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Related Concept Videos

Bacterial Growth Curve01:28

Bacterial Growth Curve

The bacterial growth curve is a fundamental concept in microbiology that describes the dynamics of bacterial population growth in a closed system with controlled environmental conditions, such as temperature and nutrient availability. This curve is divided into four distinct phases: lag, log (exponential), stationary, and death phases, each reflecting a unique stage of bacterial adaptation and growth. During the lag phase, bacteria acclimate to their surroundings by synthesizing essential...
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Related Experiment Video

Updated: May 28, 2026

ScanLag: High-throughput Quantification of Colony Growth and Lag Time
07:47

ScanLag: High-throughput Quantification of Colony Growth and Lag Time

Published on: July 15, 2014

Modeling and estimating bacterial lag phase.

Peter Olofsson1, Xin Ma

  • 1Trinity University, Mathematics Department, One Trinity Place, San Antonio, TX 78212, United States. polofsso@trinity.edu

Mathematical Biosciences
|October 12, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a mathematical model for bacterial growth, specifically addressing the initial lag phase. The model aids in estimating bacterial population parameters using simulations for validation.

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ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth
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Last Updated: May 28, 2026

ScanLag: High-throughput Quantification of Colony Growth and Lag Time
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ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth
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ODELAY: A Large-scale Method for Multi-parameter Quantification of Yeast Growth

Published on: July 3, 2017

Area of Science:

  • Microbiology
  • Mathematical Biology
  • Population Dynamics

Background:

  • Bacterial growth dynamics are crucial in various biological and medical contexts.
  • Understanding the initial lag phase is essential for accurate population modeling.
  • Existing models may not fully capture the complexities of early-stage bacterial proliferation.

Purpose of the Study:

  • To develop a novel branching process model for bacterial populations.
  • To incorporate the initial lag phase into the bacterial growth model.
  • To establish approximations for facilitating parameter estimation within the model.

Main Methods:

  • Development of a branching process mathematical model.
  • Formulation of approximations to simplify parameter estimation.
  • Validation of the model and estimation techniques using simulated bacterial population data.

Main Results:

  • A functional branching process model for bacterial populations, including the lag phase, was successfully developed.
  • Approximations were established to enable practical parameter estimation.
  • Simulated data confirmed the validity of the developed approximations and estimation procedures.

Conclusions:

  • The developed branching process model provides a robust framework for studying bacterial population dynamics during the lag phase.
  • The established approximations offer an efficient method for parameter estimation in bacterial growth models.
  • This modeling approach is valuable for research in microbiology and related fields.