The Role of Bioinformatics in Studying Rheumatic and Autoimmune Disorders

Overview

Journal Nat Rev Rheumatol

Specialty Rheumatology

Date 2011 Jun 22

PMID 21691330

Citations 4

Authors

Marina Sirota

Atul J Butte

Affiliations

Soon will be listed here.

Abstract

In the past decade, the availability and abundance of individual-level molecular data, such as gene expression, proteomics and sequence data, has enabled the use of integrative computational approaches to pose and answer novel questions about disease. In this article, we discuss several examples of applications of bioinformatics techniques to study autoimmune and rheumatic disorders. We focus our discussion on how integrative techniques can be applied to analyze gene expression and genetic variation data across different diseases, and discuss the implications of such analyses. We also outline current challenges and future directions of these approaches. We show that integrative computational methods are essential for translational research and provide a powerful opportunity to improve human health by refining the current knowledge about diagnostics, therapeutics and mechanisms of disease pathogenesis.

Citing Articles

A transcriptome atlas and interactive analysis platform for autoimmune disease.

Shen Z, Fang M, Sun W, Tang M, Liu N, Zhu L Database (Oxford). 2022; 2022.

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CD3D, GZMK, and KLRB1 Are Potential Markers for Early Diagnosis of Rheumatoid Arthritis, Especially in Anti-Citrullinated Protein Antibody-Negative Patients.

Lu J, Bi Y, Zhu Y, Huipeng S, Duan W, Zhou J Front Pharmacol. 2021; 12:726529.

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Spitzer M, Gherardini P, Fragiadakis G, Bhattacharya N, Yuan R, Hotson A Science. 2015; 349(6244):1259425.

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Applications of systems approaches in the study of rheumatic diseases.

Kim K, Lee S, Kim W Korean J Intern Med. 2015; 30(2):148-60.

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