Automated Fragment Analysis

Automated fragment analysis is a molecular biology technique that separates and measures DNA fragments to characterize genetic variation, identify alleles, or assess nucleic acid products. Fluorescently labeled fragments migrate through a capillary filled with polymer, and an instrument detects their signal relative to an internal size standard to determine fragment length and generate an electropherogram. Software then assigns allele sizes or profiles based on fluorescence peaks, reducing manual interpretation and improving throughput. The method supports genotyping, short tandem repeat analysis, mutation screening, DNA fingerprinting, and quality control in research, forensic, and diagnostic workflows.

Automated Fragment Analysis - Related Videos

Research

JoVE EoE - Cancers of the Nervous System

Automated Capillary Electrophoresis Based Fragment Size Distribution Analysis of cfDNA: A DNA Microchip-based Method to Study Size Distribution of DNA Fragments Isolated from Biofluids

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2025

In this video, we analyze the size distribution of cell-free DNA or cfDNA fragments using automated capillary electrophoresis. This technique helps gain insights into the profile of DNA fragments released by cancer cells during apoptosis.

Research

JoVE Journal - Immunology and Infection
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Automated Analysis of Intracellular Phenotypes of Salmonella Using ImageJ

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Cited by 3 •

2022

Salmonella invades and replicates inside intestinal epithelial cells both in Salmonella-specific vacuoles and free in the cytosol (hyper-replication). A high-throughput fluorescence microscopy-based protocol is described here to quantify the intracellular phenotypes of Salmonella by two complementary image analyses through ImageJ, reaching single-cell resolution and scoring.

Research

JoVE Journal - Biology
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Electroeluting DNA Fragments

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Cited by 8 •

2010

This procedure allows the purification of DNA fragments with high yield.

Automated Analysis of C. elegans Fluorescence Images using SegElegans

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2025

Here we provide instructions on effectively utilizing SegElegans, a deep learning system we developed for the automated segmentation of individual worms in widefield microscopy images, for subsequent use in image analysis software such as ImageJ. We provide ways to use the system both online and offline.

Research

JoVE Journal - Neuroscience
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Automated Analysis of C. elegans Swim Behavior Using CeleST Software

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Cited by 17 •

2016

An efficient and simple methodology for computer-based analysis of nematode swimming behavior in liquid is described. The method requires little to no investment for C. elegans laboratories. The hardware used is standard, and the computer software for the behavioral analysis (CeleST) is an open source one.

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