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Related Concept Videos

Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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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...
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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...
Genomic DNA in Eukaryotes00:58

Genomic DNA in Eukaryotes

Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.
Genome Annotation and Assembly03:36

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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.
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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...

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SGDI: system for genomic data integration.

V J Carey1, J Gentry, R Sarkar

  • 1Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA. stvjc@channing.harvard.edu

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|January 31, 2008
PubMed
Summary
This summary is machine-generated.

This study presents a framework for managing high-throughput assay data, enabling transparent and extensible analysis of gene expression and other biological data. It supports large-scale studies and genetic investigations with a customizable interface.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Managing and analyzing large-scale high-throughput assay data from multiple experiments is complex.
  • Integrating diverse datasets, including transcriptional profiling, gene expression genetics, and copy number variation with mRNA abundance, presents significant challenges.

Purpose of the Study:

  • To describe a novel framework for the systematic collection, annotation, and archiving of high-throughput assay data.
  • To provide a transparent, extensible, and customizable interface for accessing and analyzing large archives of biological assay data.

Main Methods:

  • Utilized R/Bioconductor for data capture and modeling.
  • Employed R for sample annotation and sequence ontology management.
  • Implemented secure data archiving using PostgreSQL.
  • Developed browser-based workspaces using Zope for data management.

Main Results:

  • A comprehensive framework for handling high-throughput assay data has been established.
  • The framework supports various applications, including large-scale surveys, gene expression genetics, and joint analyses of genomic and transcriptomic data.
  • A transparent and customizable interface to large assay data archives has been generated.

Conclusions:

  • The developed framework offers a robust solution for managing and analyzing complex high-throughput biological data.
  • The system enhances data accessibility and facilitates collaborative research in genomics and transcriptomics.
  • The extensible nature of the framework allows for future adaptations and integration with new biological data types.