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- Author: Theodore B Achacoso
- Publisher: CRC Press
- ISBN-10: 0367250284
- ISBN-13: 9780367250287
- Format: 15.2 x 22.9 x 1.6 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Ay's Neuroanatomy of C. Elegans for Computation (e-book) (used book) | bookbook.eu
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Description
First published in 1992, AY's Neuroanatomy of C. elegans for Computation provides the neural circuitry database of the nematode Caenorhabditis elegans, both in printed form and in ASCII files on 5.25-inch diskettes (for use on IBM(R) and compatible personal computers, Macintosh(R) computers, and higher level machines). Tables of connections among neuron classes, synapses among individual neurons, gap junctions among neurons, worm cells and their embryonic origin, and synthetically derived neuromuscular connections are presented together with the references from which the data were compiled and edited. Sample data files and source codes of FORTRAN and BASIC programs are provided to illustrate the use of mathematical tools for any researcher or student interested in examining a natural neural network and discovering what makes it tick.
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- Author: Theodore B Achacoso
- Publisher: CRC Press
- ISBN-10: 0367250284
- ISBN-13: 9780367250287
- Format: 15.2 x 22.9 x 1.6 cm, softcover
- Language: English English
First published in 1992, AY's Neuroanatomy of C. elegans for Computation provides the neural circuitry database of the nematode Caenorhabditis elegans, both in printed form and in ASCII files on 5.25-inch diskettes (for use on IBM(R) and compatible personal computers, Macintosh(R) computers, and higher level machines). Tables of connections among neuron classes, synapses among individual neurons, gap junctions among neurons, worm cells and their embryonic origin, and synthetically derived neuromuscular connections are presented together with the references from which the data were compiled and edited. Sample data files and source codes of FORTRAN and BASIC programs are provided to illustrate the use of mathematical tools for any researcher or student interested in examining a natural neural network and discovering what makes it tick.
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