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Related Concept Videos

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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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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Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Related Experiment Video

Updated: Jun 29, 2026

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
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Efficient mapping of Applied Biosystems SOLiD sequence data to a reference genome for functional genomic

Brian D Ondov1, Anjana Varadarajan, Karla D Passalacqua

  • 1School of Biology, Georgia Institute of Technology, 310 Ferst Dr., Atlanta, GA 30332-0230, USA.

Bioinformatics (Oxford, England)
|October 10, 2008
PubMed
Summary
This summary is machine-generated.

We developed SOCS (short oligonucleotide color space), a program for mapping SOLiD sequence data to genomes. This tool enhances data usability by allowing mismatches and supports functional genomics applications like transcriptome profiling and ChIP-Seq.

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Applied Biosystems SOLiD sequencing technology generates data in 'color space'.
  • Efficient mapping of this data to reference genomes is crucial for functional genomics.

Purpose of the Study:

  • To develop a program for efficient and flexible mapping of SOLiD sequence data.
  • To maximize usable sequence data by incorporating a user-specified mismatch allowance.
  • To facilitate functional genomics applications using sequence mapping.

Main Methods:

  • Development of the SOCS (short oligonucleotide color space) program.
  • Implementation of 'color space' mapping for SOLiD data.
  • Inclusion of user-specified mismatch parameters to optimize data utilization.

Main Results:

  • SOCS enables efficient and flexible mapping of SOLiD sequence data.
  • The program maximizes usable data through adjustable mismatch allowances.
  • Sequence census functions are integrated for downstream applications.

Conclusions:

  • SOCS provides a valuable tool for analyzing SOLiD sequencing data.
  • The program supports diverse functional genomics applications, including transcriptome analysis and ChIP-Seq.
  • Availability of source code and data facilitates adoption and further development.