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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.
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
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Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

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Updated: May 19, 2026

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
08:09

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

A sensitive method for computing GO-based functional similarities among genes with 'shallow annotation'.

Xiujie Chen1, Ruizhi Yang, Jiankai Xu

  • 1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. chenxiujie@ems.hrbmu.edu.cn

Gene
|August 21, 2012
PubMed
Summary

A new method for computing gene functional similarity using Gene Ontology (GO) annotations improves accuracy, especially for genes with shallow annotations. This approach offers reliable gene similarity distinctions and correlates well with sequence and EC similarities.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Gene functional similarity computation is crucial for gene clustering, expression analysis, and protein interaction prediction.
  • Current methods comparing Gene Ontology (GO) annotations often neglect GO term specificity and structure, leading to poor performance with shallow annotations.

Purpose of the Study:

  • To develop a novel method for computing gene functional similarity based on GO annotations.
  • To address limitations of existing methods, particularly their weakness with shallowly annotated genes.

Main Methods:

  • Proposed a new computational method for assessing functional similarity between genes using their GO annotations.
  • Compared the performance of the new method against the established G-SESAME method.

Main Results:

  • The new method reliably distinguishes functional similarities among genes.
  • The method demonstrates particular sensitivity and improved performance for genes with shallow annotations.
  • Achieved high correlations with sequence similarity and EC (Enzyme Commission number) similarity.

Conclusions:

  • The developed method offers a more robust approach to calculating gene functional similarity.
  • This method enhances the analysis of genes with limited GO annotations, improving biological insights.