Harnessing Data Science for Health Discovery and Innovation in Africa

The NIH Common Fund’s Harnessing Data Science for Health Discovery and Innovation in Africa program will leverage data science technologies and prior NIH investments to develop solutions to the continent’s most pressing public health problems through a robust ecosystem of new partners from academic, government, and private sectors.

https://commonfund.nih.gov/AfricaData

Current Funding Opportunities:

Mechanics of the kinesin-based transport: From single-molecule to multi-motor behaviors, to cell division

The motor protein kinesin uses ATP (adenosinetriphosphate) as a fuel and walks along the microtubule track, carrying out critical tasks such as intracellular transport and cell division. I will explain atomic simulations and single-molecule experiments analyzing modular design in kinesin's mechanochemistry. Strategies for using these findings to study multi-motor behavior will be discussed, including cooperative transport and microtubule organization in mitotic spindle dynamics.

Medical Device Innovation Consortium: MDICx Seriesㅁ

MDICx Series

Join us for the next MDICx session on March 10th at 10:00am EST as we learn about the Modeling & Simulation Heart and Vasculature Working Group. This hour long session gives an overview of the work and then dives deeper into in silico clinical trials, physiologically realistic simulation and the history, need, and difficulty of verifying and validating whole heart models.

MDIC Computational Modeling & Simulation Project

Heart and Vasculature Working Group

Microconnectomics of primary motor cortex: a multiscale computer model

The dual-output hypothesis, based on analysis of wiring patterns in M1, describes neocortex as organized around Layer-5 corticostriatal pyramidal cells which project to other cortical areas (as well as to striatum) and Layer-5 corticospinal pyramidal cells, which project out of cerebrum to brainstem and spinal cord. We propose the dual-output hypothesis as a replacement for the old canonical-circuit model of Douglas and Martin. The canonical-circuit was a major contribution in 1989, and remains today a touchstone for thinking about neocortex. Although basic concepts from that model are valid, this model is insufficient for multiscale modeling since it implicitly uses point neurons and thereby neglects the key multiscale feature of cortex -- the large L5 pyramidal cells that span circuit layers at a higher scale. (new U01 award)

Mineralized polymeric biomaterials: Simulation, Experiment, Design

This webinar will focus on the integrated treatment of mineralized polymeric biomaterials, which provide useful options towards mechanically robust systems for some tissue repairs. Silks as a mechanically robust protein-based materials provide a starting point for biomaterial options, particularly when combined with silica towards organic-inorganic hybrid systems.

Model reproducibility and reuse webinar

"Collaboration and Validation in Model of Cells and Circuits"

Rick Gerkin is an assistant research professor at Arizona State University with a research program in neuro- and bioinformatics.  His main focus is the development of approaches and tools to systematically validate computational biology models against a wide range of experimental data, and to make validation a major part of the model development and model sharing process. 

Universities Space Research Association Seeking Deputy Project Scientist to support NASA Human Research Program Cross-Cutting Computational Modeling Project (CCMP)

The NASA Human Research Program Cross-Cutting Computational Modeling Project (CCMP) focuses on using various computational modeling and simulation techniques to provide NASA researchers...

A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects

What is being modeled?
Interactions between different frequency brain rhythms.
Description & purpose of resource

Back to Main BRAIN TMM page

We provide a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. The proposed method successfully detects cross-frequency coupling (CFC) between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples.

Spatial scales
tissue
Temporal scales
10-3 - 1 s
1 - 103 s
This resource is currently
mature and useful in ongoing research
Has this resource been validated?
No
How has the resource been validated?

Details, simulation results, and applications to in vivo data are published.

Can this resource be associated with other resources? (e.g.: modular models, linked tools and platforms)
No
Key publications (e.g. describing or using resource)

A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects, Nadalin et al eLife 2019;8:e44287
https://elifesciences.org/articles/44287

DOI link to publication describing this resource

https://doi.org/10.7554/eLife.44287

Link to resource
All code to use and further develop this method is available on GitHub.
Collaborators
Mark Kramer
PI contact information
mak@math. bu.edu
Keywords
BRAIN TMM
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