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Related Concept Videos

Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Related Experiment Video

Updated: Jun 24, 2026

Parallel High Throughput Single Molecule Kinetic Assay for Site-Specific DNA Cleavage
06:51

Parallel High Throughput Single Molecule Kinetic Assay for Site-Specific DNA Cleavage

Published on: May 6, 2020

CotQuest: improved algorithm and software for nonlinear regression analysis of DNA reassociation kinetics data.

John Bunge1, Philippe Chouvarine, Daniel G Peterson

  • 1Department of Statistical Science, Cornell University, Ithaca, NY 14853, USA.

Analytical Biochemistry
|March 17, 2009
PubMed
Summary

Cot analysis (DNA reassociation kinetics) is crucial for genome studies but uses outdated tools. A new nonlinear regression procedure, CotQuest, offers improved analysis of Cot data, enhancing genome structure and diversity evaluations.

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06:51

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Published on: October 1, 2017

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Cot analysis, based on DNA reassociation kinetics, is vital for understanding genome structure, similarity, and ecological diversity.
  • Existing computational tools for Cot data analysis are outdated, difficult to use, and prone to errors, hindering research progress.

Purpose of the Study:

  • To introduce a novel nonlinear regression procedure for analyzing Cot data.
  • To develop and present CotQuest, a suite of SAS scripts implementing this new procedure.
  • To provide an improved, user-friendly tool for accurate Cot data analysis.

Main Methods:

  • Implementation of a nonlinear regression procedure within the SAS statistical package.
  • Development of a novel algorithm that iteratively refines model complexity without requiring initial parameter guesses.
  • Integration of model comparison, assessment, and selection diagnostics for robust analysis.

Main Results:

  • CotQuest offers a sophisticated approach to Cot data analysis, overcoming limitations of previous methods.
  • The software automatically generates starting values for parameter estimation through a stepwise model progression.
  • Provides statistical comparisons and diagnostic tools to aid in selecting the most appropriate model for Cot curves.

Conclusions:

  • CotQuest represents a significant advancement in the computational analysis of DNA reassociation kinetics data.
  • The tool enhances the accuracy and reliability of genome structure and diversity studies.
  • Facilitates more informed model selection through integrated statistical and visual assessment tools.