H. Ali, L. Ricci, I. Epicoco, M. Ujaldón, Jonathan Passerat-Palmbach, D. Hill, M. Villén-Altamirano
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Developing innovative data mining techniques and clever parallel computational methods to implement them will surely play an important role in efficiently extracting useful knowledge from the raw data currently available. The proper integration of carefully selected/developed algorithms along with efficient utilization of High Performance Computing (HPC) systems form the key ingredients in the process of reaching new discoveries from biological data. This tutorial focuses on addressing several key issues related to the effective utilization of HPC in biomedical informatics research, in particular, how to efficiently utilize high performance systems in the analysis of massive biological data. A major issue is that regard is how to design energy-aware models for executing computationally-intensive biomedical applications on HPC systems. Another key issue is how to develop innovative network filters for massive biological networks that would utilize parallel algorithms to construct networks samplers that would preserve original network structures while uncovering new ones.","PeriodicalId":428764,"journal":{"name":"2012 International Conference on High Performance Computing & Simulation (HPCS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"HPCS 2012 tutorials: Tutorial I: High performance computing in biomedical informatics\",\"authors\":\"H. Ali, L. Ricci, I. Epicoco, M. Ujaldón, Jonathan Passerat-Palmbach, D. Hill, M. 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HPCS 2012 tutorials: Tutorial I: High performance computing in biomedical informatics
The last decade has witnessed significant developments in various aspects of Biomedical Informatics, including Bioinformatics, Medical Informatics, Public Health Informatics, and Biomedical Imaging. The explosion of medical and biological data requires an associated increase in the scale and sophistication of the automated systems and intelligent tools to enable the researchers to take full advantage of the available databases. The availability of vast amount of biological data continues to represent unlimited opportunities as well as great challenges in biomedical research. Developing innovative data mining techniques and clever parallel computational methods to implement them will surely play an important role in efficiently extracting useful knowledge from the raw data currently available. The proper integration of carefully selected/developed algorithms along with efficient utilization of High Performance Computing (HPC) systems form the key ingredients in the process of reaching new discoveries from biological data. This tutorial focuses on addressing several key issues related to the effective utilization of HPC in biomedical informatics research, in particular, how to efficiently utilize high performance systems in the analysis of massive biological data. A major issue is that regard is how to design energy-aware models for executing computationally-intensive biomedical applications on HPC systems. Another key issue is how to develop innovative network filters for massive biological networks that would utilize parallel algorithms to construct networks samplers that would preserve original network structures while uncovering new ones.