Mining large-scale response networks reveals 'topmost activities' in Mycobacterium tuberculosis infection.
about
A multi-scale approach to designing therapeutics for tuberculosisThe application of transcriptional blood signatures to enhance our understanding of the host response to infection: the example of tuberculosis.Meta-analysis of host response networks identifies a common core in tuberculosis.DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human InteractionsExpression profiling of lymph nodes in tuberculosis patients reveal inflammatory milieu at site of infection.Unbiased Identification of Blood-based Biomarkers for Pulmonary Tuberculosis by Modeling and Mining Molecular Interaction Networks.Comparative Proteomics Analysis of Human Macrophages Infected with Virulent Mycobacterium bovisImproved understanding of pathogenesis from protein interactions in Mycobacterium tuberculosis.Macrophage defense mechanisms against intracellular bacteria.Efficacy of β-lactam/β-lactamase inhibitor combination is linked to WhiB4-mediated changes in redox physiology of Mycobacterium tuberculosis.Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach.A Systems Perspective of Signalling Networks in Host–Pathogen Interactions
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P2860
Mining large-scale response networks reveals 'topmost activities' in Mycobacterium tuberculosis infection.
description
2013 nî lūn-bûn
@nan
2013年の論文
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2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
2013年论文
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2013年论文
@zh-cn
name
Mining large-scale response ne ...... terium tuberculosis infection.
@en
type
label
Mining large-scale response ne ...... terium tuberculosis infection.
@en
prefLabel
Mining large-scale response ne ...... terium tuberculosis infection.
@en
P2860
P356
P1433
P1476
Mining large-scale response ne ...... terium tuberculosis infection.
@en
P2093
Awanti Sambarey
Karyala Prashanthi
P2860
P2888
P356
10.1038/SREP02302
P407
P577
2013-01-01T00:00:00Z