Metabolic syndrome(MetS)is a complex disorder characterized by the coexistence of phenotypes such as obesity,hypertension,hyperglycemia,high triglyceride level,and low level of high-density lipoprotein cholesterol.Inf...Metabolic syndrome(MetS)is a complex disorder characterized by the coexistence of phenotypes such as obesity,hypertension,hyperglycemia,high triglyceride level,and low level of high-density lipoprotein cholesterol.Inflammation majorly driven by oxidative stress has an overarching role in obesity and IR-mediated mechanisms leading to Mets.Besides these factors.展开更多
There are numerous online databases dedicated to genes associated with human diseases.The redundancy and lack of consistency of disease terms in these databases pose a significant impediment in high throughput data an...There are numerous online databases dedicated to genes associated with human diseases.The redundancy and lack of consistency of disease terms in these databases pose a significant impediment in high throughput data analysis.To address this,we developed GeDiPNet by compiling data available on gene-disease associations from six popular open access sources namely DisGeNET,1 ClinGen.展开更多
基金This work(RA/1346/11-2022)was supported by grants received from the Department of Biotechnology,Ministry of Science and TechnologyGovernment of India(BT/PR40165/BTIS/137/12/2021)+1 种基金Science and Engineering Research Board(India)(STR/2020/000034)the Indian Council of Medical Research,India(BMI/11(51)/2022).
文摘Metabolic syndrome(MetS)is a complex disorder characterized by the coexistence of phenotypes such as obesity,hypertension,hyperglycemia,high triglyceride level,and low level of high-density lipoprotein cholesterol.Inflammation majorly driven by oxidative stress has an overarching role in obesity and IR-mediated mechanisms leading to Mets.Besides these factors.
基金This work(No.RA/1170/11–2021)was supported by grants received from the Department of Biotechnology,India(No.BT/PR40165/BTIS/137/12/2021)Science and Engineering Research Board,India(No.STR/2020/000034).
文摘There are numerous online databases dedicated to genes associated with human diseases.The redundancy and lack of consistency of disease terms in these databases pose a significant impediment in high throughput data analysis.To address this,we developed GeDiPNet by compiling data available on gene-disease associations from six popular open access sources namely DisGeNET,1 ClinGen.
