8th International Workshop on High Performance Bioinformatics and Biomedicine (HiBB 2017)
November 13-16,2017,Kansas City, MO, USA

High-throughput technologies (e.g. microarray, mass spectrometry, NGS) and clinical diagnostic tools (e.g. medical imaging) are producing an increasing amount of experimental and clinical data. In such a scenario, large-scale databases and bioinformatics tools are key tools for organizing and exploring biological and biomedical data with the aim to discover new knowledge in biology and medicine. High-performance computing may play an important role in many phases of life sciences research, from raw data management and processing, to data analysis and integration, till data exploration and visualization. In particular, at the raw data layer, Grid infrastructures may offer the huge data storage needed to store experimental and biomedical data, while parallel computing can be used for basic pre-processing (e.g. parallel BLAST) and for more advanced analysis (e.g. parallel data mining). In such a scenario, novel parallel architectures (e.g. e.g. CELL processors, GPUs, FPGA, hybrid CPU/FPGA) coupled with emerging programming models may overcome the limits posed by conventional computers to the mining and exploration of large amounts of data.