University of California, Davis
Aug 2017 - Jul 2018
Apr 2013 - Sep 2014
Minseung Kim, Ameen Eetemadi, and Ilias Tagkopoulos (2017): DeepPep: Deep Proteome Inference from Peptide Profiles, PLOS Computational Biology, Public Library of Science (PLoS), Vol 13, Num 9, ppe1005661
Minseung Kim, Navneet Rai, Violeta Zorraquino, and Ilias Tagkopoulos (2016): Multi-Omics Integration Accurately Predicts Cellular State in Unexplored Conditions for Escherichia Coli, Nature Communications, Springer Nature, Vol 7, pp13090
Andreas Pavlogiannis, Vadim Mozhayskiy, and Ilias Tagkopoulos (2013): A Flood-Based Information Flow Analysis and Network Minimization Method for Gene Regulatory Networks, BMC Bioinformatics, Springer Nature, Vol 14, Num 1, pp137
Vadim Mozhayskiy, and Ilias Tagkopoulos (2013): Microbial Evolution in Vivo and in Silico: Methods and Applications, Integr. Biol., Royal Society of Chemistry (RSC), Vol 5, Num 2, pp262--277
Vadim Mozhayskiy, and Ilias Tagkopoulos (2012): Horizontal Gene Transfer Dynamics and Distribution of Fitness Effects During Microbial in Silico Evolution, BMC Bioinformatics, Springer Nature, Vol 13, Num Suppl 10, ppS13
Vadim Mozhayskiy, and Ilias Tagkopoulos (2012): Guided Evolution of in Silico Microbial Populations in Complex Environments Accelerates Evolutionary Rates Through a Step-Wise Adaptation, BMC Bioinformatics, Springer Nature, Vol 13, Num Suppl 10, ppS10
Vadim Mozhayskiy, and Ilias Tagkopoulos (2011): In Silico Evolution of Multi-Scale Microbial Systems in the Presence of Mobile Genetic Elements and Horizontal Gene Transfer, Springer Science + Business Media, Bioinformatics Research and Applications: 7th International Symposium (ISBRA 2011) Proceedings, pp262--273, Changsha, China
Vadim Mozhayskiy, Bob Miller, Kwan-Liu Ma, and Ilias Tagkopoulos (2011): A Scalable Multi-Scale Framework for Parallel Simulation and Visualization of Microbial Evolution, Association for Computing Machinery (ACM), Proceedings of the 2011 TeraGrid Conference on Extreme Digital Discovery (TG '11), pp7:1--7:8, Salt Lake City, Utah, U.S.A.
Blue Waters Symposium 2014, May 13, 2014
Blue Waters Symposium 2016, Jun 14, 2016
Blue Waters Symposium 2017, May 16, 2017
PRAC winners represent a range of disciplinesPetascale Computing Resource Allocations (PRAC awards) from the National Science Foundation allow research teams to work closely with the Blue Waters project team in preparing their codes. The codes and projects address key challenges faced by our society and explore fundamental scientific and engineering problems.These multiyear collaborations include help porting and re-engineering existing applications. In some cases, the teams will build entirely new applications based on new programming models. Current projects—18 representing about 30 institutions—represent a wide range of scientific disciplines. They will drive scientific discovery for years to come..
How will Blue Waters benefit science?The Blue Waters supercomputer is one of the most powerful supercomputers in the world for open scientific research when it comes online at Illinois in 2011. How will scientists and engineers across the country use this tremendous resource? How will their research be advanced by a supercomputer that can do 1 quadrillion calculations every second? Many scientists are working now with the Blue Waters team so they are ready to use the massive sustained-petaflop supercomputer when it comes online in 2011. These teams will use Blue Waters to improve our understanding of everything from the Earth's climate to earthquakes..
Supercomputers create E. coli ‘crystal ball’Predicting the reactions of living cells—huge numbers of genes, proteins, and enzymes, embedded in complex pathways and feedback loops—is a challenging task. Yet researchers are attempting just that, by building a computer model that predicts the behavior of a single cell of the bacterium Escherichia coli. The new simulation is the largest of its kind yet, says Ilias Tagkopoulos, professor of computer science at the University of California, Davis. “The number of layers, and the amount of data involved are unprecedented.”.