PURR Registry

Animal Model Dependent Response to Pentagalloyl Glucose in Murine Abdominal Aortic Injury

10.4231/1FQ0-P419

Craig Goergen , Elizabeth Niedert , Ender Finol , Jennifer Anderson , Renxiang Tang , Riley Holloway , Sourav Patnaik , Vangelina Osteguin

01/12/2021

This dataset accompanies the Journal of Clinical Medicine article by the same name (https://doi.org/10.3390/jcm10020219) and includes all data discussed therein. Please contact Craig Goergen with any questions at cgoergen@purdue.edu.

abdominal aortic aneurysms Biomedical Engineering elastin pentagalloyl glucose ultrasound

Mathematica Files: Competitive tuning: competition’s role in setting the frequency-dependence of Ca2+-dependent proteins

10.4231/R7154F7Q

Daniel Romano , Matthew C Pharris , Neal Patel , Tamara Kinzer-Ursem

09/08/2017

We study the competition among seven well-studied neuronal proteins for their common binding partner, calmodulin. We find that competition narrows and shifts the range over which proteins can be activated.

Biomedical Engineering Calcineurin Calmodulin Computational Biology Mathematica Signal Transduction

Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 1

10.4231/R7X63K3M

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

09/15/2017

This is a video-fMRI dataset for subject 1 (out of three) acquired by the Laboratory of Integrated Brain Imaging (LIBI),

Biomedical Engineering deep learning fMRI LIBI natural vision neural decoding Neural encoding Neuroscience

Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 2

10.4231/R7NS0S1F

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

09/18/2017

This is a video-fMRI dataset for subject 2 (out of three) acquired by the Laboratory of Integrated Brain Imaging (LIBI).

Biomedical Engineering deep learning fMRI LIBI natural vision neural decoding Neural encoding Neuroscience

Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 3

10.4231/R7J101BV

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

09/15/2017

This is a video-fMRI dataset for subject 3 (out of three) acquired by the Laboratory of Integrated Brain Imaging (LIBI).

Biomedical Engineering deep learning fMRI LIBI movie stimuli natural vision neural decoding Neural encoding Neuroscience

Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Stimuli

10.4231/R71Z42KK

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

09/15/2017

This is a video-fMRI dataset contains the videos with stimuli acquired by the Laboratory of Integrated Brain Imaging (LIBI).

Biomedical Engineering deep learning fMRI LIBI movie stimuli natural vision neural decoding Neural encoding Neuroscience

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

10.4231/R7V98675

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

09/25/2017

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

Separating Fractal and Oscillatory Components in the Power Spectrum of Neurophysiological Signal

10.4231/R7WQ01R7

Haiguang Wen , Zhongming Liu

09/30/2015

Matlab toolbox for separating the fractal (scale-free) component and oscillatory component in the power spectrum from the mixed time series

Bioinformatics Biomedical Engineering fractal scale-free

A Non-parametric Bayesian Model for Joint Cell Clustering and Cluster Matching: Identification of Anomalous Sample Phenotypes with Random Effects.

10.4231/R7KK98PG

Bartlomiej P. Rajwa , Ferit Akova , Halid Ziya Yerebakan , Murat Dundar

09/03/2014

The manuscript presents a non-parametric Bayesian algorithm called ASPIRE (Anomalous Sample Phenotype Identification with Random Effects) able to identify phenotypic differences across batches of cytometry samples in the presence of random effects

AML Bayesian Biomedical Engineering BMC Bioinformatics Computer Science cytometry Dirichlet process Gaussian mixture model Interdisciplinary Research Life Sciences random effects

Signal Processing Toolbox for Simultaneously Acquired fMRI and EEG

10.4231/R7DB7ZSC

Rodrigo Castellanos , Zhongming Liu

06/07/2016

This Matlab toolbox includes signal processing functions to remove gradient and pulse artifacts in EEG data recorded simultaneously with fMRI. It is distributed as a GUI plugin for EEGLAB.

Bioinformatics Biomedical Engineering Electrical and Computer Engineering fMRI-EEG independent component analysis Signal Processing Singular value decomposition

Datasets

Subject

Creator

Type

Date

Total is 41 Results

Animal Model Dependent Response to Pentagalloyl Glucose in Murine Abdominal Aortic Injury

Mathematica Files: Competitive tuning: competition’s role in setting the frequency-dependence of Ca2+-dependent proteins

Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 1

Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 2

Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 3

Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Stimuli

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

Separating Fractal and Oscillatory Components in the Power Spectrum of Neurophysiological Signal

A Non-parametric Bayesian Model for Joint Cell Clustering and Cluster Matching: Identification of Anomalous Sample Phenotypes with Random Effects.

Signal Processing Toolbox for Simultaneously Acquired fMRI and EEG

Datasets

All fields DOI Author Subject Search

Subject

Creator

Type

Date

Total is 41 Results