PhyloDet
- A Scalable Visualization Tool for Mapping Multiple Traits to Large Evolutionary Trees

 

 

Project description

HIV/AIDS researchers are using machine learning techniques to identify how the human immune system influences the evolution of HIV within a human host. To do so, they need to take the evolutionary tree of HIV into account. PhyloDet is a scalable Phylogeny Tree Browser to allow biologists to visualize multiple traits mapped to the tree.

Participants

Bongshin Lee, Researcher, Visualization and Interaction Research Group (VIBE), Microsoft Research
Lev Nachmanson,  Research Software Development Engineer, VIBE, Microsoft Research
George Robertson, Principal Researcher, VIBE, Microsoft Research
Jonathan Carlson, Researcher, eScience Research Group, Microsoft Research
David Heckerman, Research Area Manager, eScience Research Group, Microsoft Research

Publications

Bongshin Lee, Lev Nachmanson, George Robertson, Jonathan M. Carlson, David Heckerman (2009) PhyloDet: A Scalable Visualization Tool for Mapping Multiple Traits to Large Evolutionary Trees, To appear in Bioinformatics.

Thomas Kuntzen, Joerg Timm, Andrew Berical, Niall Lennon, Aaron M. Berlin, Sarah K. Young, Bongshin Lee, David Heckerman, Jonathan Carlson, Laura L. Reyor, Marianna Kleyman, Cory M. McMahon, Christopher Birch, Julian Schulze zur Wiesch, Timothy Ledlie, Michael Koehrsen, Chinnappa Kodira, Andrew D. Roberts, Georg M. Lauer, Hugo R. Rosen, Florian Bihl, Andreas Cerny, Ulrich Spengler, Zhimin Liu, Arthur Y. Kim, Yanming Xing, Arne Schneidewind, Margaret A. Madey, Jaquelyn F. Fleckenstein, Vicki M. Park, James E. Galagan, Chad Nusbaum, Bruce D. Walker, Gerond V. Lake-Bakaar, Eric S. Daar, Ira M. Jacobson, Edward D. Gomperts, Brian R. Edlin, Sharyne M. Donfield, Raymond T. Chung, Andrew H. Talal, Tony Marion, Bruce W. Birren, Matthew R. Henn, and Todd M. Allen (2008) Naturally occurring dominant resistance mutations to hepatitis C virus protease and polymerase inhibitors in treatment-na´ve patients, Hepatology, Vol. 48, No. 6, pp.1769-1778.

Bongshin Lee, Lev Nachmanson, George Robertson, Jonathan Carlson, and David Heckerman (2008) Det. (Distance Encoded Tree): A Scalable Visualization Tool for Mapping Multiple Traits to Large Evolutionary Trees, MSR Tech Report (MSR-TR-2008-97), Microsoft Research.

Availability & Download

Det. is a standalone Windows« application running on a PC environment. It is freely downloadable for non-commercial use; academic and/or research purposes.

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