Datasets

Subject
Creator
Type
Date

subject: Biomedical Engineering

Total is 44 Results
Competitive Tuning of Ca2+/Calmodulin-Activated Proteins Provides a Compensatory Mechanism for AMPA Receptor Phosphorylation in Synaptic Plasticity

10.4231/R7VX0DS0

Matthew C Pharris , Tamara L. Kinzer-Ursem ORCID logo

07/30/2018

Code for the basic 4-state competitive binding model that builds on previous work by incorporating an additional competitor for calmodulin along with a number of downstream proteins. Also include is sample code for global sensitivity analysis...

Biomedical Engineering Calmodulin Neuroscience

T1-weighted brain atlas for adolescent collision-sport athletes in Purdue Neurotrauma Group longitudinal database

10.4231/4668-DM62

Ho-Ching Yang ORCID logo , Joseph V Rispoli ORCID logo , Thomas M Talavage ORCID logo , Wenbin Zhu , Yukai Zou ORCID logo

01/16/2019

A population-specific brain atlas based on the T1-weighted MR scans from 215 adolescent collision-sport athletes in the longitudinal database of Purdue Neurotrauma Group.

Adolescents Atlasing Biomedical Engineering Brain Informatics Morphometrics MRI Neuroscience Spatial Normalization Spatial Warping Statistical Methods Trauma Workflow

In vitro Volumetric Particle Velocimetry, Computational Fluid Dynamics (CFD), and in vivo 4D Flow MRI Hemodynamic Data in Two Patient-Specific Cerebral Aneurysms

10.4231/M5F1-QC84

Benjamin Dickerhoff , David Saloner , Melissa Brindise , Michael Markl , Pavlos Vlachos ORCID logo , Sean Rothenberger ORCID logo , Susanne Schnell , Vitaliy Rayz

08/23/2019

Data from a pulsatile volumetric particle velocimetry study using two patient-specific cerebral aneurysm models, processed using Shake the Box (STB). Associated in vivo MRI and CFD datasets are also provided.

Biomedical Engineering Cerebral Aneurysm CFD Experimental Tests Fluid Mechanics Matlab MRI PIV Shake the Box

A Multi-state Model of the CaMKII Holoenzyme using MCell 3.3

10.4231/MBPK-D277

Matthew C Pharris , Tamara L Kinzer-Ursem ORCID logo

03/11/2019

This model uses a specialized rule-based syntax in MCell 3.3 to model the twelve-subunit CaMKII holoenzyme without inducing combinatorial explosion. The model allows us to explore the regulation of CaMKII activation and autophosphorylation.

Biomedical Engineering Calmodulin Computational Modeling Neuroscience Protein Signaling

Source code for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision

10.4231/R7N58JJ3

Haiguang Wen , Jiayue Cao , Junxing Shi , Kun-Han Lu ORCID logo , Yizhen Zhang , Zhongming Liu ORCID logo

11/17/2017

This document includes the main source code (Matlab or Python) related to our study.

Biomedical Engineering deep learning FMR1 LIBI Matlab natural vision neural decoding Neural encoding Neuroscience Python Code Source Code

fMRI Data for Human Subjects During Musical Perception and Imagery

10.4231/R7W957B3

Gang Chen , Haiguang Wen , Kun-Han Lu ORCID logo , Yizhen Zhang , Zhongming Liu ORCID logo

01/05/2018

This fMRI dataset includes the original stimuli and the BOLD fMRI responses for a musical imagery study.

Biomedical Engineering fMRI Inter-Session Functional Connectivity Intra-Subject Reproducibility Music Imagery Neuroscience

Next Generation Calmodulin Affinity Purification Data

10.4231/R7Q81B9G

Julia Fraseur , Tamara L Kinzer-Ursem ORCID logo

06/01/2018

Coomassie-stained gels used in semi-quantitative analysis of purified calcineurin from calmodulin Sepharose resins.

Biomedical Engineering Calcineurin Calmodulin Protein

Competitive Tuning of Ca2+/Calmodulin-Activated Proteins Provides a Compensatory Mechanism for AMPA Receptor Phosphorylation in Synaptic Plasticity

10.4231/R7ST7N11

Matthew C Pharris , Tamara L. Kinzer-Ursem ORCID logo

02/16/2018

Code for the basic 4-state competitive binding model that builds on previous work by incorporating an additional competitor for calmodulin along with a number of downstream proteins. Also include is sample code for global sensitivity analysis...

Biomedical Engineering Calmodulin Neuroscience

Simplicity of K-means versus deepness of Deep Learning. A Case of Unsupervised Feature Learning with Limited Data

10.4231/R7N58J9Z

Baichuan Zhang , Bartlomiej P. Rajwa , Murat Dundar , Qiang Kou , Yicheng He

10/01/2015

A study contrasting K-means-based unsupervised feature learning and deep learning techniques for small data sets with limited intra- as well as inter-class diversity

bacterial colonies BARDOT Biomedical Engineering Computer Science deep learning Elastic light scattering Interdisciplinary Research K-Means Clustering Life Sciences Machine Learning representation learning

Population-specific brain atlases for early-to-middle adolescent collision-sport athletes

10.4231/RTXE-0Q70

Apekshya Chhetri , Ho-Ching Yang ORCID logo , Joseph V Rispoli ORCID logo , Pratik Kashyap , Thomas M Talavage ORCID logo , Wenbin Zhu , Yukai Zou ORCID logo

10/28/2020

Population-specific brain atlases for early-to-middle adolescent collision-sport athletes in the longitudinal database of Purdue Neurotrauma Group, including cortical and white matter parcellations, T1-weighted templates, and a DTI template.

Adolescents Atlasing Biomedical Engineering Brain Informatics Morphometrics MRI Neuroscience NIfTI Spatial Normalization Statistical Methods Trauma Workflow

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