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Front Neuroinform. 2012 Apr 27;6:15. doi: 10.3389/fninf.2012.00015. eCollection 2012.

An ontological approach to describing neurons and their relationships.

Author information

1
Center for Neural Informatics, Structures, & Plasticity and Molecular Neuroscience Department, Krasnow Institute for Advanced Study, George Mason University, Fairfax VA, USA.

Abstract

The advancement of neuroscience, perhaps one of the most information rich disciplines of all the life sciences, requires basic frameworks for organizing the vast amounts of data generated by the research community to promote novel insights and integrated understanding. Since Cajal, the neuron remains a fundamental unit of the nervous system, yet even with the explosion of information technology, we still have few comprehensive or systematic strategies for aggregating cell-level knowledge. Progress toward this goal is hampered by the multiplicity of names for cells and by lack of a consensus on the criteria for defining neuron types. However, through umbrella projects like the Neuroscience Information Framework (NIF) and the International Neuroinformatics Coordinating Facility (INCF), we have the opportunity to propose and implement an informatics infrastructure for establishing common tools and approaches to describe neurons through a standard terminology for nerve cells and a database (a Neuron Registry) where these descriptions can be deposited and compared. This article provides an overview of the problem and outlines a solution approach utilizing ontological characterizations. Based on illustrative implementation examples, we also discuss the need for consensus criteria to be adopted by the research community, and considerations on future developments. A scalable repository of neuron types will provide researchers with a resource that materially contributes to the advancement of neuroscience.

KEYWORDS:

characterization; neuron; ontology; part; property; relationship; type; value

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