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StartUp Research 2017
This volume presents a collection of peer-reviewed contributions arising from StartUp Research: a stimulating research experience in which twenty-eight early-career researchers collaborated with seven senior international professors in order to develop novel statistical methods for complex brain ima...
Autores principales: | , , , |
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Lenguaje: | eng |
Publicado: |
Springer
2018
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-3-030-00039-4 http://cds.cern.ch/record/2653141 |
_version_ | 1780961025057619968 |
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author | Canale, Antonio Durante, Daniele Paci, Lucia Scarpa, Bruno |
author_facet | Canale, Antonio Durante, Daniele Paci, Lucia Scarpa, Bruno |
author_sort | Canale, Antonio |
collection | CERN |
description | This volume presents a collection of peer-reviewed contributions arising from StartUp Research: a stimulating research experience in which twenty-eight early-career researchers collaborated with seven senior international professors in order to develop novel statistical methods for complex brain imaging data. During this meeting, which was held on June 25–27, 2017 in Siena (Italy), the research groups focused on recent multimodality imaging datasets measuring brain function and structure, and proposed a wide variety of methods for network analysis, spatial inference, graphical modeling, multiple testing, dynamic inference, data fusion, tensor factorization, object-oriented analysis and others. The results of their studies are gathered here, along with a final contribution by Michele Guindani and Marina Vannucci that opens new research directions in this field. The book offers a valuable resource for all researchers in Data Science and Neuroscience who are interested in the promising intersections of these two fundamental disciplines. |
id | cern-2653141 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2018 |
publisher | Springer |
record_format | invenio |
spelling | cern-26531412021-04-22T06:33:18Zdoi:10.1007/978-3-030-00039-4http://cds.cern.ch/record/2653141engCanale, AntonioDurante, DanielePaci, LuciaScarpa, BrunoStartUp Research 2017Mathematical Physics and MathematicsThis volume presents a collection of peer-reviewed contributions arising from StartUp Research: a stimulating research experience in which twenty-eight early-career researchers collaborated with seven senior international professors in order to develop novel statistical methods for complex brain imaging data. During this meeting, which was held on June 25–27, 2017 in Siena (Italy), the research groups focused on recent multimodality imaging datasets measuring brain function and structure, and proposed a wide variety of methods for network analysis, spatial inference, graphical modeling, multiple testing, dynamic inference, data fusion, tensor factorization, object-oriented analysis and others. The results of their studies are gathered here, along with a final contribution by Michele Guindani and Marina Vannucci that opens new research directions in this field. The book offers a valuable resource for all researchers in Data Science and Neuroscience who are interested in the promising intersections of these two fundamental disciplines.Springeroai:cds.cern.ch:26531412018 |
spellingShingle | Mathematical Physics and Mathematics Canale, Antonio Durante, Daniele Paci, Lucia Scarpa, Bruno StartUp Research 2017 |
title | StartUp Research 2017 |
title_full | StartUp Research 2017 |
title_fullStr | StartUp Research 2017 |
title_full_unstemmed | StartUp Research 2017 |
title_short | StartUp Research 2017 |
title_sort | startup research 2017 |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-3-030-00039-4 http://cds.cern.ch/record/2653141 |
work_keys_str_mv | AT canaleantonio startupresearch2017 AT durantedaniele startupresearch2017 AT pacilucia startupresearch2017 AT scarpabruno startupresearch2017 |