TY - BOOK ID - 138533225 TI - Recent advances and the future generation of neuroinformatics infrastructure AU - John Van Horn AU - Venkata Satyanand Mattay AU - Qian Luo AU - Xi Cheng AU - Daniel Marcus AU - Daniel R. Weinberger PY - 2015 PB - Frontiers Media SA DB - UniCat KW - Neuroimaging KW - database KW - neuroinformatics KW - workflow KW - infrastructure KW - high-throughput KW - data processing UR - https://www.unicat.be/uniCat?func=search&query=sysid:138533225 AB - The huge volume of multi-modal neuroimaging data across different neuroscience communities has posed a daunting challenge to traditional methods of data sharing, data archiving, data processing and data analysis. Neuroinformatics plays a crucial role in creating advanced methodologies and tools for the handling of varied and heterogeneous datasets in order to better understand the structure and function of the brain. These tools and methodologies not only enhance data collection, analysis, integration, interpretation, modeling, and dissemination of data, but also promote data sharing and collaboration. This Neuroinformatics Research Topic aims to summarize the state-of-art of the current achievements and explores the directions for the future generation of neuroinformatics infrastructure. The publications present solutions for data archiving, data processing and workflow, data mining, and system integration methodologies. Some of the systems presented are large in scale, geographically distributed, and already have a well-established user community. Some discuss opportunities and methodologies that facilitate large-scale parallel data processing tasks under a heterogeneous computational environment. We wish to stimulate on-going discussions at the level of the neuroinformatics infrastructure including the common challenges, new technologies of maximum benefit, key features of next generation infrastructure, etc. We have asked leading research groups from different research areas of neuroscience/neuroimaging to provide their thoughts on the development of a state of the art and highly-efficient neuroinformatics infrastructure. Such discussions will inspire and help guide the development of a state of the art, highly-efficient neuroinformatics infrastructure. ER -