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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.
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...
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...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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Related Experiment Video

Updated: Jun 4, 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

Omics data management and annotation.

Arye Harel1, Irina Dalah, Shmuel Pietrokovski

  • 1Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.

Methods in Molecular Biology (Clifton, N.J.)
|March 4, 2011
PubMed
Summary
This summary is machine-generated.

Effective data management is crucial for handling the vast amounts of information generated by omics technologies. Implementing robust systems ensures data integrity, security, and knowledge extraction for scientific advancement.

Related Experiment Videos

Last Updated: Jun 4, 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

Area of Science:

  • Bioinformatics
  • Genomics
  • Data Science

Background:

  • Omics technologies like next-generation sequencing generate massive datasets.
  • Effective data management is essential for maintaining data integrity, security, and extracting maximum knowledge.

Purpose of the Study:

  • To outline key principles and considerations for managing omics data.
  • To illustrate these principles using the GeneCards omics project as a case study.

Main Methods:

  • Defining data management system requirements (flexibility, user-friendliness, standards, robustness).
  • Exploring solutions like Laboratory Information Management Systems (LIMS) and standardization protocols.
  • Discussing data modeling, storage (file-based, relational databases), project life cycle, and quality assurance (QA).

Main Results:

  • The GeneCards project transitioned from text files to a relational database for improved data organization and accessibility.
  • Successful omics data handling relies on integrating web-based information, public software, affordable hardware, and sound management principles.

Conclusions:

  • Robust data management systems are vital for leveraging omics data.
  • Strategic planning, appropriate technology choices, and rigorous QA are critical for omics project success.