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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...

Modern Molecular Taxonomy

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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Updated: May 9, 2026

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Workflow management systems for gene sequence analysis and evolutionary studies - A Review.

Anu Sharma¹, Anil Rai, Sb Lal

¹Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi - 110012.

|August 10, 2013

Summary

The post-genomic era presents challenges in bioinformatics due to numerous databases and tools. This article reviews workflow management systems for gene sequence analysis and phylogeny, aiding researchers in computational biology.

Keywords:

Analysis bioinformatics databases integration phylogeny workflows

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Published on: December 22, 2017

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

The post-genomic era has led to a proliferation of biological databases and analytical tools.
Managing and analyzing vast amounts of data from large sequencing projects is complex.
Heterogeneous data sources and tools hinder efficient information access and analysis for researchers.

Purpose of the Study:

To address the challenge of integrating diverse bioinformatics databases and tools.
To describe bioinformatics analysis workflow management systems specifically for gene sequence analysis and phylogeny.
To provide a resource for researchers in computational biology and bioinformatics.

Main Methods:

Review and description of existing bioinformatics analysis workflow management systems.
Focus on systems relevant to gene sequence analysis and phylogenetic analysis.
Discussion of integration challenges for databases, tools, and algorithms.

Main Results:

Identification of various workflow management systems in bioinformatics.
Highlighting the importance of integration for efficient data analysis.
Demonstrating the application of these systems in gene sequence and phylogenetic analysis.

Conclusions:

Integrated bioinformatics platforms are crucial for overcoming data access and analysis challenges.
Workflow management systems offer solutions for streamlining gene sequence and phylogenetic analyses.
This review serves as a valuable guide for biotechnologists, molecular biologists, computer scientists, and statisticians.