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Tags: nano/bio

Resources (21-40 of 427)

  1. Molecular Dynamics Showcase

    06 Jul 2013 | Tools | Contributor(s): Michael McLennan, Chen-Yu Li, john stone, Aleksei Aksimentiev

    View interesting features of a molecular dynamics trajectory file

    http://nanohub.org/resources/mdshowcase

  2. [Illinois] Physics 550 Biomolecular Physics

    05 Sep 2013 | Courses | Contributor(s): Klaus Schulten, Taekjip Ha

        Physical concepts governing the structure and function of biological macromolecules; general properties, spatial structure, energy levels, dynamics and functions, and...

    http://nanohub.org/resources/19299

  3. Neural Systems Modeling Ch10-13 Master Tool

    02 Aug 2013 | Tools | Contributor(s): Jessica S Johnson, NanoBio Node

    Combination of all tools used in Chapters 10-13 of Neural Systems Modeling by Anastasio

    http://nanohub.org/resources/nsmch10master

  4. [Illinois]: Neural Systems Modeling Ch 6-9 Master Tool

    26 Jul 2013 | Tools | Contributor(s): Jessica S Johnson, NanoBio Node

    Combination of all tools used in Chapters 6-9 of Neural Systems Modeling by Anastasio

    http://nanohub.org/resources/nsmch6master

  5. [Illinois]: Error Gradient Estimations Due to Parallel Perturbation of Weights

    07 Jul 2013 | Tools | Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool trains two-layered networks of sigmoidal units to associate patterns using simultaneous perturbation of weights.

    http://nanohub.org/resources/pertgradll

  6. [Illinois]: Perturbative Reinforcement Learning to Develop Distributed Representations

    10 Jul 2013 | Tools | Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool trains three-layered networks of sigmoidal units to associate patterns.

    http://nanohub.org/resources/pertdistrep

  7. [Illinois]: Perturbative Reinforcement Learning Using Directed Drift

    10 Jul 2013 | Tools | Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool trains two-layered networks of sigmoidal units to associate patterns using a real-valued adaptation of the directed drift algorithm.

    http://nanohub.org/resources/pertdd

  8. [Illinois]: Temporal Difference, Iterative Dynamic Programming, and Least Mean Squares

    11 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson

    This tool updates state values using the Temporal Difference Algorithm.

    http://nanohub.org/resources/tempdiff

  9. Crystalline Cellulose - Atomistic Toolkit

    17 Jul 2013 | Tools | Contributor(s): Mateo Gómez Zuluaga, Robert J. Moon, Fernando Luis Dri, Pablo Daniel Zavattieri

    Crystalline Cellulose - Atomistic Toolkit

    http://nanohub.org/resources/ccamt

  10. [Illinois] GEM4 Bionanotechnology Summer Institute 2013

    01 Aug 2013 | Workshops

    INSTITUTE FOCUS: Cancer Nanotechnology and Cellular Mechanics OBJECTIVES The overall objective is to enhance the ability to address overarching challenges in the areas of Cancer...

    http://nanohub.org/resources/19040

  11. [Illinois]: Direction Selectivity

    13 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool implements a simple direction selective network.

    http://nanohub.org/resources/dirselectivity

  12. [Illinois]: Predict Correct Set Up

    15 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool sets up a predictor-corrector model of target tracking

    http://nanohub.org/resources/predcorsetup

  13. [Illiniois]: SynchUp

    16 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool computes synchronous updates of autoassociative networks.

    http://nanohub.org/resources/synchup

  14. [Illinois]: AsynchUp

    16 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, NanoBio Node, Jessica S Johnson

    This tool computes asynchronous updates of autoassociative networks.

    http://nanohub.org/resources/asynchup

  15. [Illinois] KohonenSOM

    09 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, Jessica S Johnson, NanoBio Node

    This tool implements the Kohonen self-organizing map (SOM) algorithm

    http://nanohub.org/resources/kohonensom

  16. [Illinois]: BUTDprobInference

    17 Jul 2013 | Tools | Contributor(s): Bara Saadah, Jessica S Johnson, NanoBio Node

    This tool stimulates bottom-up/top-down processing in the visual system using probabilistic inference.

    http://nanohub.org/resources/butdprobinf

  17. [Illinois]: BUTDjointDistribution

    16 Jul 2013 | Tools | Contributor(s): Bara Saadah, Jessica S Johnson, NanoBio Node

    this tool simulates bottom-up/top-down processing in the visual system using the joint distribution

    http://nanohub.org/resources/butdjdist

  18. [Illinois]: Running Average

    10 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, Jessica S Johnson, NanoBio Node

    This tool implements a running average of a noise series.

    http://nanohub.org/resources/runningaverage

  19. [illinois] BioMEMS and Bionanotechnology: Integration of Life Sciences and Engineering at the Micro and Nanoscale

    10 Jul 2013 | Online Presentations | Contributor(s): Rashid Bashir

    Optical Society of America (OSA), University of Illinois Chapter, IEEE Electron Devices Society (EDS), University of Illinois Chapter, Micro and Nanotechnology Laboratory (MNTL),

    http://nanohub.org/resources/5985

  20. [Illinois]: Error Gradient Estimations Due to Perturbation of One Weight at a Time

    29 Jun 2013 | Tools | Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node

    This tool trains two-layered networks of sigmoidal units to associate patterns using perturbation of one weight at a time.

    http://nanohub.org/resources/pertgrad1by1

nanoHUB.org, a resource for nanoscience and nanotechnology, is supported by the National Science Foundation and other funding agencies. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.