Bradly Alicea
Cellular Reprogramming Laboratory
Michigan State University
Presented in the Embryo Physics Course, April 4, 2012
Abstract
As complex, dynamic, and often labyrinthine entities, the modeling of biological systems should not be treated using conventional computational structures and techniques. A recently developed parallel technique called GPU (graphical processing unit) computing offers a number of potential opportunities for modeling distributed, explicitly physical, and combinatorial processes. The talk will introduce GPU computing as a departure from both conventional serial computing and as a unique computational method in its own right. We will discuss what a parallel and graphical-specific algorithms looks like, and how they can be mapped to biological problems. The first part of the talk is an introduction to graphical, parallel computing and how it can be differentiated from conventional computing (e.g. serial CPUs). We will also touch on the constraints and opportunities imposed by the data structures and problem-solving requirements of this architecture. The second part of the talk will focus on applications to biology. Highlighted problem domains include the modeling of cellular signaling, sequence analysis, morphogenesis, population-based problems, and multiscalar phenomena. The talk will conclude with a consideration of applying graphical processing to a host of biologically-oriented problems that opens up new representational paradigms of potential interest to both computational scientists and biologists.
Presentation
/files/presentations/Alicea2012.pdf
The presentation with the comments:
http://syntheticdaisies.blogspot.de/p/scenes-from-graphical-parallel-biology.html
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