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Updated: Jan 27, 2026

Mutagenesis and Functional Selection Protocols for Directed Evolution of Proteins in E. coli

Mutagenesis and Functional Selection Protocols for Directed Evolution of Proteins in E. coli

Published on: March 16, 2011

SANTA-SIM: simulating viral sequence evolution dynamics under selection and recombination.

Abbas Jariani^1,2, Christopher Warth³, Koen Deforche⁴

¹Laboratory for Genetics and Genomics, Center of Microbial and Plant Genetics, KU Leuven, Leuven, Belgium.

Virus Evolution

|March 14, 2019

Summary

This summary is machine-generated.

SANTA-SIM is a new software package for simulating gene sequence evolution. This tool models key biological processes, aiding in the analysis and comparison of evolutionary inference methods.

Keywords:

fitness mutation recombination selection simulation

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Area of Science:

Computational Biology
Evolutionary Genetics
Bioinformatics

Background:

Simulations are crucial for generating expectations and predictive distributions.
They are essential for comparing empirical data and testing inference methods.
Understanding evolutionary processes requires robust simulation tools.

Purpose of the Study:

To introduce SANTA-SIM, a novel software package for simulating forward-time population genetics.
To provide a user-friendly and cross-platform tool for evolutionary sequence simulation.
To facilitate the study of genetic evolution under various biological conditions.

Main Methods:

SANTA-SIM models discrete biological processes: replication, recombination, mutation (point, indel), and selection.
It incorporates diverse fitness models and population size dynamics.
The software is designed for intuitive use and cross-platform compatibility.

Main Results:

The package enables simulation of gene sequence evolution through discrete biological components.
It supports various selection models and population dynamics.
SANTA-SIM offers a flexible platform for evolutionary studies.

Conclusions:

SANTA-SIM provides a valuable tool for simulating and studying the evolutionary dynamics of gene sequences.
Its intuitive design and broad applicability enhance its utility for researchers in evolutionary biology and bioinformatics.
The software supports the testing and development of inference methods in population genetics.