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Related Concept Videos

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...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

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.
In contrast, regions which code...
Convergent Evolution01:54

Convergent Evolution

Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.
Evolutionary Processes in Microbes01:26

Evolutionary Processes in Microbes

Microbial evolution occurs rapidly due to short generation times and a variety of genetic processes, including horizontal gene transfer, mutation, recombination, and genetic drift. These mechanisms collectively enable microbes to adapt swiftly to changing environments.Horizontal gene transfer (HGT) allows genes to move between different species and occurs through three main mechanisms: conjugation, transformation, and transduction. Conjugation involves direct cell-to-cell contact for DNA...
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...

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A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq
07:09

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

Published on: May 28, 2021

Parallel evolutionary computation in bioinformatics applications.

Jorge Pinho1, João Luis Sobral, Miguel Rocha

  • 1Computer Sciences and Technologies Center (CCTC), Universidade do Minho, Dep. Informática - Campus de Gualtar - 4710-057 Braga, Portugal. jmpinho@di.uminho.pt

Computer Methods and Programs in Biomedicine
|November 7, 2012
PubMed
Summary
This summary is machine-generated.

ParJECoLi is a Java library offering metaheuristic methods for complex bioinformatics optimization problems. It enables efficient execution on various parallel architectures, simplifying computational challenges.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Computer Science

Background:

  • Bioinformatics optimization problems are often NP-hard, requiring significant computational resources.
  • Efficient execution on parallel architectures is crucial for tackling these complex problems.

Purpose of the Study:

  • To introduce ParJECoLi, a Java-based library for optimization in bioinformatics.
  • To provide a user-friendly platform for efficient execution of metaheuristic methods on diverse parallel architectures.

Main Methods:

  • Development of a Java library (ParJECoLi) offering various metaheuristic methods.
  • Utilization of Aspect-Oriented Programming for transparent adaptation to multicore, cluster, and grid environments.
  • Implementation of pluggable parallelism modules for user-configurable environments.

Main Results:

  • ParJECoLi facilitates the independent development of optimization algorithms and their parallel execution.
  • The library ensures ease of use, abstracting the complexity of different parallel architectures.
  • Performance validation through two case studies in biological model optimization.

Conclusions:

  • ParJECoLi offers a flexible and efficient solution for complex bioinformatics optimization tasks.
  • The library's design promotes ease of use and adaptability across various parallel computing environments.
  • This approach simplifies the application of advanced optimization techniques in biological research.