Support

Support Options

Submit a Support Ticket

 

Tags: NanoBio Node

Resources (41-60 of 514)

  1. [Illinois] Computational Microscopy for Health and Technology

    17 Dec 2013 | Online Presentations | Contributor(s): Klaus Schulten

    It is today becoming possible to view and study biological systems on the cellular scale using computational methods, offering insights into new solutions to mankind's health and energy needs....

    http://nanohub.org/resources/19483

  2. [Illinois] The Spectacular Nano-Structured Attachment of Tendon to Bone and Our Appalling Attempts to Reconstitute It

    17 Dec 2013 | Online Presentations | Contributor(s): Guy Genin

    Joining mechanically dissimilar materials is a challenge throughout engineering, with spectacular and often devastating failures. This challenge also underlies one of the worst procedures in all...

    http://nanohub.org/resources/19484

  3. [Illinois] Metal and Semiconductor Nanoparticles Supported on Graphene for Energy Conversion and Heterogeneous Catalysis

    17 Dec 2013 | Online Presentations | Contributor(s): M. Samy El Shall

    Graphene has attracted great interest for a fundamental understanding of its unique structural and electronic properties and also for important potential applications in nanoelectronics and...

    http://nanohub.org/resources/19493

  4. [Illinois] Fluidic Nanoprobes for In Vitro Single Cell Studies

    17 Dec 2013 | Online Presentations | Contributor(s): Horatio Espinosa

    A robust method for single cell access to deliver genes and small molecules to primary and sensitive cells is needed to advance the state-of-the-art in personalized medicine and therapeutics. To...

    http://nanohub.org/resources/19495

  5. [Illinois] Multi-function Semiconductor Membranes with Nanopore for Bio-Molecule Sensing and Manipulation

    17 Dec 2013 | Online Presentations | Contributor(s): Jean-Pierre Leburton, Anuj Gridhar

    In the recent years there has been a tremendous interest in using solid-state membranes with nanopores as a new tool for DNA and RNA characterization and possible sequencing. Among solid-state...

    http://nanohub.org/resources/19498

  6. [Illinois] A Microfluidic Approach for Cocrystallization of Drugs and Analysis via X-ray Diffraction

    16 Dec 2013 | Online Presentations | Contributor(s): Elizabeth Horstman

    The process of pharmaceutical drug development is cost- and time-intensive. Candidate drugs (CDs) are screened with many counter ions (salt or cocrystal formers) to find solid forms of the drug...

    http://nanohub.org/resources/19500

  7. [Illinois] Microcapsules for Luminescent Tracking and Controlled Drug Delivery

    16 Dec 2013 | Online Presentations | Contributor(s): Yulia Maximenko

    Polyelectrolyte microcapsules are formed on porous calcium carbonate templates that are impregnated and coated with 2.9 nanometer luminescent silicon nanoparticles. The complexes are characterized...

    http://nanohub.org/resources/19509

  8. [Illinois] MCB 493 Lecture 13: Predictor-Corrector Models and Probabilistic Inference

    30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    http://nanohub.org/resources/19663

  9. [Illinois] MCB 493 Lecture 10: Time Series Learning and Nonlinear Signal Processing

    30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    http://nanohub.org/resources/19662

  10. [Illinois] MCB 493 Lecture 1: Vectors, Matrices, and Basic Neural Computations

    30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Using mathematical and computational methods to simulate many aspects of neural systems function.

    http://nanohub.org/resources/16716

  11. [Illinois] MCB 493 Lecture 3: Forward and Recurrent Lateral Inhibition

    30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Networks with forward and recurrent laterally inhibitory connectivity profiles can shape signals in space and time, and simulate certain forms of sensory and motor processing.

    http://nanohub.org/resources/16718

  12. [Illinois] MCB 493 Lecture 6: Supervised Learning and Non-Uniform Representations

    30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Supervised learning algorithms can train neural networks to associate patterns and simulate the non-uniform distributed representations found in many brain regions.

    http://nanohub.org/resources/17022

  13. [Illinois] MCB 493 Lecture 7: Reinforcement Learning and Associative Conditioning

    30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Reinforcement learning algorithms can simulate certain types of associative conditioning and train neural networks to form non-uniform distributed representations.

    http://nanohub.org/resources/18832

  14. [Illinois] MCB 493 Lecture 9: Probability Estimation and Supervised Learning

    30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Supervised learning algorithms can train neural units and networks to estimate probabilities and simulate the responses of neurons to multisensory stimulation.

    http://nanohub.org/resources/18834

  15. [Illinois] MCB 493 Lecture 14: Future Directions in Neural Systems Modeling

    30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    In the future, neural systems models will become increasingly complex and will span levels from molecular interactions within neurons to interactions between networks

    http://nanohub.org/resources/18948

  16. [Illinois] MCB 493 Lecture 2: Recurrent Connections and Simple Neural Circuits

    29 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Networks with recurrent connections, forming circuits, and containing only a few neural units can shape signals in time, produce oscillations, and simulate certain forms of low-level motor control.

    http://nanohub.org/resources/16717

  17. [Illinois] MCB 493 Lecture 4: Covariation Learning and Auto-Associative Memory

    29 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Networks with recurrent connection weights that reflect the covariation between pattern elements can dynamically recall patterns and simulate certain forms of memory.

    http://nanohub.org/resources/16950

  18. [Illinois] MCB 493 Lecture 5: Unsupervised Learning and Distributed Representations

    29 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Unsupervised learning algorithms, given only a set of input patterns, can train neural networks to form distributed representations of those patterns that resemble brain maps.

    http://nanohub.org/resources/16951

  19. [Illinois] MCB 493 Lecture 8: Information Transmission and Unsupervised Learning

    29 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Unsupervised learning algorithms can train neural networks to increase the amount of information they contain about their inputs and simulate the properties of sensory neurons.

    http://nanohub.org/resources/18833

  20. [Illinois] MCB 493 Lecture 11: Temporal-Difference Learning and Reward Prediction

    29 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio

    Temporal-difference learning can train neural networks to estimate the future value of a current state and simulate the responses of neurons involved in reward processing.

    http://nanohub.org/resources/18947

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.