Introduction to genomic and proteomic data analysis

Daniel Berrar, Martin Granzow, Werner Dubitzky

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Citations (Scopus)

Abstract

Genomics can be broadly defined as the systematic study of genes, their functions, and their interactions. Analogously, proteomics is the study of proteins, protein complexes, their localization, their interactions, and posttranslational modifications. Some years ago, genomics and proteomics studies focused on one gene or one protein at a time. With the advent of high-throughput technologies in biology and biotechnology, this has changed dramatically. We are currently witnessing a paradigm shift from a traditionally hypothesis-driven to a data-driven research. The activity and interaction of thousands of genes and proteins can now be measured simultaneously. Technologies for genome- and proteome-wide investigations have led to new insights into mechanisms of living systems. There is a broad consensus that these technologies will revolutionize the study of complex human diseases such as Alzheimer syndrome, HIV, and particularly cancer. With its ability to describe the clinical and histopathological phenotypes of cancer at the molecular level, gene expression profiling based on microarrays holds the promise of a patient-tailored therapy. Recent advances in high-throughput mass spectrometry allow the profiling of proteomic patterns in biofluids such as blood and urine, and complement the genomic portray of diseases.

Original languageEnglish
Title of host publicationFundamentals of Data Mining in Genomics and Proteomics
PublisherSpringer US
Pages1-37
Number of pages37
Volume9780387475097
ISBN (Electronic)9780387475097
ISBN (Print)0387475087, 9780387475080
DOIs
Publication statusPublished - 2007 Jan 1

ASJC Scopus subject areas

  • Medicine(all)

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  • Cite this

    Berrar, D., Granzow, M., & Dubitzky, W. (2007). Introduction to genomic and proteomic data analysis. In Fundamentals of Data Mining in Genomics and Proteomics (Vol. 9780387475097, pp. 1-37). Springer US. https://doi.org/10.1007/978-0-387-47509-7-1