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PCR01:32

PCR

Overview
Labeling DNA Probes03:31

Labeling DNA Probes

DNA probes are fragments of DNA labeled with a reporter tag to enable their detection or purification. The resulting labeled DNA probes can then hybridize to target nucleic acid sequences through complementary base-pairing, and may be used to recover or identify these regions.
Radioisotopes, fluorophores, or small molecule binding partners like biotin or digoxigenin, are the most widely used reporter tags for labeling DNA probes. These labels can be attached to the probe DNA molecule via...

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Related Experiment Video

Updated: May 30, 2026

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling
08:04

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

Published on: October 8, 2019

PTPan--overcoming memory limitations in oligonucleotide string matching for primer/probe design.

Tilo Eissler1, Christopher P Hodges, Harald Meier

  • 1Department of Informatics, Technische Universität München, Boltzmannstrasse 3, 85748 Garching, Germany.

Bioinformatics (Oxford, England)
|August 23, 2011
PubMed
Summary

We developed PTPan, a space-efficient index for approximate oligonucleotide matching, to handle massive nucleic acid data for primer design. It significantly reduces memory usage and construction time, enabling rapid analysis of growing sequence collections.

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Last Updated: May 30, 2026

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Nucleic acid diagnostics requires efficient exact and approximate oligonucleotide matching for primer/probe design.
  • Rapid growth of public sequence repositories outpaces hardware capabilities, challenging existing primer design tools.
  • Need for novel, space-efficient indexing structures to manage large-scale nucleic acid sequence data.

Purpose of the Study:

  • To develop a space-efficient indexing structure for approximate oligonucleotide string matching in large nucleic acid datasets.
  • To enable efficient primer/probe design and similarity searches on rapidly growing sequence collections.
  • To address the memory and computational limitations of existing bioinformatics tools.

Main Methods:

  • Developed PTPan, a novel indexing structure based on suffix trees.
  • Incorporated partitioning, truncation, and suffix tree stream compression for efficient data handling.
  • Implemented weighted Levenshtein distance for approximate queries, including indels and substitutions.

Main Results:

  • PTPan significantly reduces memory requirements compared to existing methods for large datasets like SILVA.
  • Achieved shorter construction times and extended functionality when integrated into the ARB software package.
  • Demonstrated efficient operation in both main memory and on secondary storage, balancing performance and resource usage.

Conclusions:

  • PTPan enables effective indexing of massive nucleic acid sequence collections with reasonable response times.
  • It overcomes main memory limitations, advancing rapid oligonucleotide string matching for primer/probe design.
  • PTPan is a crucial advancement for future molecular sequence data analysis, accommodating exponential growth.