From Data to Disease Mechanism and Treatments
Each OMF funded study is selected, with oversight from our Scientific Advisory Board, for its ability to provide meaningful data that will fuel the search for treatment and diagnosis. This data is essential to develop diagnostic technologies, understand the molecular basis of the diseases, and uncover effective diagnostic tools and treatments. Under the direction of Wenzhong Xiao, PhD, the Computational Research Center for Complex Diseases analyzes and integrates the data from OMF funded studies, an essential step in developing diagnostics and treatments. |
Dr. Xiao is a world expert in computational genomics and the Director of the Immuno-Metabolic Computational Center at Massachusetts General Hospital (MGH), Harvard Medical School. He also leads a Computational Genomics Group at Stanford Genome Technology Center (SGTC). His research is at the interface of computation, genomics and medicine. In collaboration with Open Medicine Foundation, his lab analyzes studies on ME / CFS and compares ME / CFS with other diseases.
statistical and bioinformatic analyses of collaborative research studies
and apply of state-of-the-art algorithms to uncover ME/CFS disease mechanisms and drug targets
Triple Giving Tuesday starts today: Announcing our sixth Research Center! From the desk of Linda Tannenbaum Chief Executive Officer, Open Medicine Foundation Open Medicine Foundation (OMF) is pleased to share,
With your support, Open Medicine Foundation funds open, collaborative research so that, as soon as possible, precise diagnostic tools and life-changing treatments can be available to people with ME/CFS and related chronic, complex diseases such as Post-Treatment Lyme Disease Syndrome, Fibromyalgia, and Post-COVID Syndrome.
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.
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.
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.
We will 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.
Post-exertional malaise is a hallmark of ME/CFS, and the iCPET provides a unique opportunity to investigate the molecular mechanism Sequence Analysis of Viruses and Other Microbes will
Please help us expand our research efforts across the globe. Every donation brings us closer to a fully-funded research effort and the answers we all seek.
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