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Data Standards in Proteomics: Promises and Challenges

Published

Author(s)

Veerasamy Ravichandran, Ram D. Sriram, G L. Gilliland, S Srivastava

Abstract

Rapid advances in the field of proteomics are yielding abundant data in many formats that, because of the vast quantity and complexity, are becoming increasingly difficult to analyze. A strategic objective of streamlining the transfer of knowledge and technology is to develop the means to analyze data from disparate formats to provide new inferences about the complex role of proteomics in disease processes. Data mining, a process of knowledge extraction from data or a process of exploring the available data for patterns and relationships, is increasingly needed for today s high throughput technologies. It is prudent to develop data architectures to support the integration and analysis of biological data files with epidemiologic profiles of human clinical responses. This ability to develop and analyze metadata will stimulate new research theories and streamline transfer of basic knowledge to clinical applications. This article outlines the ideas and concepts required to develop data standards for proteomics research, and it will serve as a unique reference for researchers, biologists, technologists, clinicians and other health professions alike, to learn about informatics issues relevant to proteome research designed for detecting molecular targets for disease detection, diagnosis, and treatment.
Citation
Data Standards in Proteomics: Promises and Challenges
Publisher Info
Informatics in Proteome Research Chapter for a book entitled Informatics in Proteome Research,

Keywords

data standards, proteomics

Citation

Ravichandran, V. , Sriram, R. , Gilliland, G. and Srivastava, S. (2021), Data Standards in Proteomics: Promises and Challenges, Informatics in Proteome Research Chapter for a book entitled Informatics in Proteome Research, (Accessed June 22, 2024)

Issues

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Created October 12, 2021