ArticlemSystems2021
AMiGA: Software for Automated Analysis of Microbial Growth Assays.
Article in mSystems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 65 citations in OpenAlex.
- Selective sugar transport supports Proteus mirabilis fitness in the urinary tract.PLoS pathogens · 2026Article
- Shifts in soil microbiome surrounding a thermal treatment facility for hazardous waste: the hidden impact of environmentally persistent free radicals.Environmental science. Processes & impacts · 2026Article
- Rapid Adaptive Evolution under Combination Therapy inACS infectious diseases · 2026Article
- Mixing Is Dispensable for Optical Density-Based High-Throughput Growth Screening Assay in Fission Yeast.International journal of molecular sciences · 2026Article
- Investigating uncharacterised genes in Saccharomyces cerevisiae using robot scientists.Scientific reports · 2026Article
- Widespread effects of catecholamines on growth of human gut bacteria.NPJ biofilms and microbiomes · 2026Article
- Functionally distinct core microbes of Tricholoma matsutake revealed by cross-study analysis.Microbiome · 2026Article
- Characterization of the clade 4 non-toxigenicFEMS microbes · 2026Article
- Accurate monitoring of substrate-dependent growth reveals ecotypic differentiation among marine yeasts.ISME communications · 2026Article
- Cobamide-based interactions between soil bacteria can be predicted based on monoculture growth.bioRxiv : the preprint server for biology · 2025Article
- Translating microbial kinetics into quantitative responses and testable hypotheses using Kinbiont.Nature communications · 2025Article
- Vancomycin-resistant enterococci utilise antibiotic-enriched nutrients for intestinal colonisation.Nature communications · 2025Article
- A Pair of Promiscuous Surrogates forBiochemistry · 2025Article
- EmergingmSystems · 2025Article
- Control ofmBio · 2025Article
- Laboratory evolution ofJournal of bacteriology · 2025Article
- Less is more: the lack of autoinducer-2-dependent quorum sensing promotes competitive fitness ofFrontiers in cellular and infection microbiology · 2025Article
- Welly: a web-tool for visualizing growth curves from microplate data.Bioinformatics advances · 2025Article
- Influence of Temperature and Saline Conditions on Bacteria Naturally Associated With the Cnidarian HostInternational journal of microbiology · 2025Article
- Genetic and phenotypic changes to Venezuelan equine encephalitis virus following treatment with β-D-N4-hydroxycytidine, an RNA mutagen.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The analysis of microbial growth is one of the central methods in the field of microbiology. Microbial growth dynamics can be characterized by meaningful parameters, including carrying capacity, exponential growth rate, and growth lag. However, microbial assays with clinical isolates, fastidious organisms, or microbes under stress often produce atypical growth shapes that do not follow the classical microbial growth pattern. Here, we introduce the analysis of microbial growth assays (AMiGA) software, which streamlines the analysis of growth curves without any assumptions about their shapes. AMiGA can pool replicates of growth curves and infer summary statistics for biologically meaningful growth parameters. In addition, AMiGA can quantify death phases and characterize diauxic shifts. It can also statistically test for differential growth under distinct experimental conditions. Altogether, AMiGA streamlines the organization, analysis, and visualization of microbial growth assays.
Indexed as
Identifiers
What OpenQuestion holds
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.