University of Pittsburgh

Other

Vegenics Pty Limited

Vegenics Limited

David Finegold

Robert Ferrell

Kari Alitalo

Marika Karkkainen

Tianjiao Chu

David Gerard Peters

Catherine Baty

Lisa Ann Pan

Computational techniques are disclosed for using methylation profiles to classify the medication condition of a person. Initial sequence data is obtained containing sequences of an initial set of nucleic acids from a biological sample of a person. The initial sequence data is filtered to generate filtered sequence data that describes sequences of a filtered subset of nucleic acids from the biological sample. A methylation profile is determined for the filtered subset of nucleic acids from the biological sample. The methylation profile can be processed to determine a likelihood that the person has the specified medical condition. The system outputs an indication of the likelihood that the person has the specified medical condition.

Computational filtering of methylated sequence data for predictive modeling

Methods are provided for identifying risk of developing lymphedema, including primary and secondary edema. The methods comprise identifying the presence in a biological sample of a polymorphism in one or more of GJA4, GJA5 and GJC2, resulting in a functional mutation of one or more of connixin 37 (Cx37), Cx40 or Cx47.

Connexin mutation detection for lymphatic variation and disease

The present invention provides materials and methods for screening for and treating hereditary lymphedema in human subjects.

Method of treatment for lymphedema comprising administering a polynucleotide encoding VEGF-D

Method of treating lymphedema comprising administering VEGF-D

Screening for lymphatic disorders involving the FLT4 receptor tyrosine kinase (VEGFR-3)

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Pittsburgh, PA, United States of America

David Finegold