ArticleBMC bioinformatics2016
PRECOG: a tool for automated extraction and visualization of fitness components in microbial growth phenomics.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
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- Cell Population Dynamics Informed by Cell-Cycle Regulation: A Deterministic Modeling Toolkit.Computational and structural biotechnology journal · 2026Review
- Genomic adaptation of an autochthonous cider yeast strain to buckwheat and barley wort under stressful brewing conditions.Applied and environmental microbiology · 2025Article
- Genetic and phenotypic insights into Cyberlindnera jadinii as a promising yeast for industrial biotechnology.G3 (Bethesda, Md.) · 2025Article
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- gcplyr: an R package for microbial growth curve data analysis.BMC bioinformatics · 2024Article
- Engineering Saccharomyces cerevisiae for targeted hydrolysis and fermentation of glucuronoxylan through CRISPR/Cas9 genome editing.Microbial cell factories · 2024Article
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- Building synthetic chromosomes from natural DNA.Nature communications · 2023Article
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- Parsley: a web app for parsing data from plate readers.Bioinformatics (Oxford, England) · 2023Article
- A robust yeast biocontainment system with two-layered regulation switch dependent on unnatural amino acid.Nature communications · 2023Article
- System-wide optimization of an orthogonal translation system with enhanced biological tolerance.Molecular systems biology · 2023Article
- A high-throughput yeast approach to characterize aquaporin permeabilities: Profiling the Arabidopsis PIP aquaporin sub-family.Frontiers in plant science · 2023Article
- Growth Rate Evaluation of the Budding Yeast Saccharomyces cerevisiae Cells Carrying Endogenously Expressed Fluorescent Protein Fusions.Methods in molecular biology (Clifton, N.J.) · 2023Article
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Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPhenomics is a field in functional genomics that records variation in organismal phenotypes in the genetic, epigenetic or environmental context at a massive scale. For microbes, the key phenotype is the growth in population size because it contains information that is directly linked to fitness. Due to technical innovations and extensive automation our capacity to record complex and dynamic microbial growth data is rapidly outpacing our capacity to dissect and visualize this data and extract the fitness components it contains, hampering progress in all fields of microbiology.
resultsTo automate visualization, analysis and exploration of complex and highly resolved microbial growth data as well as standardized extraction of the fitness components it contains, we developed the software PRECOG (PREsentation and Characterization Of Growth-data). PRECOG allows the user to quality control, interact with and evaluate microbial growth data with ease, speed and accuracy, also in cases of non-standard growth dynamics. Quality indices filter high- from low-quality growth experiments, reducing false positives. The pre-processing filters in PRECOG are computationally inexpensive and yet functionally comparable to more complex neural network procedures. We provide examples where data calibration, project design and feature extraction methodologies have a clear impact on the estimated growth traits, emphasising the need for proper standardization in data analysis.
conclusionsPRECOG is a tool that streamlines growth data pre-processing, phenotypic trait extraction, visualization, distribution and the creation of vast and informative phenomics databases.
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