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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...

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Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

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Published on: October 18, 2013

Cancer genome analysis informatics.

Ian P Barrett¹

¹Cancer Bioscience, AstraZeneca, Macclesfield, Cheshire, UK.

Methods in Molecular Biology (Clifton, N.J.)

|March 19, 2010

Summary

This summary is machine-generated.

Technological advances enable large-scale cancer genome analysis. This review covers informatics resources and approaches to manage and interpret this complex genomic data for cancer research.

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Area of Science:

Genomics
Bioinformatics
Cancer Research

Background:

Cancer genome analysis has advanced significantly due to new technologies.
Next-generation sequencing (NGS) is increasingly applied to cancer genome studies.
Large-scale initiatives like The Cancer Genome Atlas (TCGA) are generating vast amounts of data.

Purpose of the Study:

To provide an overview of informatics resources for cancer genome analysis.
To discuss informatics approaches for managing and interrogating cancer genomic data.
To address the challenges researchers face with large-scale cancer genomic datasets.

Main Methods:

Review of existing informatics resources.
Discussion of bioinformatics tools and methodologies.
Exploration of data coordination and interrogation strategies.

Main Results:

Numerous informatics resources are available for cancer genome analysis.
Various bioinformatics approaches can be applied to study cancer genomes.
Effective data management and analysis are crucial for cancer research.

Conclusions:

Advances in sequencing technology necessitate robust informatics solutions.
Access to and utilization of public cancer genomic data are vital.
Informatics plays a critical role in advancing cancer genome research.