HiBB 2013  - 4th Workshop on High Performance Bioinformatics and Biomedicine

Track 4: Tuesday, August 27, 9:00 – 12:30, Room: Main Building - Lecture Hall IV

Mario Cannataro (chair), University Magna Graecia of Catanzaro, Italy


Session WE4, Room: Main Building - Lecture Hall IV, Chair: Mario Cannataro - Large Scale High Performance Biomedicine


9:00 Epidemic Data Mining: Global Knowledge without Global Communication,

Invited speaker: Giuseppe Di Fatta, University of Reading, UK


10:00 Heterogeneous Platforms Programming for Faster Medical Imaging Processing

Renan Sales Barros, Sytse van Geldermalsen, A. M. Boers, Adam S. Z. Belloum, Henk A. Marquering, Silvia D. Olabarriaga


10:30 - 11:00 Coffee Break

Session WF4, Room: Main Building - Lecture Hall IV, Chair: Mario Cannataro - Software Platforms for Bioinformatics and Systems


11:00 Transparent Incremental Updates for Genomics Data Analysis Pipelines

Edvard Pedersen, Nils P. Willassen, Lars Ailo Bongo


11:30 msPar: A Parallel Coalescent Simulator

Carlos Montemui�oAntonio EspinosaJuan Carlos Moure, Gonzalo Vera Rodr�guez, Sebasti�n Ramos-Onsins, Porfidio Hern�ndez Bud�


12:00 Panel on High Performance Bioinformatics and Biomedicine
Chair: Mario Cannataro
Panelists: Renan Sales Barros, Giuseppe Di Fatta, Antonio Espinosa, Edvard Pedersen


The goal of the panel is to discuss emerging topics and problems regarding the application of
High Performance Computing techniques, such as GPU, Grid and Cloud Computing,
to biomedical applications, bioinformatics and systems biology.

The panelists will voice their opinions about topics like:

- Trends in data mining for e-science: parallel data mining, workflow development environments, data science

- High Performance Computing for medical imaging in acute care

- Cooperation between the biology and computer science groups

- Apache Hadoop and Google Grid Engine for bioinformatics

- Managing a small-scale cluster for bioinformatics

- Workflow management for bioinformatics

- Porting genomic sequence alignment into Hadoop and GPU environments