Network Medicine for Disease Mechanisms and Treatment
The goal of this project is to use data integration and network analyses to discover disease mechanisms and potential treatments.
iCPET Omics Studies of ME/CFS
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.
OMF Data Center
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.
Skeletal Muscle Dysfunction
This project aims to explore the biological changes that occur in the muscles during Post-exertional Malaise (PEM).
Condensed Precision Medicine Protocol for ME/CFS
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.
Stress-Activated MicroRNAs
Studying microRNAs could help to bridge the conceptual gap between genetic predisposition and environmental factors causing ME/CFS or exacerbating specific symptoms.
Autoimmunity and Autoantibodies
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.
Severely iIl Patient
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.
Extended Big Data Study in Families
The goal of this study was to extend the Severely ill Patient Study and conduct a comprehensive “Big Data” analysis on ME/CFS patients and their families.
Personalized Automated Symptom Summary (PASS)
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.
