Tags: nano/bio

Resources (41-60 of 430)

  1. [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.

    https://nanohub.org/resources/butdprobinf

  2. [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

    https://nanohub.org/resources/butdjdist

  3. [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.

    https://nanohub.org/resources/runningaverage

  4. [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),

    https://nanohub.org/resources/5985

  5. [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.

    https://nanohub.org/resources/pertgrad1by1

  6. MAE 6291 Lecture 07: FET, WGM and GMR as Signal Transducers

    07 Jul 2013 | Online Presentations | Contributor(s): jonathan silver

    F. Patolsky et al., Electrical detection of single viruses, Proc. Natl. Acad. Sci. 101:14017-14022 (2004) A. M. Armani et al., Label-free single molecule detection with optical...

    https://nanohub.org/resources/18851

  7. MAE 6291 Lecture 06: Single-Molecule Fluorescence, TIRF, FRET

    07 Jul 2013 | Online Presentations | Contributor(s): jonathan silver

    A. Jain et al., Probing cellular protein complexes using single-molecule pull-down. Nature 474: 484-489 (2012)

    https://nanohub.org/resources/18850

  8. [Illinois]: Big Mess

    26 Jun 2013 | Tools | Contributor(s): Bara Saadah

    This tool stimulates the pulse or step response of a neural network with ten input and ten output units that are randomly connected.

    https://nanohub.org/resources/bigmess

  9. [Illinois]: Posterior target probability given single-sensory input (delta rule)

    02 Jul 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of one modality (i.e., visual)

    https://nanohub.org/resources/unisensorydelta

  10. [Illinois]: Posterior probability of a target given single-sensory input (Bayes')

    28 Jun 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Computes the posterior probability of a target given sensory input of one modality (i.e., visual)

    https://nanohub.org/resources/unisensorybayes

  11. [Illinois]: Posterior probability of a target given input for two senses (Bayes')

    01 Jul 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Computes the posterior probability of a target given sensory input of two modalities (i.e., visual and auditory)

    https://nanohub.org/resources/bisensorybayes

  12. [Illinois]: Posterior probability of a target given input for two senses (delta)

    01 Jul 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of two modalities (i.e., visual and auditory)

    https://nanohub.org/resources/bisensorydelta

  13. [Illinois]: Posterior probabilities of hypothetical fish classes

    28 Jun 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Computes the posterior probabilities of each of three hypothetical fish classes using Bayes' rule

    https://nanohub.org/resources/fishbayesrule

  14. [Illinois]: Fish classification using back-propagation

    28 Jun 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Trains a three-layered network of sigmoidal units using back-propagation to classify fish according to their lengths

    https://nanohub.org/resources/fishbackprop

  15. [Illinois]: Avoidance Learn Simulation with 'Call' Neuron

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

    This script simulates avoidance learning as a reinforcement learning with two upper motoneurons (sumo and fumo) and one "call" neuron.

    https://nanohub.org/resources/avoidlearncall

  16. [Illinois]: Avoidance Learn Simulation

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

    This script simulates avoidance conditioning as reinforcement learning with two upper motoneurons (SUMO and FUMO).

    https://nanohub.org/resources/avoidlearn

  17. [Illinois]: Sigmoidal unit training with the delta rule

    26 Jun 2013 | Tools | Contributor(s): Lisa Sproat, NanoBio Node, Jessica S Johnson

    Uses the delta rule to train a single sigmoidal unit with feedback to simulate the responses of neurons in the parabigeminal nucleus

    https://nanohub.org/resources/pbndeltarule

  18. Hydrodynamic Particle Trapping

    14 Jun 2013 | Tools | Contributor(s): Melikhan tanyerim@illinois.edu Tanyeri, John Feser, Nahil Sobh

    Simulates the motion of a nanoparticle in a hydrodynamic trap.

    https://nanohub.org/resources/particletrap

  19. [Illinois]: Predictor-corrector simulation of parabigeminal nucleus neural responses

    24 Jun 2013 | Tools | Contributor(s): Lisa Sproat, NanoBio Node, Jessica S Johnson

    Implements a predictor-corrector simulation of the responses of neurons in the parabigeminal nucleus

    https://nanohub.org/resources/pbnpredict

  20. [Illinois]: Midbrain dopamine neuron responses to temporal-difference learning

    21 Jun 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node

    Simulates the responses of midbrain dopamine neurons using temporal difference learning

    https://nanohub.org/resources/midbraindopamin