ArticleDatabase : the journal of biological databases and curation2014
IFIM: a database of integrated fitness information for microbial genes.
Article in Database : the journal of biological databases and curation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Adaptation of commensal proliferatingProceedings of the National Academy of Sciences of the United States of America · 2018Article
- Selection for energy efficiency drives strand-biased gene distribution in prokaryotes.Scientific reports · 2017Article
- Genomic Complexity Places Less Restrictions on the Evolution of Young Coexpression Networks than Protein-Protein Interactions.Genome biology and evolution · 2016Article
- Essentiality drives the orientation bias of bacterial genes in a continuous manner.Scientific reports · 2015Article
- Comparative analysis of essential genes in prokaryotic genomic islands.Scientific reports · 2015Article
- ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes.Nucleic acids research · 2015Article
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Authors and funding
6 authors.
Funding
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Abstract
Knowledge of an organism's fitness for survival is important for a complete understanding of microbial genetics and effective drug design. Current essential gene databases provide only binary essentiality data from genome-wide experiments. We therefore developed a new database that Integrates quantitative Fitness Information for Microbial genes (IFIM). The IFIM database currently contains data from 16 experiments and 2186 theoretical predictions. The highly significant correlation between the experiment-derived fitness data and our computational simulations demonstrated that the computer-generated predictions were often as reliable as the experimental data. The data in IFIM can be accessed easily, and the interface allows users to browse through the gene fitness information that it contains. IFIM is the first resource that allows easy access to fitness data of microbial genes. We believe this database will contribute to a better understanding of microbial genetics and will be useful in designing drugs to resist microbial pathogens, especially when experimental data are unavailable. Database URL: http://cefg.uestc.edu.cn/ifim/ or http://cefg.cn/ifim/
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