Collaborating with Dr. Michelle Zhang on the creation of a software infrastructure platform for high performance proteomics in C++. High quality peptide identification is critical to all subsequent proteomics data analysis stages, such as protein identification as well as application areas such as biomarker & drug discovery.
Faculty Collaboration Projects
These are our Faculty Collaboration Projects
Performed preliminary research for Dr. Clyde Phelix on providing an infrastructure to enable the streamlining and automating of large scale SimBiology based simulations on the Matlab Distributed Server environment and the Copasi simulation environment.
Performed parallelization opportunities preliminary research for Dr. Aleksander Kartusinski for a single and multi-phase fluid simulation code. Computational fluid dynamics has important applications in a variety of critical areas such as fluid simulation for biomedical applications and oil exploration.
Collaborating with Dr. William Haskins & proteomics lab team on providing custom software to automate the proteomics workflow. Starting with acquisition data management to integrating with tools such as Mascot Daemon, Mascot Server, R, and the Ingenuity Systems Pathway Analysis web service. Automation in the proteomics workflow is critical to enable the efficient utilization of next generation proteomics hardware.
Providing access to the CBI allocation at TACC for testing parallel computational chemistry code. The CBI compute time allocation allows the researchers to test out their codes on TACC systems such as Ranger and Lonestar. Over 2 million SU's have been allocated for this project on Lonestar. Collaborating with Dr. Walter C. Ermler(Dept. of Chemistry, UTSA)
Collaborating with Dr. Fidel Santamaria & Dr. Toma Marinov on a high performance C++ software toolbox for Matlab for high speed Fractional Integration and Fractional Diffusion simulation applications. The (fit) toolbox was developed in C++ with OpenMP parallelism to make use of as many cores as are available on a system. It can be compiled for both the Linux and Windows operating system environments. Fractional integration has a wide array of applications in areas such as neural simulation.
Working to enable custom distributed software using the Matlab Distributed Computing Server Cluster. Faculty Collaboration: Arturo Ponce-Pedraza, Ph.D. Cesar Santiago Cortes, Ph. D. (Research Fellow) Hector Barron-Escobar, Ph.D. Candidate Pedro L. Galindo Ph.D (Full Professor) Computer Science and Engineering Dept., Universidad de Cádiz
Working with Dr. Fidel Santamaria & Dr. Toma Marinov to enable large scale distributed neural diffusion simulation workflows at the CBI as well as at the Texas Advanced Computing Center.
Utilizing the ClusterCheckpointer(tm) system developed to allow automating the management of the checkpointing of long running jobs.
Collaborating with Dr. Long Liu from the UTSA Department of Economics to enable parallelization of software in the R programming language
within the Cheetah HPC Cluster.
- Computational Econometrics: Nonparametric estimation techniques in the statistical software environment R with parallel enablement.