Mrs
Tanya Levshina
(Fermilab)
06/03/2017, 15:05
Dr
Brian Bockelman
(University of Nebraska-Lincoln)
06/03/2017, 16:30
Kaushik De
(Univ. of Texas at Arlington)
06/03/2017, 16:50
Dr
Burt Holzman
(FNAL), Mr
John Hover
(Brookhaven National Laboratory)
06/03/2017, 17:30
Prof.
Frank Wuerthwein
(UCSD)
07/03/2017, 08:50
Brian Lin
(University of Wisconsin-Madison)
07/03/2017, 09:10
Dr
Derek Weitzel
(University of Nebraska - Lincoln), Mr
Suchandra Thapa
(Computation Institute / University of Chicago)
07/03/2017, 09:30
Eric Sedore
(Syracuse University)
07/03/2017, 09:50
Prof.
Tom Cheatham
(University of Utah)
07/03/2017, 10:10
Prof.
Dana Brunson
(Oklahoma State University)
07/03/2017, 11:00
Mark Neubauer
(University of Illinois at Urbana-Champaign)
07/03/2017, 11:20
Mr
Edgar Fajardo Hernandez
(UCSD)
07/03/2017, 11:40
Kaushik De
(Univ. of Texas at Arlington)
07/03/2017, 12:00
Prof.
Fernando Luco
(Texas A&M University)
07/03/2017, 13:30
Prof.
Nepomuk Otte
(Georgia Institute of Technology)
07/03/2017, 13:30
Mr
Ahmad Golmohammadi
(New Mexico State University)
07/03/2017, 13:50
Lossy source coding is an efficient data compression technique that aims to minimize the distortion in the reconstructed sequence. Our research involves the investigation of the distortion performance of state-of-the art protograph-based SC-LDGM codes. We show that performance close to Shannon's optimal rate-distortion limits can be achieved with an efficient windowed encoding (WE) algorithm...
Mustafa Mustafa
(LBL)
07/03/2017, 14:00
Dr
Ben Intoy
(University of Minnesota)
07/03/2017, 14:10
In previous work (Physical Review E 89, 022725 (2014)), a Kauffman-like model for prebiotic evolution was used to explore the effects of requiring that the final steady states generated
be out of chemical equilibrium. That constraint, consistent with intuitive ideas of the meaning of 'lifelike', had a significant impact on the probability of the appearance of lifelike states in the model....
Dr
Richard Jones
(University of Connecticut)
07/03/2017, 14:30
Mr
Scott Cole
(University of California San Diego)
07/03/2017, 14:30
https://docs.google.com/presentation/d/1s5n-ObLv5In3lVpqUJoUqO7RZDEMf5WjXzYmJJGdraA/edit?usp=sharing
As data collection systems are augmented, more individual labs require high-throughput computing in order to process all of their data. In these labs, researchers are continuously developing their own analytics methods in scripting languages. These facts are especially true in the neuroscience...
Dr
Benedikt Riedel
(University of Chicago)
07/03/2017, 14:50
Mats Rynge
(USC / Information Sciences Institute)
07/03/2017, 15:10
Mr
Suchandra Thapa
(Computation Institute / University of Chicago)
07/03/2017, 16:20
FreeSurfer is a software suite for processing and analyzing human MRI images. Freesurfer takes several hours to process a typical MRI scan (~40MB in size) and generates about 300MB of results. This makes it a good fit for computation on OSG. We present FSurf, a computational service that allows users to easily run typical FreeSurfer workflows on OSG.
Dr
Derek Weitzel
(University of Nebraska - Lincoln)
07/03/2017, 16:20
Dr
Oana Carja
(University of Pennsylvania)
07/03/2017, 16:40
Molecular processes are fundamentally stochastic. Randomness is the rule in transcription, translation, cell-to-cell variation in protein levels, and heterogeneity in interactions. One common assumption is that such phenotypic variation is simply noise, and scientists often appeal to the statistics of large numbers when developing deterministic theories, ignoring any potentially adaptive role...
Marina Krenz
(Indiana University)
07/03/2017, 16:40
Todd Miller
(University of Wisconsin–Madison)
07/03/2017, 17:00
Prof.
Stephen Ficklin
(Washington State University), Mr
William Poehlman
(Clemson University)
07/03/2017, 17:00
Several petabytes of raw DNA sequencing data have been deposited into public databases in recent years, introducing novel opportunities for mining useful biological information. The Open Science Grid (OSG) provides hardware and software infrastructure that have enabled us to address complex biological questions at a larger scale than previously possible with our local HPC resources at...
Prof.
Frank Wuerthwein
(UCSD)
08/03/2017, 09:05
David Swanson
(University of Nebraska Lincoln)
08/03/2017, 09:30
Prof.
Robert Gardner
(University of Chicago)
08/03/2017, 09:45
Annie Malkus
(University of Wisconsin–Madison)
08/03/2017, 11:00
Rami Vanguri
(Columbia University)
08/03/2017, 11:25
Prof.
Kam Arnold
(University of California San Diego)
08/03/2017, 11:50
Dr
Jerome Lauret
(Brookhaven National Laboratory), Prof.
Steffen Bass
(Duke University)
08/03/2017, 12:15
Rob Quick
(Indiana University)
08/03/2017, 14:00
A look back at the successes of the past year of OSG.
Dr
Brian Bockelman
(University of Nebraska-Lincoln)
08/03/2017, 14:30
Mats Rynge
(USC / Information Sciences Institute)
09/03/2017, 09:00
Mr
Suchandra Thapa
(Computation Institute / University of Chicago)
09/03/2017, 09:15
Dr
Bala Desinghu
(Scientific Computing Consultant)
09/03/2017, 10:00
Dr
Bala Desinghu
(Scientific Computing Consultant)
09/03/2017, 11:00
Brian Lin
(University of Wisconsin-Madison)
09/03/2017, 11:00
Mats Rynge
(USC / Information Sciences Institute)
09/03/2017, 11:25
Dr
Derek Weitzel
(University of Nebraska - Lincoln)
09/03/2017, 11:45
Mats Rynge
(USC / Information Sciences Institute)
09/03/2017, 11:50
Prof.
Robert Gardner
(University of Chicago)
09/03/2017, 14:00
Mr
Suchandra Thapa
(Computation Institute / University of Chicago)
Prof.
Stephen Ficklin
(Washington State University), Mr
William Poehlman
(Clemson University)
Several petabytes of raw DNA sequencing data have been deposited into public databases in recent years, introducing novel opportunities for mining useful biological information. The Open Science Grid (OSG) provides hardware and software infrastructure that have enabled us to address complex biological questions at a larger scale than previously possible with our local HPC resources at...