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f62ec12fc510995f820ba67f317f0b5ed8217f8abb047c85dd05b6f424700a19 | Text | 633 | 3 | # ganglioside_method_paper
R scripts to process LipidSearch outputs with a focus on gangliosides
We developed R scripts to clean and filter the LipidSearch results. Briefly, our criteria for the sphingolipids were that the retention time was more than 2 minutes, the peak area was more than 1000, and the t-score was le... |
f6d4e3af97965ad4a462b745f9593027aefb5e9560e091903a41a61a71349bdb | Text | 644 | 2 | # CNNs-lightning-prediction
This codebase was developed for the CNNs lightning prediction project, which produced two manuscripts: "Predicting Cloud-to-Ground Lightning in the Western United States from the Large-Scale Environment using Explainable Neural Networks" by Kalashnikov et al. (2024) and "Projections of Light... |
a5a8da6846cb34b5b4c1a4e96391fc04ab82a6920bd63de98cfff8b54d217e97 | Text | 646 | 14 | ## Overview
```
This project hosts the data analysis scripts for the preliminary outcome data from a 2-week-long smartphone delivered attention retraining program.
Clinical Trials Identifier: NCT02977403
Data were processed in bids format following the mne_bids_pipeline.
We used custom code to extract oscillatory pow... |
577e60c7d875b8736f4337e5912253277810d6420230bdea1825560ff8a9dce3 | Text | 650 | 9 | ## A simulated annealing algorithm for randomizing weighted networks
This repository contains code written in support of the work presented in
[A simulated annealing algorithm for randomizing weighted networks](https://www.nature.com/articles/s43588-024-00735-z),
as well as data necessary to reproduce the results.
... |
c166220758bd09ccef22da352880df8e0b9defe4fdcf9861c964fff0e785750d | Text | 650 | 14 | Columms in each GWAS summary statistic file include:
MarkerName: chr:pos (in hg19)
Allele1: effect allele
Allele2: non-effect allele
Freq1: frequency of effect allele
Effect: association estimate
StdErr: standard error of the association estimate
HetChiSq: the estimated chi-squared ('Q') value representing the between-... |
8a7496d347d1f102f71c24da026b2fc9451e720a8bedd20f11cd459b8cd5dfa1 | Text | 652 | 6 | [](https://github.com/eippertlab/spinal_sep1/releases/tag/v1.1)
[](https://zenodo.org/doi/10.5281/zenodo.12658877)
[](https:/... |
8b9e89375fd47ce17ff5c78d39f85c0ecbc349f63c83ebe5096b28ce8fc7e565 | Text | 652 | 6 | [](https://github.com/eippertlab/spinal_sep1/releases/tag/v1.0)
[](https://zenodo.org/doi/10.5281/zenodo.12658877)
[](https:/... |
b41c3872b00076a0a7f03d3021a514d1c863d7d828359ea4cefc9f19d75eab5d | Text | 655 | 10 | # DLPFC-LIP
Data:
For acquiring Statistical charts in figures, download data: "Figure.pzfx";
For classification of DLPFC neurons, download data:"DLPFC_neuron classify.zip";
For classification of LIP neurons, download data: "LIP_Sequence neurons.zip", "LIP_Subsequence neurons.zip", "LIP_Element neurons_LLRR.zip", "LIP_E... |
b55c778314f3f98d59c90ad03ea68004f46adf8ad6a011933224d3ce6338225d | Text | 656 | 5 | # Huntington
ImageJ/Fiji macro script to analyse huntingtin load in immunofluorescent images of brain sections. Project in collaboration with Tamara Vasilkovska (Bio-Imaging Lab, University of Antwerp). Building blocks based on https://github.com/DeVosLab/CellBlocks.
## Citation
Vasilkovska T, Verschuuren M, Pustina ... |
bf758d42bec81158d0a5885a5513f5e0059c5fed6a24cd0042e92288a6660da9 | Text | 658 | 7 | # MotorLearningPutamen
Source code used in study: Muehlberg et al. 2024: Motor learning is modulated by dopamine availability in the sensorimotor putamen
Note that all the scripts require a specific folder setup using relative paths. These should be adapted using own requirements.
The files are published for open acc... |
d018e9b97ab4504352223d362fb7d44b78a269d9e1fc44454ddfdcce9c817401 | Text | 671 | 10 | # Phospho-regulation of ASCL1-mediated chromatin opening during cellular reprogramming bulk ATAC-seq and bulk RNA-seq analysis
This repository contains code to for the data analysis in the manuscript: Phospho-regulation of ASCL1-mediated chromatin opening during cellular reprogramming (Development, 2024)
## data avai... |
2fcbb0feda42d35475f0e695352687452345d6ff4c3670dfbaf6c811b7f08c44 | Text | 686 | 15 | main.py -> Run in a VENV (not container), Handles GUI, call docker and pipe everything through the Vol
process_subjects.py -> Run in mne docker, process and register mri/ct
segmentation.py -> Run in mne docker, segments the electrodes/probes. saves data as txt/p files
MANUAL STEP -> LABEL THE ELECTRODES (refacto... |
18dbb661c41235f580acd1d81540dbf119880d7c4767179c12d96dc930a12c64 | Text | 688 | 9 | # CMS-Net
The repository contains an implementation of CMS-Net, which is a classification problem suitable for small sample datasets of the LC-MS type.
# Data preparation
There are obvious Batch effects in MDD data, which can be corrected using batch removal effect.R.
# Training and testing
The training and testing of ... |
7d9b7db4e31b90b0b0f109d714e92ede62b1c0c78a1548a5d299ae2022ac9744 | Text | 690 | 14 |
# NeuroMET MP2RAGE pipeline
Structural preprocesing pipeline for MP2Rage
## The pipeline
The T1w<sub>UNI</sub> image from the MP2Rage sequence has an optimal contrast for the brain, but its high background noise, caused by the high (7 T) magnetic field, makes it difficult to use this image as-is with various softw... |
4f2ff1ecbcf84f83d37f965077c75c679fba2ca4702fbdb4e44d440fdc623a58 | Text | 703 | 15 | # longCOVID
long COVID scRNA-seq study
```
This repository contains code and resource files lined to our manuscript "A signle-cell RNA-seq dataset of peripheral blood cells in long COVID patients on herbal therapy".
The raw sequencing data used in this study is available in GEO under an accession number GSE265753.
... |
f7a66d2f42f4cf79644858d3113a227aee5e5f70bfc47cde9d2f5fc3493d12c6 | Text | 703 | 13 | [](https://zenodo.org/records/13368267)
This repository contains the behavioral and MEG analyses associated with the <a href="https://www.nature.com/articles/s41467-024-53406-y" target="_blank">paper</a>:<br>
### Anticipatory and evoked visual cortical d... |
4d5df715f3d00a55bd1405b61c852e1d0e68efe390e5e8fba14d628d65b60c41 | Text | 704 | 24 | # road-surface-detection-aerial
## Title
Convolutional Neural Networks for Road Surface Classification on Aerial Imagery
## Description
Source code used for paper Convolutional Neural Networks for Road Surface
Classification on Aerial Imagery. The repozitory is frozen since January 2024
at the state corresponding t... |
3325fc100d9486bee5b293b405cc5c7b840effed1ae9d30868d34b11f9a47006 | Text | 707 | 13 | # Simplified Astrocyte Model
This repository contains the code for the simulation of the simplified astrocyte compartmental model by Bezerra & Roque, Dopamine facilitates the response to glutamatergic inputs in astrocyte cell models. PLOS Computational Biology. 2023 (DOI:).
The main code is divided into three files: ... |
f3ab2bf1755dc97fa7888bb7ace9ce3b345dc6ef8026bb6d8fa01b29069a3a8d | Text | 714 | 4 | # AP_scRNA
Data and code for processing single nuclei transcriptomes from the study "Area Postrema Cell Types that Mediate Nausea-associated Behaviors" https://doi.org/10.1016/j.neuron.2020.11.010
In this repository are the counts matricies provided by zUMIs 2.8.0 of single nuclei encapsulated by InDrop. Also provided... |
c08044d44ad11e49191742cc6b99097c0817170e28fd3b168b3fd7976dca20a0 | Text | 720 | 14 | # Introduction
This folder contains the code used in the paper titled "Nexus of Depression and Subcortical Volumes: Unveiling Shared Genetic Architecture"
## Operating systems and software
Linux environment (tested on CentOS release 6.9, Ubuntu 18.04).
Python 3 (tested with Python 3.7), with numpy, scipy>=1.2.1, numd... |
c5decbdfdee9e525908d94bf73f63105a9a1030a2540b34bf62de4eb8d3a60f1 | Text | 733 | 17 | # RECOLLECT
This repository contains an implementation of the RECOLLECT architecture as described in:
A.R. van den Berg, P. R. Roelfsema & S. M. Bohte (2023). [Biologically plausible gated recurrent neural networks for working memory and learning-to-learn.](https://www.biorxiv.org/content/10.1101/2023.07.06.547911v1.... |
146083452a0f12f18eba212e7b80334ab4f8bb4e77b7e0b15bd3e06809751159 | Text | 741 | 25 | # ORCHID
Scripts for the analysis of ORCHID imaging data presented in Selfe et al. (2023).
All-optical reporting of chloride ion driving force in the nervous system. Joshua S. Selfe, Teresa J. S. Steyn, Eran F. Shorer, Richard J. Burman, Kira M. Düsterwald, Ahmed S. Abdelfattah, Eric R. Schreiter, Sarah E. Newey, Col... |
20a26aff06135c1bea9ea263eeaf14ba79276e8d92cd75d62de08258b2226b4e | Text | 744 | 23 | # General information
This dataset contains resting(eyes open) and hypoxia levels EEG recordings with 23 participants during six experimental sessions.
# Dataset
## Presentation
The data collection was initiated in November 2022 and was terminated in March 2023. The detailed description of the d... |
550099193cbc3f7b34e23476df89f0fb13e83fb55d0f7ba20acdc42e929fc255 | Text | 746 | 7 | # Drosophila_Sensory_Neuron_Quantification
The following FIJI (Neuron morphology quantifier_FIJI.ijm) and R (Compiles and sorts neuron morphology data_R.txt) codes are for use with thresholded neuronal images. The FIJI macro requires ".jpg" files within the input folder. Note: ".jpeg" files will not work. The FIJI mac... |
f77a1ec16e5c7c64404f0cd9b273eb4f1ac6ec8c042458d84ca01f24db8a9351 | Text | 749 | 3 | # README
This repository contains the code base with exemplar data to run the major analyses in the python environment. The main script is "Load_data_do_eccentricity_fpca_final.py" and can be found in "Python_code" directory. It requires the following packages: json, nibabel, nilearn, pandas, numpy, matplotlib, seabor... |
393bb4f2d07934f5748787463273f4a4b18f74a23c924757641db47b27ffd3c7 | Text | 757 | 26 |
## group graph
You can run GIN of group graph in classification tasks for molecular property prediction
```
class_task.py
```
You can run GIN of group graph in regression tasks for molecular property prediction
```
regression_task.py
```
You can run GIN of group graph in classification tasks for drug-drug... |
88353b8220619c4da673f64a40ce95dde610c11ebbc3735276d5c4e5a1fbf219 | Text | 758 | 12 | # FlyWire Visual Neuron Types
This repository contains data and code for the manuscript [Neuronal "parts list" and wiring diagram for a visual system](https://www.biorxiv.org/content/10.1101/2023.10.12.562119v3).
## See also
1. Catalog of optic lobe neuron types: https://codex.flywire.ai/app/optic_lobe_catalog
2. Libr... |
43655b815888aae29358f5579c80f45edb3c1a02dd66d485471078029964c157 | Text | 767 | 8 | # NeuronAstrocyteCounter
The following script had the aim of automatically quantifying the percentage of neurons and astrocytes from ICC imaging. It is optimized for 10X and 20X images, however, a bit of manual tuning of the detection threshold is needed for best personalized results. Example images are provided to te... |
83902c4da3535834fcd957963559021ad4bcb679a329c9f74563a39cd5bed727 | Text | 770 | 8 | [](https://github.com/eippertlab/spinal_sep2/releases/tag/v1.1)
[](https://zenodo.org/doi/10.5281/zenodo.12658895)
[](https:/... |
94b0ebd41045379f8f7d53bbe6e519dea2a14d9a2f9d11dfde972cdaea96840c | Text | 770 | 8 | [](https://github.com/eippertlab/spinal_sep2/releases/tag/v1.0)
[](https://zenodo.org/doi/10.5281/zenodo.12658895)
[](https:/... |
037c77ac8eac58e693f4f87219fb143148e9d21a19ca06745291121171ff94b2 | Text | 773 | 15 | # tre-tVMC
Taylor-Root Expansion time-dependent Variational Monte Carlo [](https://zenodo.org/doi/10.5281/zenodo.13273353)
Please cite our work if you use this code
```
@article{nys2024ab,
title={Ab-initio variational wave functions for the time-dependent many-electron S... |
b2e37757df71821dd56f061151d6241080ef536e0bfdadfd968bc3294c4c6c3b | Text | 777 | 25 | Probabilistic modeling toolkit version 3
See https://github.com/probml/pmtk3 for details.
Steps:
1. run initPmtk3.m (takes a few minutes)
2. run testPmtk3.m (takes under a minute)
3. run runDemos.m (takes about 1 hour)
The code relies on various external toolboxes (in addition to those in
pmtksupport), li... |
ec97423d3f1160a60aa869da7e5eef28542593b1f7bf27b30df484b5847e84d8 | Text | 783 | 9 | # Analysis code for: "Reorganization of structural connectivity in the brain supports preservation of cognitive ability in healthy aging"
This folder contains the code used for analyses in:
Neudorf, J., Shen, K., & McIntosh, A. R. (2023). Reorganization of structural connectivity in the brain supports preservation of ... |
34124c13bfcab9afd4945853ffc57e7ff0cf7908696e3724d1fae21bdf47bb95 | Text | 791 | 25 | # Protein binding site representation in latent space
This repository contains a pipeline for end-to-end analysis of protein latent representations learned by deep learning models.
## Setup
### Environment
This code was written in ```Python 3.8.13```. We recommend using a conda environment and installing the required... |
35b7049e54004e0e9251f75688962c1bbd06102e3f34692ad890ddf7c2c7ed18 | Text | 793 | 30 | # vanhateren
Work with [Van Hateren's natural image database](
http://cin-11.medizin.uni-tuebingen.de:61280/vanhateren/)
## Example
```python
import vanhateren
# Use the calibrated or uncalibrated dataset
vh = vanhateren.VanHateren(calibrated=True)
# Get the first image (downloads automatically)
image1 = vh.image(1... |
52afecaf3c9bb3d0ffa348eebcb7a83ce7b248090436fa4bc73eec2ebedaa547 | Text | 797 | 7 | Supporting source code and post-processing scripts for the article:
Zhou, X., Wang, Z. J., Camps, J., Tomek, J., Santiago, A., Quintanas, A., ... & Rodriguez, B. (2024). Clinical phenotypes in acute and chronic infarction explained through human ventricular electromechanical modelling and simulations. eLife, 13. https... |
4a0a4eeeaa774851aeec0e517e9e4903cd5c2ac36bbf953cb8428eebc688528a | Text | 799 | 18 |
[](https://doi.org/10.5281/zenodo.7181045)
# NeuroMET MP2RAGE pipeline
Structural preprocesing pipeline for MP2Rage
## The pipeline
The T1w<sub>UNI</sub> image from the MP2Rage sequence has an optimal contrast for the brain, but its high background ... |
7b9cae37fb2e282c23ec13fd99a2de8000f7f5b6ec1267a5e1c5b43bfece1850 | Text | 800 | 8 | # CIT-EmotionNet
The model integrates Convolutional Neural Network (CNN) and Transformer within a single framework in a parallel manner for EEG-based emotion recognition problem.
We propose a Convolution Interactive Transformer module, which facilitates the interaction and fusion of local and global features extrac... |
5c9a73de07213b036fe587f65e665c7d05201576deda9658f590ccaf80123308 | Text | 802 | 11 | # SingleTrialDynamics
This repository contains the custom behavioral and analysis functions supporting Panichello, Jonikaitis, Oh, Zhu, Trepka, & Moore, 2024.
./task/taskCode.m presents stimuli and records behavioral responses in the memory-guided saccade task.
./clust/clusterMassOneSampZ.m is the core function use... |
4dbed933b64c455f1a05eb0de8d31bfed8cf8396d4474b4a6d067afa9b57d630 | Text | 805 | 36 | # ICL_P1_Data_processing
These python and R scripts are submitted in part fullfillment of Project 1 taken place during the MRes Cancer Informatics Course at Imperial College London (ICL).
**Order of running scripts:**
1. '1_Full_TCGA_data.Rmd'
2. '2_Data_Imputation.ipynb'
3. '3_Shortlisting_Protein_List.ipynb'
4. '4... |
883e02bc3fdd935012b25a1e2fa97b663da03ee413405955f9858dede8e3ef3b | Text | 807 | 21 | # Cytosolic 3D Spot Detection
This macro detect spots in an image stack in 2 channels and report the number of spots, their overlap and normalize it by the cytosolic volume calculated as the volume left by the nuclear staining (eg DAPI).
This macro was written by Ulrike Schulze.
# Requirements
- [Fiji](https://image... |
50ac7b9566c3b589ea68027de64cabfe65081b385cb6789a2790a598653ea24f | Text | 809 | 10 | # iEEG_connectomics
This repository contains all the code necessary to reproduce the results from the main article submitted to the journal.
The following folders are included:
1. iEEG_Preprocessing - includes the analysis of the invasive electrophysiology data (https://mni-open-ieegatlas.research.mcgill.ca/)
2. MRI_C... |
c5b51f5728b09497966cbaab34c5edb7fa5ea80f7b3d296b98a4b66e85a4e98e | Text | 811 | 22 | # Analysis pipeline for *No evidence of interaction between FADS2 genotype and breastfeeding on cognitive or other traits in the UK Biobank*
Snakemake workflow for analysis and plots for the manuscript on the gene-by-environment interaction between *FADS2* and breastfeeding on cognitive traits, cardiometabolic measure... |
4ae150e76dd77f699ec32654ec8596170708b0d4b8b525fee6d0adf3c7105f3a | Text | 812 | 1 | affectr is a an r package for sentiment analysis. The built in dictionaries permit accurate classification of text along three affective dimensions: rationality vs. emotionality, social impact, and valence (positive vs. negative). These dimensions have been found to organize the neural representation of others' mental ... |
a6089a919975050ce772f56440a6e4ce590e83aaaf5895b2c60bc828450ec056 | Text | 815 | 19 | # PFC-LDS-approx
Code to fit context-dependent linear dynamical systems (LDS) and tensor factor regression (TFR) models to approximate PFC responses during contextual decision-making, as appears in:
_Inferring context-dependent computations through linear approximations of prefrontal cortex dynamics_, Soldado-Magraner ... |
6a2a6f1b98d23986c4bc1a44321f058c7f0891a94455dc6da925d817fcd2bf91 | Text | 820 | 41 | deepsignal2
===========
Release
-------
0.1.4
-----
optimize/test more on multi-gpu support in call_mods module
add scipy==1.7.3 in requirements (floating point error in scipy>=1.9->tombo). fix this in deepsignal2, although tombo only is the pre-process tool for this tool.
replace np.int/np.float with i... |
69f6da9507180fa04fa10375148d4bbbf6f87e0bd518253f6d9f1b813caf7f96 | Text | 823 | 4 | # Vit_Flavonoid
Vision transformer (ViT)-based deep neural network is applied to classify the flavonoid glycoside isomers by analysis of the spectrum of electrospray ionization tandem mass spectrometry (ESI-MS/MS). Our model successfully classified the flavonoid isomers as various substituted pat-terns between flavonoi... |
7678e620f1903b6b41a6b3bc04c9e01b375b7c7f7c842d8c274e6418771b9a17 | Text | 835 | 10 | # Pipette-Cleaning-Software
By Mighten Yip and Corey Landry ([Precision Biosystems Laboratory](http://pbl.gatech.edu/) at Georgia Tech, 2020).
Software based on the cleaning methods as published in Bio-protocols ([source]). Improved upon the reuse method introduced by [Ilya Kolb et al](https://www.nature.com/articles/... |
4e1230718a4693c340b6da57eb03d6bc5921afab62801e0d0ca202248235e476 | Text | 844 | 10 | # disperseNN2
[](https://dispersenn2.readthedocs.io/en/latest/?badge=latest)
[](htt... |
ceb764be3c7afe661cc16e3a795730721e28bdd9074241d4c941e17b30f3129b | Text | 848 | 38 | # Adjoint Method-based Fourier Neural Operator Surrogate Solver for Wavefront Shaping in Tunable Metasurfaces
## Data preparation
Our metalens dataset used in the paper can be accessed on [GoogleDrive](https://drive.google.com/file/d/1WDrvt3TtVXNnNFYRgFmbYpTg0nblSOw5/view?usp=share_link).
The train-test data should... |
4bf5a72a17ea8e2b6a0cedc626d289acd09e136cddda1ea33bcaa043d71ae194 | Text | 854 | 17 | # 3D Single Molecule Localisation Microscopy Data Analysis
## Applied to 3D PSD95 localisations
# Author: Leila Muresan (https://github.com/lemur01)
<img src=CleanedData.png width="400" height="300"><img src=Sample.png width="550" height="300">
AnalyseExperiment:
- Separates pointillist localisation data into monom... |
38d4cf8f1345f61f776e2607b0c1137357392bf017847291cc72258f71d9ef61 | Text | 856 | 26 |
Scripts needed to perform the adaptive rewiring simulations and data analysis in
the article:
Luna, R., Li, J., Bauer, R., & van Leeuwen, C. (2023). Retinal waves in adaptive
rewiring networks orchestrate convergence and divergence in the visual system.
Network Neuroscience
1- You will first need to... |
51a4e6263e595a3f8c49e06de393f1937ceb03e7d032c2471675000d987df197 | Text | 861 | 3 | # HIE
Here you will find the [supplementary material](https://gin.g-node.org/johndlewis/HIE/src/master/Supplementary%20Material) for our paper "Automated Neuroprognostication via Machine Learning in Neonates with Hypoxic-Ischemic Encephalopathy", as well as our new population specific neonatal brain multi-contrast MRI ... |
91bd8fc4c9b19d2746ec056d8fc128922e6bfdd7777a525135427a29045249d9 | Text | 871 | 15 | # Readme
This repository contains R code for the main analysis of the following submitted manuscript:
“Machine Learning-based Prediction of Elevated NT-pro BNP among US General Population” (ESCHF-23-01016)
For contact information, please refer to the corresponding author details provided in the paper.
The original... |
d18068ad7b598a82fea3e0456901ab5d148c55cb294acac8f3d5e064b4ddf460 | Text | 882 | 27 | # Adaptive_Rewiring_CalciumWaves
Scripts needed to perform the adaptive rewiring simulations and data analysis in
the article:
Luna, R., Li, J., Bauer, R., & van Leeuwen, C. (2024). Retinal waves in adaptive
rewiring networks orchestrate convergence and divergence in the visual system.
Network Neuroscience, 8(3),... |
5ea34bf9459b00e6ab5434d4ce94926e17c1c3eb36fb1a83bc3068ca4de354b8 | Text | 883 | 17 | This directory contains the essential code used in the the Stasinski et al. 2024 paper.
TO run the dFIC tuning we recommend to read use and adapt the code in sample_dFIC_script.py:
- using your own SC would require changing the setup of connectivity object
This code requires a preinstalled The Virtual Brain and uses... |
30856535120221d308a5e199066c101e7eb0f30ccacdc375bf610938f4fdac9e | Text | 884 | 10 | # Kirai Dataset
A new accurate ground truthed dataset of aerial high dynamic range infrared imagery containing heat signature of koalas. The dataset is known as Koala InfraRed Aerial Imagery (Kirai). The paper proposing the dataset has been published on MPDI sensors journal. The Kirai dataset has been made publicly ava... |
8db49b83e83b237f4bd6472dc54eaa99d7152587e09991b52837408b43c6414a | Text | 889 | 23 | ## Zagare_2025_WT-part
## Introduction
This is the code repository for the "Insulin resistance compromises midbrain organoid neuronal activity and metabolic efficiency predisposing to Parkinson's disease pathology" project.
Please check and cite complete manuscript at [doi: 10.1177/20417314241295928](https://... |
d93aa11d8b3a2599740aafbf7dbb94aaa8cf15b24ebc3819097b01e9f82eb4f7 | Text | 892 | 24 | MorphoHub <Petabyte-Scale Multi-Morphometry of Single Neurons for Whole Brains>
===
---
>*Designed by Shengdian Jiang, 2020-02-12
Email: allencenter@seu.edu.cn*
## MorphoHub has the following components:
1. MorphoHub_DBMS:
- Multi-level data generation and workflow management.
- Version control of morphometry ... |
e1c87553c341f48bc96f790f42ac7714d254bbe3ad893c48fc0b7f665cfaadfb | Text | 895 | 37 | awake-mice-pupil-fMRI-analysis
Software（Windows system): MATLAB R2023a; AFNI_23.0.02
Example file:
Pupillometry recording
Codes:
AFNI:
n_command: main script that can call different fMRI preprocessions
n_mysetting: set up the datasets (raw, processed, atlas) address
o_corr_X: the GLM analysis
r... |
2431f248cb12a2fbb770ea49b6e353487071583a4d54713e9a644b907d1e255e | Text | 898 | 37 | ===========
m6A-calling
===========
.. image:: https://img.shields.io/pypi/v/m6a_calling.svg
:target: https://pypi.python.org/pypi/m6a_calling
.. image:: https://img.shields.io/travis/mrvollger/m6a_calling.svg
:target: https://travis-ci.com/mrvollger/m6a_calling
.. image:: https://readthedocs.org/pr... |
ce2fb2606d8cc80adad69657841ba67097269d085f815c196e1bed3ffe792a54 | Text | 905 | 42 | # Fast Median
Median estimator
Python implementation of real time median estimator
## Publication
For an explanation of the algorithm see [1].
If you use this algorithm, pleas cite:
Burman A, Solé-Casals J, Lew SE (2024) Robust and memory-less median estimation for real-time spike detection. PLoS ONE 19(11): e030... |
e8e5d498ad6c7c4226214b4823179c846f34e094370a0801e6ce8ef609946bee | Text | 906 | 16 | # VimbaPeron!
This script is used to acquire images with Allied Vision cameras using Python API of Vimba SDK. Tested on model Alvium 1800 U-500m
Vimba for Windows can be downloaded from here:
https://www.alliedvision.com/en/products/vimba-sdk/
Requires to install openCV. It has been tested with pip install opencv-py... |
b772a8cf95fb9ddbe58949c5bf03b3b510114412f5fdfa7e2a937ed9b631f9dc | Text | 910 | 42 | # Brain Structural Classification Workflow
This experimental project processes volumes and centroids of various brain structures using pretrained machine learning algorithms.
## Requirements
- FreeSurfer
- Python 3.x
- Required Python packages (see requirements.txt)
## Installation
### Python and Required Packages... |
424fbdc80509423dc0f91934c0c9ac41f96bccef96aa96274c7419aa0376dac2 | Text | 911 | 14 | # Sieu-et-al_2024
## Summary
This repository includes the analysis codes implemented for the main figures in
**Slow and fast cortical cholinergic arousal is reduced in a mouse model of focal seizures with impaired consciousness**
Lim-Anna Sieu, Shobhit Singla, Jiayang Liu, Xinyuan Zheng, Abdelrahman Sharafeldin, G... |
d5603079bf34541db12d0e84ef308fd0b3c388413771344910b643dbf4cb6c95 | Text | 914 | 26 | # Postoperative brain tumour segmentation with BraTS
convert_brats2021_to_twolabel.py converts BraTS2021 segmentation files to a two-label format provided HD-GLIO segmentation files.
# Prerequisites:
The python script requires the packages:
argparse, numpy, nibabel and scipy.
# Usage:
python convert_brats20... |
0e48b9b0a75b74a5a8d1cfe9ad5a6f8fab3c8ace59d39852b6727aa2bf37db27 | Text | 917 | 19 | # Node-Edge-Graph-Attention-Networks
Adversarial Learning Based Node-Edge Graph Attention Networks for Autism Spectrum Disorder Identification
## Description
1. Model Interpretability see [BrainVisial.ipynb](./BrainVisial.ipynb)
2. The norm trained, FGSM trained and PGD trained see [k-fold.ipynb](./k-fold.ipynb)
3. Mo... |
929242c8ba41bf3c763be5d326474325b4fb9b8469b4eeb2206051ba86e00b92 | Text | 917 | 31 | # DevCCF to CCFv3 mapping
Code for generating analyses for Figure 5 in Kronman et al. (doi: 10.1101/2023.09.14.557789)
### Requirements
#### System requirements
Mapping requires a single computer workstation with enough memory to load data.
#### Dependencies
All code is written in the python (3.11) environment
R... |
3cc86d41a9dba7b1c3d50e0e6ea41caddd1b7a5ebc396108afcfd12d50fde412 | Text | 923 | 23 | # LGMF-GNN
Code of paper "An Objective Quantitative Diagnosis of Depression Using Local-to-global Multi-modal Fusion Graph Neural Network"
## Overview
Content includes source code for the implementation of local-to-global multi-modal fusion graph neural network on large multi-site MDD fMRI datasets for major depressiv... |
0ad0ee80ff62e0788e8e176392d963e135854ab58b9bb293ee41baaa8f7d3b18 | Text | 924 | 8 | # Metabolomic profiles differentiate between porto-sinusoidal vascular disorder, liver cirrhosis, and healthy individuals
## Description
These notebooks were developed and used by Oleksandr Petrenko to analyze metabolomics datasets for the study:
G. Semmler*, O. Petrenko*, J. Jose Lozano, S. Shalaby, J. I. Sánchez-A... |
cffa284eb056436be8d83011539e8ecd47b452cfbd6fd16a15a0f629b25ff8b5 | Text | 925 | 21 | # Neural Radiance Fields for Fisheye Driving Scenes using Edge-aware Integrated Depth Supervision
We propose an edge-aware integration loss function, which leverages sparse LiDAR projections and dense depth maps estimated from a learning-based depth model. Our algorithm assigns larger weights to neighboring points that... |
e63f3454b6492316ab3eafb652d37a1a33fc34ef3710030d31acb4fa64926473 | Text | 926 | 17 | [](https://pypi.org/project/scbs)
[](https://pepy.tech/project/scbs)
[](https://github.com/LKremer/scbs/stargazers)
# `scbs`: A Command L... |
ead96e5cd521b7797b0139869a80e77638f9284e1bb412c32c8f54d01abb12e6 | Text | 929 | 16 | # Description
ProteoMill is a fast, efficient web-based tool for exploring functional enrichment of expression sets. It is freely available at https://proteomill.com/
# Directory structure
ui.R contains the structure of visual components
server.R contains core functions that communicate with ui.R
global.R contains add... |
68e94d2ea94d633e1c7a767ed086e0f3a2426317efeb7706d80dc3600cfefa3d | Text | 930 | 13 | # spdm <img src='man/figures/logo.png' align="right" height="138.5" />
The **spdm** package contains routines for the analysis of symmetric, positive-definite (SPD) matrices. For in-depth details and instructions, see the [documentation](https://areshenk-rpackages.github.io/spdm).
**spdm** is designed largely for geo... |
c622202fee7924a06e3b1ab5597d4a712d8a0ad16642ac8d579a9f9c1689b1fe | Text | 934 | 14 | README - Adenosine deficiency facilitates CA1 synaptic hyperexcitability in the presymptomatic phase of a mouse KI model of Alzheimer disease. Bonzanni and Braga et al.
The following files are deposited:
- README file.
- MATLAB file and decoder code (Dataset.mat, DataDecoder.m).
- Excel Files containing single ... |
5d34b0bc521afea6239541b910deb8999777cd3e5fae58766ff457c4a544297f | Text | 936 | 11 | # GradientAnalysis
***
- lineprofile.ijm: ImaageJ macro to extract the intensity profile in the embryo, given a manually drawn line ROI, for a list of input images with two channels (DIC+fluorescence)
Run in Fiji/ImageJ. Output: directory ./Results with list of txt output files with the intesity profile per image
***
... |
51a0f88c258164b5d77612e4d7f8b9dce95e8313856ef5adc607008d4297ff80 | Text | 941 | 12 | # Gamma_Oscillations_PCx
This repository contains all python codes to reproduce Figures 1-7 of
Gonzalez, J., Torterolo, P., & Tort, A. B. L. (2023). Mechanisms and functions of respiration-driven gamma oscillations in the primary olfactory cortex. eLife, 12, e83044. https://doi.org/10.7554/eLife.83044
The datasets sh... |
6ffa30be6f92ad2104fe6bfc51c31f5c0c57c7c3942d8afaedbd168ea8c41136 | Text | 943 | 21 | # Codes for symptom-based depression subtypes
This repo contains the codes and collect data for replicating the results in our paper about exploring the biological underpinnings for MDD subtypes.
## inputs
This folder contains the raw subject list table (subject_merge_MDD_HC.xlsx), and the generated files for each a... |
b9dc646abd39d42ff2aaf77c87a487e3ef16aa980c7dd47a677fb6bfc1ad2d27 | Text | 945 | 17 | # orientation_tuning_drift
Code to produce figures 1 and 2 (and associated supplementary figures) from Bauer et al., 2023 (https://doi.org/10.1101/2023.09.22.558966)
The data can be downloaded from https://gin.g-node.org/Joel-Bauer/orientation_tuning_drift
### requirements
Code was tested on MATLAB R2018a. Please inst... |
0227f980881d3b0148fb3c63b7a32345faaed2915b4bffc44e913d367dcfbf08 | Text | 947 | 29 | # Voice analysis in dogs with deep learning: development of a fully automatic voice analysis system for bioacoustics studies
### This repository contains the implementation of the study mentioned in the paper. If you use it in your work, please consider citing it.
https://doi.org/10.3390/s24247978
```
# may... |
f9d905b879dcec32d30721f3c5d670ec7b134eb4cf29525fd6d84322ab8c1892 | Text | 967 | 8 | # DPABI: a toolbox for Data Processing & Analysis for Brain Imaging
[DPABI](http://rfmri.org/dpabi) is a toolbox for Data Processing & Analysis of Brain Imaging, evolved from [DPARSF](http://rfmri.org/DPARSF) (Data Processing Assistant for Resting-State fMRI) and contains [DPABISurf](http://rfmri.org/DPABISurf), [DPAB... |
bd79fdca3f43165961c9ff71926a09c8f221ddd73c1f9dd935ea674e1cd93e62 | Text | 975 | 15 | # psg-simultscoring-models
Model definitions used in the manuscript by Huttunen et. al titled "[A Comparison of Signal Combinations for Deep Learning-Based Simultaneous Sleep Staging and Respiratory Event Detection](https://ieeexplore.ieee.org/document/9964431)"
The models are based on https://github.com/perslev/U-Ti... |
45c7112e73f208f1f2401c9601ac97b95c3ebf14567cb6cb77b5c3d84a5bb0ed | Text | 977 | 14 | ## **Exploring PDE5A upregulation in bipolar disorder: insights from single-nucleus RNA sequencing of human basal ganglia**
## **Description**
This github repository contains the source code related to the manuscript entitled **"Exploring PDE5A upregulation in bipolar disorder: insights from single-nucleus RNA sequenc... |
97f3d8d356a99b0d1ab1925bf243ce34385760544dff1f22902e6bc857668440 | Text | 978 | 9 | # 3D-Texture-Analysis
# Overview
Our in-house developed 3-dimensional method, VGLCM-TOP-3D, uses the GLCM approach to compute voxel-wise texture maps of MRI images. Ref: Voxel-Based Texture Analysis of the Brain Maani R, Yang YH, Kalra S (2015) Voxel-Based Texture Analysis of the Brain. PLOS ONE 10(3): e0117759. https... |
4b316708a3fc7da6311c6b339decb8963da7926f9edfcd4cc425b3bdc336d4f7 | Text | 985 | 43 | # Photometry
This software read data from DORIC Neuroscience studio .A signal GCamp 465 nm and Isobestic 405 nm synchronized with Behavioral type and duration.
Trend Correct... |
70457dcb07ce37dedccf64f93b3138a6497622d3ae3c66da0a5201d11dc18379 | Text | 985 | 9 | The repository contains two archive files:
- `processed.zip` (16Gb), once unzipped, a folder containing the preprocessed MEG data for 13 of our subjects. Each subject folder contains two folders:
- `bem`: with a single file, the source model `oct6-src.fif`
- `meg`: with preprocessed MEG files (MNE-python format):
... |
4872a909c715aecf2a77f4b257c33dc03d2db87c8d580505996c09308f36d5be | Text | 991 | 9 | Code repository for the stimulus and data analysis used in the study [A chronometric relationship between circuits underlying learning and error monitoring in the basal ganglia and salience network](https://doi.org/10.1162/imag_a_00343).
# Folders:
- Task: stimulus code. **Requirements**: Psychtoolbox 3.0
- Protocol_d... |
a6e9fcc9f9a69fd931109dcc769532f6790db19674036c435498a47f30c7e662 | Text | 991 | 21 | # layer4-temporal-patterns
This repository contains spike-sorted single unit recordings from Layer 4 neurons in rat barrel cortex responding to various whisker stimuli.
## Data Organization
The data consists of CSV files containing spike-sorted neural responses, where:
- Each file (e.g., `6042062.csv`) represents a ... |
a2de3c35a9bc2922633a58693145037455131c6362d7119c071661125e482bff | Text | 997 | 24 | # Temporal structure abnormality in agitated depression
#### Description
This repository provides the code and necesary data files to replicate the analysis on the time delay heterogenous in clinical subtypes.
#### File Architecture
**/scripts** contains the R code to run the main analysis. Please run the codes in t... |
bc7b591f008573eed38e5a523796404c9c0af8b83ed8d5035fcbdd1b263fc759 | Text | 1,006 | 9 | This repository contains scripts for reproducing the graphs and statistic results of the manuscript 'From silence to song: Testosterone triggers extensive transcriptional changes in the female canary HVC' https://www.biorxiv.org/content/10.1101/2022.06.13.495861v3
Data were deposited on dryad: https://doi.org/10.5061... |
1022d37738b52c672304dbe71038a4a1f0d2cac5de3c9178652873a5698a8674 | Text | 1,007 | 33 | # Google Research
This repository contains code released by
[Google Research](https://research.google).
All datasets in this repository are released under the CC BY 4.0 International
license, which can be found here:
https://creativecommons.org/licenses/by/4.0/legalcode. All source files in this
repository are relea... |
8555c2bbe8fb4d744f0183f2ff6431472a30ff7837d8534b727528a664f105b5 | Text | 1,014 | 12 | # dry
Free-water elimination for diffusion MRI with synthetic data and deep learning.
Diffusion metrics are typically biased by Cerebrospinal fluid (CSF) contamination. In this work, we present a deep learning based solution to remove the CSF contribution. First, we train an artificial neural network (ANN) with synth... |
454e1d030201be7547a3255efca9eecf0a86fc7ab863c7a23c13a09cceee0298 | Text | 1,027 | 24 | # EpiRev
**EpiRev** is a collection of notebooks for completing a systematic review of methods for identifying epilepsy surgery targets using invasive EEG.
## Publication
This repository accompanies the following systematic review:
> Ivankovic K. et al. — [Methods for identifying epilepsy surgery targets using inva... |
e0c3b16ed0b10ff11d1c2e35bfba01755bdd71ebd25f351178e1f37111cc6489 | Text | 1,027 | 14 | # evrbhi (emotion-vr-brain_heart_interaction)
Analysis scripts for **Fourcade et al., (2024) - Linking brain-heart interactions to emotional arousal in immersive virtual reality**. *Psychophysiology*. DOI:10.1111/psyp.14696
Folders:
* BHI_modeling - contains the brain-heart interaction (BHI) modeling and analysis
* E... |
d68446958e1e14ff8c6dc008d3433147cf475c1b3f5085295f1f35089c9d5662 | Text | 1,035 | 25 | # Deep Learning for Hypertension forecasting
This repository provides the means of fast prototyping and experimenting with the models for Hypertension forecasting.
## Environment Installation
To prepare all needed libraries, create the environment from the file using Anaconda.
```
conda env create --file environment... |
a7cb3d8b97ac60a5246b5c9c599d1b1fb5f26334f5a35fc7eaec4ff523f849ba | Text | 1,038 | 3 | This software package includes code for decoding muscle activity from motor cortex (MCx) signals and afferent activities. It also contains an example data file to demonstrate the functionality of each function. The code is written in MATLAB as .m scripts and has been tested on MATLAB R2022b running on a Windows 11 v22H... |
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