ArticleAdvances in bioinformatics2011
Generation and Analysis of Large-Scale Data-Driven Mycobacterium tuberculosis Functional Networks for Drug Target Identification.
Article in Advances in bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Reviewing and assessing existing meta-analysis models and tools.Briefings in bioinformatics · 2021Pooled it
- Dissecting Meta-Analysis in GWAS Era: Bayesian Framework for Gene/Subnetwork-Specific Meta-Analysis.Frontiers in genetics · 2022Article
- Network-driven analysis of human-Plasmodium falciparum interactome: processes for malaria drug discovery and extracting in silico targets.Malaria journal · 2021Article
- IHP-PING-generating integrated human protein-protein interaction networks on-the-fly.Briefings in bioinformatics · 2021Article
- Identifying genetic variants and pathways associated with extreme levels of fetal hemoglobin in sickle cell disease in Tanzania.BMC medical genetics · 2020Article
- Post genome-wide association analysis: dissecting computational pathway/network-based approaches.Briefings in bioinformatics · 2019Review
- A post-gene silencing bioinformatics protocol for plant-defence gene validation and underlying process identification: case study of the Arabidopsis thaliana NPR1.BMC plant biology · 2017Article
- Decoding the similarities and differences among mycobacterial species.PLoS neglected tropical diseases · 2017Article
- ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations.Bioinformatics (Oxford, England) · 2016Article
- A Quantitative Approach to Analyzing Genome Reductive Evolution Using Protein-Protein Interaction Networks: A Case Study of Mycobacterium leprae.Frontiers in genetics · 2016Article
- Maximum flow approach to prioritize potential drug targets of Mycobacterium tuberculosis H37Rv from protein-protein interaction network.Clinical and translational medicine · 2015Article
- Comparative Genome and Network Centrality Analysis to Identify Drug Targets of Mycobacterium tuberculosis H37Rv.BioMed research international · 2015Article
- Using biological networks to improve our understanding of infectious diseases.Computational and structural biotechnology journal · 2014Review
- DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures.BMC bioinformatics · 2013Article
- Latent Tuberculosis: Models, Computational Efforts and the Pathogen's Regulatory Mechanisms during Dormancy.Frontiers in bioengineering and biotechnology · 2013Review
- Predicting and analyzing interactions between Mycobacterium tuberculosis and its human host.PloS one · 2013Article
- Translating basic science insight into public health action for multidrug- and extensively drug-resistant tuberculosis.Respirology (Carlton, Vic.) · 2012Review
- Function prediction and analysis of mycobacterium tuberculosis hypothetical proteins.International journal of molecular sciences · 2012Article
- A topology-based metric for measuring term similarity in the gene ontology.Advances in bioinformatics · 2012Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Technological developments in large-scale biological experiments, coupled with bioinformatics tools, have opened the doors to computational approaches for the global analysis of whole genomes. This has provided the opportunity to look at genes within their context in the cell. The integration of vast amounts of data generated by these technologies provides a strategy for identifying potential drug targets within microbial pathogens, the causative agents of infectious diseases. As proteins are druggable targets, functional interaction networks between proteins are used to identify proteins essential to the survival, growth, and virulence of these microbial pathogens. Here we have integrated functional genomics data to generate functional interaction networks between Mycobacterium tuberculosis proteins and carried out computational analyses to dissect the functional interaction network produced for identifying drug targets using network topological properties. This study has provided the opportunity to expand the range of potential drug targets and to move towards optimal target-based strategies.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.