Subject
- Mechanical Engineering 4
- Bioinformatics 3
- Computer Science 2
- Interdisciplinary Research 2
- Life Sciences 2
Creator
- Zhongming Liu, 0000-0002-8773-4204 12
- Haiguang Wen 10
- Kun-Han Lu, 0000-0002-0355-8515 8
- Junxing Shi 7
- Yizhen Zhang 7
- Jiayue Cao 6
- Michael Markl 6
- Vitaliy Rayz 6
- Ho-Ching Yang, 0000-0003-2670-1772 5
- Joseph V Rispoli, 0000-0003-4514-3390 5
Type
- Dataset 41
Date
subject: Biomedical Engineering type: dataset
Total is 41 Results
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
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...
Separating Fractal and Oscillatory Components in the Power Spectrum of Neurophysiological Signal
10.4231/R7WQ01R7
09/30/2015
Matlab toolbox for separating the fractal (scale-free) component and oscillatory component in the power spectrum from the mixed time series
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
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
Repeated Free-Viewing of a Natural Movie Stimulus Using fMRI
10.4231/R71V5C4T
Haiguang Wen
,
Kun-Han Lu
,
Lauren Kelly Marussich
,
Shao-Chin Hung
,
Zhongming Liu
10/06/2017
Video-fMRI dataset acquired by the Laboratory of Integrated Brain Imaging (LIBI, https://engineering.purdue.edu/libi) at Purdue University.
Biomedical Engineering fMRI Intra-Subject Reproducibility LIBI movie stimuli natural vision Neuroscience
Display #
Results 1 - 10 of 41