Mini Symposia

Listed below are Mini Symposia for SciPy2013.

More details and schedule information coming soon.

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Astronomy and Astrophysics
Accessing the Virtual Observatory from Python Plante, Raymond, NCSA/UofIL; Fitzpatrick, Mike, NOAO; Graham, Matthew, Caltech; Tody, Doug, NRAO
Astropy, growing a community-based software system for astronomy Droettboom, Michael, STScI; Robitaille, Thomas, Max Planck Institute; Tollerud, Erik, Yale Universit
Combining C++ and Python in the LSST Software Stack Bosch, Jim, Princeton University
Ginga: an open-source astronomical image viewer and toolkit Jeschke, Eric, Subaru Telescope, National Astronomical Observatory of Japan
Python and the SKA Simon Ratcliffe SKA South Africa, Ludwig Schwardt SKA South Africa
SunPy - Python for Solar Physicists Mumford, Stuart, University of Sheffield / SunPy
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All-by-all learning of protein complexes from mass spectrometry data Blake Borgeson, Center for Systems and Synthetic Biology, University of Texas at Austin; Cuihong Wa
Best-practice variant calling pipeline for fully automated high throughput sequencing analysis Chapman, Brad; Kirchner, Rory; Hofmann, Oliver; Hide, Winston
Detection and characterization of interactions of genetic risk factors in disease Francis-Lyon, Patricia, University of San Francisco; Belvadi, Shashank, University of San Francisco; Wang, Lin, University of San Francisco
EMAN2 and EMEN2: Flexible Python-based platforms for electron microscopy Rees, Ian, Baylor College of Medicine; Ludtke, Steven, Baylor College of Medicine
Exploring disease genetics from thousands of individual genomes with Gemini Quinlan, Aaron, University of Virginia; Paila, Uma, University of Virginia; Chapman, Brad, Harvard School of Public Health; Kirchner, Rory,
Massive Online Collaborative Research and Modeling using Synapse and Python Omberg, Larsson, Sage Bionetworks
metaseq: a Python framework for integrating high-throughput sequencing analyses Dale, Ryan, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of
MIST: Micro-Simulation Tool to Support Disease Modeling Jacob Barhak
Stuff to do with your genomic intervals Pedersen, Brent; University of Colorado
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GIS - Geospatial Data Analysis
GIS Panel Panel participants: Sergio Ray (Arizona State U), Shaun Walbridge (ESRI), Andrew Wilson (TWDB)
LarvaMap - A python powered larval transport modeling system Wilcox, Kyle, Applied Science Associates (ASA); Crosby, Alex, Applied Science Associates (ASA)
Optimizing Geographic Processing and Analysis for Big Data Carissa, GeoDecisions; Gleason, Jason, GeoDecisions
SCI-WMS: A Python Based Web Map Service For Met-Ocean Data Accessible Over OpenDAP Or As NetCDF Crosby, Alexander
Streamed Clustering of Lightning Mapping Data in Python Using sklearn Bruning, Eric C., Texas Tech University
The Production of a Multi-Resolution Global Index for Geographic Information Systems MacManus, Kytt, Columbia University CIESIN
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Medical Imaging
A Rapidly-Adaptable Analytical Imaging & Measurement Standardization Platform for Cancer Diagnostics Research Garsha, Karl, Ventana Medical Systems Inc.; Ventura, Franklin, Ventana Medical Systems Inc.;
An Open Source System for De-identification and Use of Medical Images for Research Miller, Jeffrey, Center for Biomedical Informatics, The Children's Hospital of Philadelphia
Automating Quantitative Confocal Microscopy Analysis Fenner, Mark; Fenner, Barbara, King's College, Wilkes-Barre, PA
Estimating and Visualizing the Inertia of the Human Body with Python Moore, Jason, University of California at Davis; Dembia, Christopher, Stanford
Experiences in Python for Medical Image Analysis Warner, Joshua, Mayo Clinic Department of Biomedical Engineering
NeuroTrends: Large-scale automated analysis of the neuroimaging literature Carp, Joshua, University of Michigan
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Meteorology, Climatology, Atmospheric and Oceanic Science
Advances in delivery and access tools for coastal ocean model data Signell, Richard, US Geological Survey
Climate Observations from ACIS in pandas Noon, William: Northeast Regional Climate Center
Iris & Cartopy: Open source Python packages for Atmospheric and Oceanographic science Elson, Philip, UK Met Office;
Oil spill modeling and uncertainty forecasts with Python Hou,Xianlong, University of Texas at Austin; Hodges,Ben, University of Texas at Austin
Using Python to drive the General NOAA Operational Modeling Environment Barker, Christopher H. NOAA Emergency Response Division.