DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene–disease networks

Bauer-Mehren, Anna; Rautschka, Michael; Sanz, Ferrán; Furlong, Laura I.

doi:10.1093/bioinformatics/btq538

Cited by 181 publications

(145 citation statements)

References 11 publications

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“…Network of gene-disease associations (altered expression, casual mutation, genetic variation, marker, and more) were generated using DisGeNET Cytoscape plugin as described previously (Bauer-Mehren et al, 2010). The top 50 hCM up-regulated genes were inquired individually for disease association in the cardiovascular disease class.…”

Section: Gene-disease Association Network Analysismentioning

confidence: 99%

Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes

Liu

Plongthongkum³

et al. 2013

Protein Cell

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With defined culture protocol, human embryonic stem cells (hESCs) are able to generate cardiomyocytes in vitro, therefore providing a great model for human heart development, and holding great potential for cardiac disease therapies. In this study, we successfully generated a highly pure population of human cardiomyocytes (hCMs) (>95% cTnT + ) from hESC line, which enabled us to identify and characterize an hCM-specific signature, at both the gene expression and DNA methylation levels. Gene functional association network and gene-disease network analyses of these hCM-enriched genes provide new insights into the mechanisms of hCM transcriptional regulation, and stand as an informative and rich resource for investigating cardiac gene functions and disease mechanisms. Moreover, we show that cardiac-structural genes and cardiac-transcription factors have distinct epigenetic mechanisms to regulate their gene expression, providing a better understanding of how the epigenetic machinery coordinates to regulate gene expression in different cell types.

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Section: Gene-disease Association Network Analysismentioning

confidence: 99%

Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes

Liu

Plongthongkum³

et al. 2013

Protein Cell

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“…To achieve knowledge integration, a number of strategies and tools can be used that leverage advances in computational, mathematical, and engineering sciences (Box 4) (32, 33). The participation and close collaboration of basic and clinical scientists with bioinformaticians and engineers is key for the proper curation and understanding of findings (33,34). Several currently available examples include, among others (35)(36)(37), the identification of novel candidate genes for idiopathic pulmonary fibrosis (38,39), personalized therapies for patients with cystic fibrosis (40), and predictive outcome signatures in lung cancer (41).…”

Section: Bioinformatics: the New Kid On The Blockmentioning

confidence: 99%

Personalized Respiratory Medicine: Exploring the Horizon, Addressing the Issues. Summary of a BRN-AJRCCM Workshop Held in Barcelona on June 12, 2014

Agustí

Antó

Auffray

et al. 2015

Am J Respir Crit Care Med

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“…As shown in figure 1b, in the molecular diseasome two diseases are linked if they: 1) share disease-associated genes, as identified by DisGeNET, a database that integrates information on gene−disease associations from various public repositories and the biomedical literature [21,22]; and/or 2) the proteins encoded by disease-associated genes are connected in the interactome [23], a publically available protein interaction network (HIPPIE) [24]. As detailed in the online supplement, to reduce the potential bias that shared genes/proteins might be more easily identified in those diseases that have been more extensively characterised, and to estimate the strength of the association between two diseases in the molecular diseasome, we used the Molecular Comorbidity Index (MCI) [13] and a bootstrap analysis.…”

Section: Molecular Diseasomementioning

confidence: 99%

Molecular and clinical diseasome of comorbidities in exacerbated COPD patients

et al. 2015

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The frequent occurrence of comorbidities in patients with chronic obstructive pulmonary disease (COPD) suggests that they may share pathobiological processes and/or risk factors.To explore these possibilities we compared the clinical diseasome and the molecular diseasome of 5447 COPD patients hospitalised because of an exacerbation of the disease. The clinical diseasome is a network representation of the relationships between diseases, in which diseases are connected if they co-occur more than expected at random; in the molecular diseasome, diseases are linked if they share associated genes or interaction between proteins.The results showed that about half of the disease pairs identified in the clinical diseasome had a biological counterpart in the molecular diseasome, particularly those related to inflammation and vascular tone regulation. Interestingly, the clinical diseasome of these patients appears independent of age, cumulative smoking exposure or severity of airflow limitation.These results support the existence of shared molecular mechanisms among comorbidities in COPD.@ERSpublications Half of the comorbidities observed in COPD patients hospitalised by an exacerbation share common molecular mechanisms

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DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene–disease networks

Abstract: DisGeNET is compatible with Cytoscape 2.6.3 and 2.7.0, please visit http://ibi.imim.es/DisGeNET/DisGeNETweb.html for installation guide, user tutorial and download.

Cited by 181 publications

References 11 publications

Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes

Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes

Personalized Respiratory Medicine: Exploring the Horizon, Addressing the Issues. Summary of a BRN-AJRCCM Workshop Held in Barcelona on June 12, 2014

Molecular and clinical diseasome of comorbidities in exacerbated COPD patients

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