Computational Neuroscience
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Beschreibung
This detailed volume explores practical and reproducible computational techniques and pipelines that span the translational neurosciences continuum. The first section of the book focuses on experimental platforms that generate high-dimensional biological data and the computational methodologies required to transform raw signals into mechanistic insights, while the second half transitions from bench to bedside, illustrating how computational methodologies reshape diagnosis, prognosis, and mechanistic inference across the whole pathophysiological spectrum of the nervous system, from normal brain function to neurological diseases. Written for the highly successful Methods in Molecular Biology series, each chapter provides step-by-step workflows, code snippets, tool recommendations, and the practical guidance needed for positive results.
Authoritative and up-to-date, Computational Neuroscience serves as both a reference and a catalyst: a reference for reproducible pipelines across diverse subfields, and a catalyst for interdisciplinary collaboration.
This detailed volume explores practical and reproducible computational techniques and pipelines that span the translational neurosciences continuum. The first section of the book focuses on experimental platforms that generate high-dimensional biological data and the computational methodologies required to transform raw signals into mechanistic insights, while the second half transitions from bench to bedside, illustrating how computational methodologies reshape diagnosis, prognosis, and mechanistic inference across the whole pathophysiological spectrum of the nervous system, from normal brain function to neurological diseases. Written for the highly successful Methods in Molecular Biology series, each chapter provides step-by-step workflows, code snippets, tool recommendations, and the practical guidance needed for positive results.
Authoritative and up-to-date, Computational Neuroscience serves as both a reference and a catalyst: a reference for reproducible pipelines across diverse subfields, and a catalyst for interdisciplinary collaboration.
Includes cutting-edge techniques Provides step-by-step detail essential for reproducible results Contains key implementation advice from the experts
Autor*in
Antonio Di Ieva
Themen in »Computational Neuroscience«
Artificial Intelligence Machine learning Computational modeling Brain research Coding