A global analysis on the differential regulation of RNA binding proteins (RBPs) by TNF–α as potential modulators of metabolic syndromes

Louis, Jiss Maria; Agarwal, Arjun; Mondal, Sukanta; Talukdar, Indrani

doi:10.1016/j.bbadva.2021.100037

Cited by 1 publication

(1 citation statement)

References 76 publications

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“…CDIPT was hypomethylated and up-regulated in the fetus of mice with Maternal Gestational Diabetes 56 . SNRPA was found to be associated with metabolic syndromes 57 .…”

Section: Resultsmentioning

confidence: 97%

PHEVIR: an artificial intelligence algorithm that predicts the molecular role of pathogens in complex human diseases

Zhou

Astore

Skolnick

2022

Sci Rep

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Infectious diseases are known to cause a wide variety of post-infection complications. However, it’s been challenging to identify which diseases are most associated with a given pathogen infection. Using the recently developed LeMeDISCO approach that predicts comorbid diseases associated with a given set of putative mode of action (MOA) proteins and pathogen-human protein interactomes, we developed PHEVIR, an algorithm which predicts the corresponding human disease comorbidities of 312 viruses and 57 bacteria. These predictions provide an understanding of the molecular bases of complications and means of identifying appropriate drug targets to treat them. As an illustration of its power, PHEVIR is applied to identify putative driver pathogens and corresponding human MOA proteins for Type 2 diabetes, atherosclerosis, Alzheimer’s disease, and inflammatory bowel disease. Additionally, we explore the origins of the oncogenicity/oncolyticity of certain pathogens and the relationship between heart disease and influenza. The full PHEVIR database is available at https://sites.gatech.edu/cssb/phevir/.

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“…CDIPT was hypomethylated and up-regulated in the fetus of mice with Maternal Gestational Diabetes 56 . SNRPA was found to be associated with metabolic syndromes 57 .…”

Section: Resultsmentioning

confidence: 97%