The goal of this project is to use data integration and network analyses to discover disease mechanisms and potential treatments.
This Harvard study evaluates the different explanations of heart preload failure in ME/CFS patients to determine which is active in many, if not all, ME/CFS patients. The Computation Center is now seeking to better understand the causes of ME/CFS (PLF, the high flow type) as well as to identify potential drug targets for future therapies.
The purpose of the OMF Data Center is to house raw data and processed results, which is shared with our research network through the web-based data portal.
This project aims to explore the biological changes that occur in the muscles during Post-exertional Malaise (PEM).
The study aims to establish a condensed personalized research protocol that can be used to characterize ME/CFS in individual patients as it pertains to all their unique biological aspects, interacting with a complex chronic disease.
Studying microRNAs could help to bridge the conceptual gap between genetic predisposition and environmental factors causing ME/CFS or exacerbating specific symptoms.
This study is designed to explore the hypothesis that deranged flow of the cerebrospinal fluid (CSF) due to craniocervical obstructions and/or instability may cause deranged intracranial pressure (ICP), neuroinflammation and cardinal symptoms of ME/CFS.
The aim is to investigate potential differences in adrenergic and muscarinic receptor autoantibody levels in plasma and cerebrospinal fluid samples between ME/CFS patients and healthy controls.
The goal of the Severely ill Patient Study was to conduct a comprehensive “Big Data” analysis on severely ill ME/CFS patients in order to begin an exploration to find the molecular basis of ME/CFS.
Researchers are developing a tool to help clinicians more efficiently define the character and priorities of a patient’s current symptoms of ME/CFS, Post-Treatment Lyme Disease, or Fibromyalgia.