ArticleNature reviews. Rheumatology2011
The role of bioinformatics in studying rheumatic and autoimmune disorders.
Article in Nature reviews. Rheumatology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- A transcriptome atlas and interactive analysis platform for autoimmune disease.Database : the journal of biological databases and curation · 2022Article
- CD3D, GZMK, and KLRB1 Are Potential Markers for Early Diagnosis of Rheumatoid Arthritis, Especially in Anti-Citrullinated Protein Antibody-Negative Patients.Frontiers in pharmacology · 2021Article
- IMMUNOLOGY. An interactive reference framework for modeling a dynamic immune system.Science (New York, N.Y.) · 2015Article
- Applications of systems approaches in the study of rheumatic diseases.The Korean journal of internal medicine · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
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.
Indexed as
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21691330What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.