Identifying essential genes in bacterial metabolic networks with machine learning methods
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1752-0509
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Identifying essential genes in bacterial metabolic networks with machine learning methods ; volume:4 ; number:1 ; day:3 ; month:5 ; year:2010 ; pages:1-16 ; date:12.2010
BMC systems biology ; 4, Heft 1 (3.5.2010), 1-16, 12.2010
- Creator
- Contributor
- DOI
-
10.1186/1752-0509-4-56
- URN
-
urn:nbn:de:1111-2016072955669
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:47 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
- Kitiporn Plaimas
- Eils, Roland
- König, Rainer
- SpringerLink (Online service)
Other Objects (12)
3D reconstruction, mathematical modeling and simulation of chromatin structures in cell nuclei
Comprehensive analysis of background modeling for non-coding mutations and regulatory impact of mutations in human genome
Supervised and unsupervised analyses in next generation sequencing data
siRNA high-content screening of 3D cultured MCF10A spheroids probing breast tumorigenesis
Systems Biological Analysis of Signal Transduction in Telomere Length Maintenance
Molecular Mechanism of Chromosome Segregation by the E. coli Min system
Performance comparison of four human whole-genome sequencing technologies
Segmentation-free inference of cell types from in situ transcriptomics data
An interaction-based modeling approach to predict response to cancer drugs
Identification of pathogenic virus sequences in pancreatic ductal adenocarcinoma
Uncovering the mechanisms and information content of CpG-resolved DNA methylation programming during hematopoietic differentiation
Optimization of strategies for overcoming therapy resistance in pancreatic cancer chemotherapy by mathematical modelling
3D reconstruction, mathematical modeling and simulation of chromatin structures in cell nuclei
Comprehensive analysis of background modeling for non-coding mutations and regulatory impact of mutations in human genome
Supervised and unsupervised analyses in next generation sequencing data
siRNA high-content screening of 3D cultured MCF10A spheroids probing breast tumorigenesis
Systems Biological Analysis of Signal Transduction in Telomere Length Maintenance
Molecular Mechanism of Chromosome Segregation by the E. coli Min system
Performance comparison of four human whole-genome sequencing technologies
Segmentation-free inference of cell types from in situ transcriptomics data
An interaction-based modeling approach to predict response to cancer drugs
Identification of pathogenic virus sequences in pancreatic ductal adenocarcinoma
Uncovering the mechanisms and information content of CpG-resolved DNA methylation programming during hematopoietic differentiation
Optimization of strategies for overcoming therapy resistance in pancreatic cancer chemotherapy by mathematical modelling
3D reconstruction, mathematical modeling and simulation of chromatin structures in cell nuclei
Comprehensive analysis of background modeling for non-coding mutations and regulatory impact of mutations in human genome
Supervised and unsupervised analyses in next generation sequencing data
siRNA high-content screening of 3D cultured MCF10A spheroids probing breast tumorigenesis
Systems Biological Analysis of Signal Transduction in Telomere Length Maintenance
Molecular Mechanism of Chromosome Segregation by the E. coli Min system
Performance comparison of four human whole-genome sequencing technologies
Segmentation-free inference of cell types from in situ transcriptomics data
An interaction-based modeling approach to predict response to cancer drugs
Identification of pathogenic virus sequences in pancreatic ductal adenocarcinoma
Uncovering the mechanisms and information content of CpG-resolved DNA methylation programming during hematopoietic differentiation