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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.
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.
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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...
RNA-seq03:21

RNA-seq

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Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
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Protein Complex Assembly

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Related Experiment Video

Updated: Jun 9, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
12:08

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

Integrating genome assemblies with MAIA.

Jurgen Nijkamp1, Wynand Winterbach, Marcel van den Broek

  • 1Department of Mediamatics, Delft University of Technology, Delft, The Netherlands. j.f.nijkamp@tudelft.nl

Bioinformatics (Oxford, England)
|September 9, 2010
PubMed
Summary
This summary is machine-generated.

This study presents MAIA, an assembly integrator that combines multiple de novo assemblies and reference genomes for improved eukaryotic genome sequencing. MAIA significantly enhances contig number and coverage compared to single-assembly methods.

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Last Updated: Jun 9, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • De novo genome assembly using next-generation sequencing data presents significant challenges.
  • Existing assemblers are often specialized for specific sequencing data types.
  • The increasing availability of reference genomes enables comparative assembly approaches.

Purpose of the Study:

  • To develop an assembly integrator that leverages multiple data sources for improved genome assembly.
  • To optimize the combination of de novo assemblies and comparative mappings against related genomes.

Main Methods:

  • An assembly integrator algorithm was developed.
  • The algorithm optimizes a weighted combination of criteria from multiple de novo assemblies and comparative mappings.
  • MAIA was implemented as a Matlab package.

Main Results:

  • The algorithm was applied to the de novo sequencing of Saccharomyces cerevisiae CEN.PK 113-7D.
  • Integration of two de novo and three comparative assemblies using Solexa and 454 read data.
  • Resulted in 29 contigs covering over 12 Mbp, a substantial improvement over single assemblies.

Conclusions:

  • MAIA effectively integrates diverse assembly data for enhanced eukaryotic genome reconstruction.
  • The approach offers a significant improvement in contiguity and coverage compared to traditional methods.
  • MAIA is available as a downloadable Matlab package.