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DotMotif: an open-source tool for connectome subgraph isomorphism search and graph queries.
Matelsky, Jordan K; Reilly, Elizabeth P; Johnson, Erik C; Stiso, Jennifer; Bassett, Danielle S; Wester, Brock A; Gray-Roncal, William.
Afiliación
  • Matelsky JK; The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA.
  • Reilly EP; The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA.
  • Johnson EC; The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, 20723, USA.
  • Stiso J; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Bassett DS; Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Wester BA; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Gray-Roncal W; Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Sci Rep ; 11(1): 13045, 2021 06 22.
Article en En | MEDLINE | ID: mdl-34158519
ABSTRACT
Recent advances in neuroscience have enabled the exploration of brain structure at the level of individual synaptic connections. These connectomics datasets continue to grow in size and complexity; methods to search for and identify interesting graph patterns offer a promising approach to quickly reduce data dimensionality and enable discovery. These graphs are often too large to be analyzed manually, presenting significant barriers to searching for structure and testing hypotheses. We combine graph database and analysis libraries with an easy-to-use neuroscience grammar suitable for rapidly constructing queries and searching for subgraphs and patterns of interest. Our approach abstracts many of the computer science and graph theory challenges associated with nanoscale brain network analysis and allows scientists to quickly conduct research at scale. We demonstrate the utility of these tools by searching for motifs on simulated data and real public connectomics datasets, and we share simple and complex structures relevant to the neuroscience community. We contextualize our findings and provide case studies and software to motivate future neuroscience exploration.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Bases de Datos como Asunto / Motor de Búsqueda / Conectoma Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / Bases de Datos como Asunto / Motor de Búsqueda / Conectoma Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos