
Share to Chromosome Mapping
Share to Cluster Analysis

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Computer Simulation

Share to Environment

Share to Gene Expression Regulation

Share to Proteome

Share to Selection, Genetic

Source

Identifiers

PMID: 18689840
DOI: 10.1093/bioinformatics/btn302

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026. Prepared record publication-18689840-2026-09-02.2. Manifest publication-graph-cohort-2026-09-02.2.

Source receipt: PubMed via Helena Literature Corpus, retrieved 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

An environmental perspective on large-scale genome clustering based on metabolic capabilities.PMID 18689840Read ↗

A validated pangenome-scale metabolic model for the <i>Klebsiella pneumoniae</i> species complexSemantic proximity Read ↗

Niche-specific metabolic phenotypes can be used to identify antimicrobial targets in pathogens.Semantic proximity Read ↗

Reconstruction and exploitation of a dedicated Genome-Scale Metabolic Model of the human pathogen <i>C. neoformans</i>Semantic proximity Read ↗

IDENTIFICATION AND ANALYSIS OF BACTERIAL GENOMIC METABOLIC SIGNATURES.Semantic proximity Read ↗

Recommendation of: Comparative genomics of Rickettsiella bacteria reveal variable metabolic pathways potentially involved in symbiotic interactions with arthropods. Round#3Semantic proximity Read ↗

proGenomes2: an improved database for accurate and consistent habitat, taxonomic and functional annotations of prokaryotic genomes.Semantic proximity Read ↗

Phylogenomics of expanding uncultured environmental Tenericutes provides insights into their pathogenicity and evolutionary relationship with BacilliSemantic proximity Read ↗

Entamoeba histolytica: Observations on metabolism based on the genome sequenceSemantic proximity Read ↗

Core and panmetabolism in Escherichia coli.Semantic proximity Read ↗

Comparative genomic analysis reveals differential genomic characteristics and featured genes between rapid- and slow-growing non-tuberculous mycobacteriaSemantic proximity Read ↗

Metabolic Interactive Nodular Network for Omics (MINNO): Refining and investigating metabolic networks based on empirical metabolomics dataSemantic proximity Read ↗

Genomic diversity, population structure and accessory genome analysis of <i>Pasteurella multocida</i> : New Insights into host adaptation and disease specializationSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.