Search research articles

Related Concept Videos

Evolutionary Relationships through Genome Comparisons

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...

Epistasis Analysis

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

Organization of Genes

Organization of Genes

Organization of Genes

Organization of Genes

Genome Annotation and Assembly

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.

Synteny and Evolution

Synteny and Evolution

John H. Renwick first coined the term “synteny” in 1971, which refers to the genes present on the same chromosomes, even if they are not genetically linked. The species with common ancestry tend to show conserved syntenic regions. Therefore, the concept of synteny is nowadays used to describe the evolutionary relationship between species.
Around 80 million years ago, the human and mice lineages diverged from the common ancestor. During the course of evolution, the ancestral...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Influence of environmental factors on the tropical peatlands diazotrophic communities from the Southern Brazilian Atlantic Rain Forest.

Letters in applied microbiology·2021

Same author

Quantitative assessment of protein function prediction programs.

Genetics and molecular research : GMR·2016

Same author

Whole-Genome Sequence of Leptospira interrogans Serovar Hardjo Subtype Hardjoprajitno Strain Norma, Isolated from Cattle in a Leptospirosis Outbreak in Brazil.

Genome announcements·2015

Same author

Microbial community and performance of slaughterhouse wastewater treatment filters.

Genetics and molecular research : GMR·2014

Same author

Prokaryotic communities of acidic peatlands from the southern Brazilian Atlantic Forest.

Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]·2013

Same author

The RecX protein interacts with the RecA protein and modulates its activity in Herbaspirillum seropedicae.

Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas·2012

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Apr 16, 2026

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

Biosom: gene synonym analysis by self-organizing map.

K R Otemaier¹, M B R Steffens¹, R T Raittz²

¹Programa de Pós-Graduação em Bioinformática, Universidade Federal do Paraná, Curitiba, PR, Brasil.

Genetics and Molecular Research : GMR

|March 3, 2015

Summary

This study introduces a novel methodology to identify gene synonyms and reduce naming inconsistencies in biological databases. This approach enhances gene annotation and data mining by minimizing errors and standardizing gene names.

More Related Videos

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Related Experiment Videos

Last Updated: Apr 16, 2026

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps

Published on: October 28, 2018

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Published on: June 28, 2018

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Gene nomenclature guidelines exist but are inconsistently applied to new gene discoveries.
Lack of standardization leads to database errors like duplicate gene entries with different names, distinct genes with identical names, and ambiguous abbreviations.
These inconsistencies hinder accurate gene annotation and effective data mining in public biological databases.

Purpose of the Study:

To present a methodology for predicting gene synonyms and detecting naming redundancy and inconsistency.
To facilitate the annotation of newly identified genes and improve data mining in public databases.
To address issues of gene ambiguity and standardize gene naming conventions.

Main Methods:

Utilizes a Kohonen self-organizing map artificial neural network to group genes based on their names.
Employs the Matrix-U technique to identify and analyze the generated gene groups.
Applies these computational techniques to infer synonyms and predict potential gene names.

Main Results:

Successfully detected numerous errors related to gene nomenclature in existing databases.
Demonstrated the effectiveness of the methodology in identifying gene ambiguity and synonyms.
The approach can infer synonyms, predict hypothetical gene names, and highlight database record errors.

Conclusions:

The developed methodology effectively predicts gene synonyms, thereby minimizing naming redundancy and inconsistency.
This approach is valuable for annotating hypothetical and putative genes and can suggest functions for uncharacterized genes.
Standardizing gene nomenclature through synonym prediction is crucial for maintaining accurate and reliable biological databases.