This is a list of common, well-known or infamous diseases.This is neither complete nor authoritative. This is not intended to be a list of rare diseases, nor is it a list of mental disorders.. Each of these databases focuses on different aspects of the phenotype-genotype relationship, and due to the nature of the database curation process, they are not complete, but in a way they are fully complementary between each other.Essentially, there are four types of databases: curated databases, predictive databases, literature databases and integrative databases,The term curated data refers to information, that may comprise the most sophisticated computational formats for structured data, scientific updates, and curated knowledge, that has been composed and prepared under the regulation of one or more experts considered to be qualified to engage in such an activity.CTD is a unique resource where bioinformatics specialists read the scientific literature and manually curate four types of core data:A predictive database is one based on statistical inference. Several databases have been developed storing associations between genes and diseases such as the Comparative Toxicogenomics Database (CTD), Online Mendelian Inheritance in Man (OMIM), the genetic Association Database (GAD) or the Disease genetic Association Database (DisGeNET). WHO main areas of work include: health systems, promoting health through the life-course, noncommunicable diseases, communicable diseases, corporate services, preparedness, surveillance and response. Gene Disease Databases integrate human gene-disease … The site's stated aim is "education, background reading and general interest" with an intended audience "physicians, … Available:K. Brown, "Online Predicted human Interaction Database,",S. Hunter and P. Jones, "InterPro in 2011: new developments in the family and domain prediction database,",C. Bult and J. Eppig, "The Mouse genome Database (MGD): mouse biology and model systems,",M. Dwinell, E. Worthey and S. M, "The Rat genome Database 2009: variation, ontologies and pathways,",A. Homosh, "Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders,","Control of VEGF-A transcriptional programs by pausing and genomic compartmentalization","Network medicine analysis of COPD multimorbidities","Organ system heterogeneity DB: A database for the visualization of phenotypes at the organ system level","Molecularly and clinically related drugs and diseases are enriched in phenotypically similar drug-disease pairs","Prioritizing Disease-Linked Variants, Genes, and Pathways with an Interactive Whole-Genome Analysis Pipeline","A Computational Framework to Infer Human Disease-Associated Long Noncoding RNAs","Choline Protects Against Cardiac Hypertrophy Induced by Increased After-load","Detection of differentially methylated gene promoters in failing and nonfailing human left ventricle myocardium using computation analysis","Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes","Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network","Charting the NF-κB Pathway Interactome Map",International Society for Computational Biology,List of open-source bioinformatics software,"Databases, data tombs and dust in the wind","The Comparative Toxicogenomics Database: update 2011","Text Mining Effectively Scores and Ranks the Literature for Improving Chemical-Gene-Disease Curation at the Comparative Toxicogenomics Database","DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene–disease networks","Systematic analysis of gene properties influencing organ system phenotypes in mammalian perturbations","Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical–gene–disease networks","The Universal Protein Resource (UniProt)","Ongoing and future developments at the Universal Protein Resource","The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease","Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research","DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes","Predicting disease genes using protein-protein interactions",https://en.wikipedia.org/w/index.php?title=Gene_Disease_Database&oldid=970854475,Creative Commons Attribution-ShareAlike License,Ongoing and future developments at the Universal Protein Resource.Yes – manual and automatic. The Rare Disease Database. Audience Medical practitioners and students are users of Diseases Database. In bioinformatics, a Gene Disease Database is a systematized collection of data, typically structured to model aspects of reality, in a way to comprehend the underlying mechanisms of complex diseases, by understanding multiple composite interactions between phenotype-genotype relationships and gene-disease mechanisms.

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