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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...
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 Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
Occasionally these regions can be adapted to take on new roles within the organism, becoming novel genes...
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Structure of a Gene

A gene is the fundamental unit of heredity. Every individual has two copies of each gene, one inherited from each parent. Although most people contain the same genes, there is a small fraction that is slightly different amongst people. A gene with a small difference in its sequence of DNA bases forms different alleles, contributing to different phenotypes.
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Data management in structural genomics: an overview.

Sabrina Haquin1, Eric Oeuillet, Anne Pajon

  • 1Yeast Structural Genomics, IBBMC, Université Paris-Sud, Orsay, France.

Methods in Molecular Biology (Clifton, N.J.)
|June 11, 2008
PubMed
Summary
This summary is machine-generated.

Effective data management is vital for large-scale scientific projects. Laboratory Information Management Systems (LIMS) offer solutions for tracking complex experimental data, improving reproducibility and data mining in structural genomics.

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Area of Science:

  • Biotechnology and Bioinformatics
  • Genomics and Proteomics
  • Scientific Data Management

Background:

  • Large-scale experimental projects require robust data management due to multiple personnel, diverse locations, and complex protocols.
  • Accurate record-keeping is essential for publication, protocol reuse, troubleshooting, and validation in scientific research.
  • Existing data management solutions are limited for broad projects like structural genomics, metabolomics, and systems biology.

Purpose of the Study:

  • To highlight the critical role of data management in large-scale scientific endeavors.
  • To discuss the challenges and requirements for designing effective information management systems in genomics research.
  • To review existing and emerging data management solutions, focusing on Laboratory Information Management Systems (LIMS).

Main Methods:

  • The study reviews the necessity of comprehensive data management for understanding experimental details (what, when, who, how).
  • It examines the impact of complex and evolving protocols on information management system design.
  • The authors discuss the need for systems adaptable to both robotic and manual data entry, emphasizing flexibility.

Main Results:

  • Most structural genomics groups develop custom solutions due to the lack of suitable commercial systems.
  • Laboratory Information Management Systems (LIMS) offer significant advantages for daily project management and data mining in structural genomics.
  • Three specific LIMS solutions developed by the authors (Xtrack, Sesame, HalX) are presented as examples.

Conclusions:

  • Implementing a LIMS is crucial for efficient data management in structural genomics projects.
  • Custom-developed LIMS can address the specific needs of complex, evolving research environments.
  • The discussed systems (Xtrack, Sesame, HalX) provide valuable tools for managing and analyzing structural genomics data.