Event Abstract

Logically defining Neurons in the Cell Ontology

  • 1 The Jackson Laboratory, United States
  • 2 Lawrence Berkeley National Laboratory, United States
  • 3 University at Buffalo, School of Dental Medicine, United States
  • 4 University at Buffalo, School of Medicine and Biomedical Sciences, United States

The Cell Ontology (CL) is a candidate OBO Foundry ontology for the representation of cell types and is under revision to better represent neuronal cell types. As the CL grows in complexity, logical definitions are used to ensure neuron types are mutually independent from each other. For successful implementation of logical definitions, the differentiae used by a biologist to distinguish a neuron from other cell-types must be established. At a recent joint CL-INCF workshop*, ontology editors and neurobiologists discussed the differentiae that are necessary and sufficient to distinguish a neuron. The concept of a “neuron” was found to have different meanings among neurobiologists, with a hierarchy established for three definitions of “neuron” that are increasingly stringent in the number of cell types they include. The most permissive neuron type includes cell types that detect stimulus involved in sensory perception (“olfactory receptor cell’) while the most conservative neuron cell-type only includes those cells that carry out voltage-dependent release of cell signaling molecules and have the ability to maintain a voltage gradient or propagate an action potential along a cell process. With either a permissive or stringent definition of neuron, there was an agreed upon set of necessary and sufficient differentiae to define sub-types of neurons.  These differentiae fall along axes of anatomy, cell morphology, neurotransmitter release, electrophysiology, developmental lineage, and the biological processes a neuron type participates in.  We are currently in the process of generating logical definitions for retinal neurons based on these differentiae and will use this as a model for how we define all neuron types in the CL. (Work supported by INCF and an ARRA administrative supplement grant HG002273-09Z to the parent grant, HG002273). * Participants of the Cell Ontology-INCF Neuron Workshop, Atlanta, GA (April, 2011) Janis Breeze, INCF Program Officer Stephan Larson, University of California, San Diego Jyl Boline, Informed Minds, Inc. Ed Lein, Allen Brain Institute Paul Katz, Center for Neuromics at Georgia State University Jose Leonardo Mejino, University of Washington Giorgio Ascoli, George Mason University Sasha Nelson, Brandeis University Mihail Bota, University of Southern California Sridevi Polavaram, George Mason University Robert Burgess, The Jackson Laboratory David Osumi-Sutherland, Cambridge University Akshaye Dhawan, Ursinus College Abir Ashfakur Rahman, Georgia State University Chad Frederick, Georgia State University Patrick Ray, SUNY Buffalo Daniel Gardner, Weil Medical College, Cornell Kathleen Rockland, Massachusetts Institute of Technology Melissa Haendel, Oregon Health & Science University Deboleena Roy, Emory University David Hamilton, George Mason University Joseph Shea, SUNY Buffalo Sean Hill, INCF Gordon Shepherd, Yale University Kei Ito, The University of Tokyo Raj Sunderraman, Georgia State University Saurav Karmakar, Georgia State University Menno Witter, Norwegian University of Science and Technology

Keywords: General neuroinformatics

Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011.

Presentation Type: Poster Presentation

Topic: General neuroinformatics

Citation: Meehan T, Mungall C, Ruttenberg A, Blake J and Diehl A (2011). Logically defining Neurons in the Cell Ontology. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00156

Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.

The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.

Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.

For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.

Received: 17 Oct 2011; Published Online: 19 Oct 2011.

* Correspondence: Dr. Terrence F. Meehan, The Jackson Laboratory, Bar Harbor, United States, tmeehan@informatics.jax.org