sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 17k | content stringlengths 1 200k |
|---|---|---|---|---|
5afc575593b7867af3fe89b8ffacc6358c7a4fc9e7efcfad9254b49fdaab90b5 | Shell | 28,357 | 923 | #!/bin/bash
# Bash shell script to process diffusion & structural 3D-T1w MRI data
#
# Requires Mrtrix3, FSL, ants
#
# @ Stefan Sunaert - UZ/KUL - prof.sunaert@gmail.com
# @ Ahmed Radwan - KUL - radwanphd@gmail.com
#
# v0.1 - dd 09/11/2018 - created
version="v1.3 - dd 27/11/2021"
# To Do
# - fod calc msmt-5tt in stead... |
fc99e1be7b571f9d61b4cf90e721e42bebcc70e1a830005e3b0e33f9c644d8bc | Shell | 31,335 | 691 | #!/bin/bash
set -e
if [[ $# -lt 12 ]];then
echo "usage: sh $0 -SN -dataDir -registJson -speciesName -tissueType -outDir -imageRecordFile -imageCompressedFile -doCellBin -threads -sif
-SN : sample id
-dataDir : output directory of gene expression matrix result
-proteinList : protein list file which cont... |
77c0e03472c4c0a928d8413aad8053455a07955199233e18d43eed403cc94277 | Shell | 32,626 | 743 | #!/bin/bash
set -e
if [[ $# -lt 12 ]];then
echo "usage: sh $0 -splitCount -maskFile -fq1 -fq2 -refIndex -genomeFile -speciesName -tissueType -annotationFile -outDir -imageRecordFile -imageCompressedFile -doCellBin -rRNARemove -threads -sif
-splitCount : count of splited stereochip mask file, usually 16 for Q4 ... |
1c62e0142c110d1c46e2dfa380655ba7eba04f6649ca8630c57283157218ee52 | Shell | 40,179 | 895 | #!/bin/bash
set -e
if [[ $# -lt 12 ]];then
echo "usage: sh $0 -splitCount -maskFile -rnaFq1 -rnaFq2 -adtFq1 -adtFq2 -proteinList -refIndex -genomeFile -speciesName -tissueType -annotationFile -outDir -imageRecordFile -imageCompressedFile -doCellBin -rRNAremove -pidStart -threads -sif
-splitCount : count of spl... |
f11b83115291b633feb54c38605931a3768bbfd8609f83e2550a2000f9caa641 | Shell | 43,846 | 1,327 | #!/bin/bash
set -x
# Ahmed Radwan ahmed.radwan@kuleuven.be
# Stefan Sunaert stefan.sunaert@kuleuven.be
# # v 1.0 - dd 20/03/2019 - dev Alpha
v="1.0 - dd 20/03/2019"
# This script is meant for allowing a decent recon-all output in the presence of a large brain lesion
# It is not a final end-all solution but a r... |
dd841b46ba330e5ae8983026e6f3b0e3d66bff2d2c66c801396ed1d995e071cc | Shell | 44,836 | 998 | #!/bin/bash
# Sarah Cappelle & Stefan Sunaert
# 22/12/2020 - v1.0
# 18/02/2021 - v1.1 (adding calibration)
# 24/10/2022 - v1.2 (accepted for publication)
# 17/08/2023 - v1.3 bug fix (using local path)
#
# This script computes a T1/T2, T1/FLAIR and MTC (magnetisation transfer contrast) ratio
#
# This scripts follows t... |
bf68a37acebfd26acf200d333883db976d8d654080d0e7136a2d3f3e2548f209 | Shell | 46,053 | 1,342 | #!/bin/bash
# Bash shell script to analyse clinical fMRI/DTI
#
# Requires matlab fmriprep
#
# @ Stefan Sunaert - UZ/KUL - stefan.sunaert@uzleuven.be
# 07/12/2021
version="0.9"
kul_main_dir=$(dirname "$0")
script=$(basename "$0")
source $kul_main_dir/KUL_main_functions.sh
# $cwd & $log_dir is made in main_functions
# ... |
8e0b7187801a66fecc6288e75531d4b81f915ada6f89b1eaf750b2711ebac422 | Shell | 50,435 | 1,591 | #!/bin/bash
# set -x
# Bash shell script to convert dicoms to bids format
#
# Requires dcm2bids, dcm2niix, Mrtrix3
#
# @ Stefan Sunaert - UZ/KUL - stefan.sunaert@uzleuven.be
# @ Ahmed Radwan - KUL - ahmed.radwan@kuleuven.be
#
version="v0.9 - dd 29/11/2021"
# Notes
# - NOW USES https://github.com/UNFmontreal/Dcm2Bid... |
5f1ebdcbbcbec0447f9142735cac06627cd0517283259b4d9e8688fc7325f1ef | Shell | 50,528 | 1,588 | #!/bin/bash
# set -x
# Bash shell script to convert dicoms to bids format
#
# Requires dcm2bids, dcm2niix, Mrtrix3
#
# @ Stefan Sunaert - UZ/KUL - stefan.sunaert@uzleuven.be
# @ Ahmed Radwan - KUL - ahmed.radwan@kuleuven.be
#
version="v0.9 - dd 29/11/2021"
# Notes
# - NOW USES https://github.com/UNFmontreal/Dcm2Bid... |
a1de4e654ddaebeb73844d09f738416ca3387aedcb6db7b8a482642b6caa433b | Shell | 52,790 | 1,343 | #!/bin/bash -e
# Bash shell script to process diffusion & structural 3D-T1w MRI data
# Developed for generating major fiber bundles for presurgical mapping with Tensor_Prof abd iFOD2 msmt_CSD
# for S61759.
# Project PI: Stefan Sunaert
#
# Requires Mrtrix3, FSL, ants, freesurfer
#
# @ Stefan Sunaert - UZ/KUL - stefan.... |
1d28820f6a86414cda4df393f2959e09e80788706541183eeefc6a2ffd9c95b5 | Shell | 68,958 | 1,853 | #!/bin/bash
# @ Stefan Sunaert & Ahmed Radwan- UZ/KUL - stefan.sunaert@uzleuven.be
#
# v0.1 - dd 06/11/2018 - first version
version="v1.1 - dd 21/01/2021"
verbose_level=1
# This is the main script of the KUL_NeuroImaging_Toools
#
# Description:
# This script preprocces an entire study (multiple subjects) with struct... |
1eb5b5c1cf4a9de15c53b86cf56c15db1538f1acdf664186dd803d6ae607e21d | Stan | 417 | 19 | data{
int ns;
int nt;
row_vector[ns] slp_sim_ground_truth[nt];
row_vector[ns] slp_true[nt];
}
parameters{
real amplitude_star;
real offset;
}
transformed parameters{
real amplitude = exp(pow(0.5, 2) + log(1.0) + 0.5*amplitude_star);
}
model{
amplitude_star ~ normal(0, 1.0);
offset ~ normal(0, 1.0);
... |
7ffbdd8a9494216de3bc56000fdbf8b53fcd9735b0fb9bc9061330525cfd8e2d | Stan | 470 | 32 | functions {
}
data {
int nn;
int ns;
int nt;
matrix[ns,nn] gain;
real epsilon;
real sigma;
// Modelled data
row_vector[ns] seeg[nt];
}
parameters {
row_vector[nn] x[nt];
real offset;
real alpha;
}
model {
row_vector[ns] mu_seeg[nt];
alpha ~ normal(0,1);
offset ~ normal(0,1);
for (t ... |
4482dd3fb767ca19281e38ee1740a4962864d13b0ab349220d32eb8a5821304b | Stan | 1,830 | 79 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
b6875aec9900ca63fe264a4610ad468fe7e76d6228a1586a2a3c2e30ffab9a23 | Stan | 1,956 | 82 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step, real time_scale,
real sigma) {
int nn = num_elem... |
6bfa4d881e1830562ddc7a712c34629492dbe8d6db3c2764404281db6843699b | Stan | 2,533 | 104 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
7a5a09ff337f389798edf6269ef18cd3bba35e82fbdc3a8e75509208dbe0563d | Stan | 2,533 | 104 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
3edbf0e3bac8a737525ccec5f28c9c0e823109e2f484d537f66fd13e61ad4c97 | Stan | 2,624 | 99 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
a61e07de2afb61ff7567c040574c4030c6c9f83f2815db670da64c18aad6074f | Stan | 3,138 | 114 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
6dd8ede753ce1e69d4660d35251f2132da7a2c507d503c6d4dadddda03440fcd | Stan | 3,257 | 116 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
8471f998fe3e73c099be1f4dd1e65cb0911fb08b6ca7e423bb1b829f050b48f2 | Stan | 3,402 | 117 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
1ce9d577286b1de6c48630dd6eed430d528bed217b1f888cb69a6243cad5045d | Stan | 3,910 | 137 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
d42329fec8d6a99b534fb4c63c840bb1b5bcc2cbc06789ef885d5247b56527ce | Stan | 4,176 | 145 | functions {
matrix vector_differencing(row_vector x) {
matrix[num_elements(x), num_elements(x)] D;
for (i in 1:num_elements(x)) {
D[i] = x - x[i];
}
return D;
}
row_vector x_step(row_vector x, row_vector z, real I1, real time_step) {
int nn = num_elements(x);
row_vector[nn] x_next;... |
14596f211d129d5ca2bac5d1d4a60be7c5156453404ed7c62166f9456bdf3029 | Stata | 443 | 21 | clear all
use "1-Incidence.dta"
****significant****
xtgee infant lagtotal_std i.id [fw=pop] , family(binomial 1) link(probit) exposure(pedpop) corr(independent) vce(robust)
margins , dydx(lagtotal_std)
***test extended probit***
gsem ///
(infant <- lagtotal_std i.id c.ln_pedpop, probit) ///
... |
d87a6d4fab3148908927e9aea1e62796058d03676edbff69e6f8e71eac5b41db | Stata | 447 | 23 | clear all
use "2-Mortality.dta"
****significant****
xtgee infant lagtotal_std i.id [fw=pop] , family(binomial 1) link(probit) exposure(pedpop) corr(independent) vce(robust)
margins , dydx(lagtotal_std)
***test extended probit***
gsem ///
(infant <- lagtotal_std i.id c.ln_pedpop, probit) ///
... |
23cf5d33ef6430ebc8fc9b71eb75a1af6bdd81b71f80dfa898774c2becd9431f | Text | 13 | 1 | # pyrockstats |
7a49fca977fc55cfd7ef051137bfd75483cbb1e4bf86f022902d97ee214b6a6e | Text | 17 | 1 | # MeCP2_analysis
|
1e01be1e4989582115b3a0b428e298fb42c3e967df69ab947fc99db8a3637ef5 | Text | 45 | 2 | # eNeuro-repo
Code used in eNeuro 2026 paper
|
89aff78d08f9a8c9e350db2d90235af884c3bb655a6c8b9b0254e4c58a9345e3 | Text | 58 | 2 | # accumulating-puffs-fastlearning
Code for Oostland et al
|
0107506058518594bbad1c6ae4bdac1ea0704a2be817d799fc5ab5049ac9680e | Text | 93 | 2 | # elife2026
custom code described in 2026 elife paper https://doi.org/10.7554/eLife.108593.1
|
1a0940934ed046e6bb5da5e382572d578f6f97ebee83d9d2bf45bb01769e79dc | Text | 105 | 2 | # MIDb-Specs
Code related to the specification of resources and interfaces necessary for MIDB operation.
|
a399cc4d8a2f1cb7fd8f52d27aded2b8b8f0c76c5557ce3993cb39a7163b658c | Text | 142 | 3 | # data_OligDev
This repository contains the data related to the oligodendrocyte development physiological map from Kuchovska, Bartmann et al. |
b092a7d4f920dc4a065a22af3355b1525798053119af1194526c7b788d8c98e7 | Text | 142 | 7 | This repository contains the code and data for the accumulating puffs experiment.
Ben Deverett
2015-2018
deverett [at] princeton [dot] edu
|
cb3e126787db92db65eee08bd1c2a4d25cdb07ab7855213ff6f9d3d3e99084b8 | Text | 142 | 2 | # RGCaEFS
RGCaEFS: A Dataset for Waveform-Specific Calcium Dynamics in Mouse’s Retinal Ganglion Cells Exposed to Electric Field Stimulation
|
38f8e8de22d2d9e890d3ce37395ec36a28454b18b25421abf8ed14fe1845492b | Text | 229 | 5 | # reverse_correlation_demo
Demo for the RC analysis in:
Fernández, A., Okun, S., & Carrasco, M. (2022). Differential effects of endogenous and exogenous attention on sensory tuning. Journal of Neuroscience, 42(7), 1316-1327.
|
95e0d08d13232692e5d1f9f679e0c79a968a51ff2b1ed75680dd6a9bc054aac2 | Text | 275 | 1 | Please note that the code provided is in its raw form; it has not been optimized, cleaned, or commented. While this may affect the ease of use or adaptation, we believe it remains a valuable resource for those interested in understanding or extending our analytical methods.
|
4a19fcc5273117363627e922be43e5bcdc91a079f3c3778389f1f262b9b51310 | Text | 297 | 5 | # NT_heterogeneity
# data and analysis scripts associated with Xiong et al., "Heterogeneity of Sonic Hedgehog response dynamics and fate specification in single neural progenitors" https://doi.org/10.1101/412858
# Version of record published at eLife: DOI: https://doi.org/10.7554/eLife.96980.3
|
b17e5fafb38fbb8b30897967d5432ed44a92c1eebc45a5a63c057bd3a3e785d5 | Text | 317 | 18 | # mo
## Usage
This project uses UV for virtual environment and dependency management.
First, run the command to download dependencies.
```bash
uv sync
```
Second, run the command to run this project.
```bash
uv run "ChebyKAN Open.py"
```
> [!NOTE]
> Please use powershell to run this project if os is windows.
|
c0bcd33d67f0270b85f6a33d0d12b194527a83129edbe4f6f7d7679b01f09cde | Text | 369 | 10 | # Targeting-insulo-frontal-pathway-to-reduce-stress-evoked-cognitive-rigidity
Shaorong Ma1, Kuan Hong Wang2,*, and Yi Zuo1*
1Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
2Department of Neuroscience, University of Rochester Medical Center, Roch... |
f661963f9ad1b568f2d4f56d3f623ee5c8a9894d0c5f458390534fbcb1c950c6 | Text | 396 | 5 | # CL_KG - a data-linked knowledge graph for the Cell Ontology
Documentation for the CL_KG including access guide, query guide and links to documentation of schema and use cases can be found at https://cellular-semantics.github.io/CL_KG/
A regularly updated **summary statistics report** is also available here: https:/... |
fbcb5189ba2f83e7ad66ad0f20b7123a63c8c1ff0d7ff93d2a4800dcdca8b468 | Text | 469 | 21 | Code for Marshall et al., _Intrinsic Units: Identifying a system’s causal grain_.
Installation:
```
cd path/to/Marshall-Intrinsic-Units
uv venv
uv sync --dev
```
Run all code from the project's root (the directory containing `pyproject.toml`):
```
uv run scripts/run_min_micro.py
...
```
The following options in `py... |
386c1f2aaa8bdffb4a1abdfc0cb2bbe0140cf182ed2491dce0b143cca4fcc156 | Text | 481 | 15 |
<p align="center">
<img width="680" height="150" src="https://github.com/BrainDynamicsUSYD/braintrak/blob/master/docs/img/braintrak_logo.png">
</p>
_Real-time brain states tracking and corticothalamic neural field model parameter estimation_
#### Getting started
The documentation in [BrainTrak's wiki](https://gi... |
e0b60c8926157f47656871114c900ea4fe267bdf6e61bfb8a3da72f75e46a998 | Text | 499 | 4 | # MClust-Spike-Sorting-Toolbox
MClust is a Matlab-based spike sorting toolbox for the separation of putative cells from multi-site neurophysiological recordings. It is particularly good for tetrodes.
This initial version is started from Version 4.4.07 released on 03 October 2017 from A. David Redish from the RedishLa... |
05e586c80f588403b65d8a1a9b195d9024020ba9a1c05f7f8ab03995353e6fb0 | Text | 501 | 8 | # Velocyto [](https://travis-ci.org/velocyto-team/velocyto.py)
*This repo is not maintained anymore. Instead consider using [STARSolo](https://github.com/alexdobin/STAR/tree/master) which mimics velocyto behavior, is up-to-date, and quic... |
801836cbb1d3385d77aafe64e138c530b3bdd0dbacadc12384a7e0f4d466783e | Text | 501 | 14 | # Percephone
Percephone is a tool developed to analyze recordings of neuronal activity (two-photon calcium imaging) obtained during a Go/No-Go perceptual decision-making task.
# Requirements:
- Python 3.6 or more
- the versions of the differents python dependencie... |
712ac487323def3ea5150dbf135f327e6db7e1bfb6282b3386087865b4bd95f7 | Text | 509 | 9 | # Sleep-Analysis
This is a set of code to analyze data for zebrafish tracking datasets.
There are two branches:
1) Format-Viewpoint Files, which is used to reformat quantized data from Viewpoint tracking experiments
2) Sleep_Analysis Code, which is used to pull out sleep/wake data and graphs.
The code requires the f... |
405a1d9887805dcb691ae27b083153d41a088b4a4bed9b10a29e9461ef5fb201 | Text | 549 | 4 | # Cell type-Agnostic Transcriptomic Signatures Enable Uniform Comparisons of Neurodevelopment
* This repository contains cell type agnostic models to predict the developmental age of brain cell types from single cell RNAseq data. <br>
* Code contains 4 jupyter notebooks, which apply pretrained models to predict neuro... |
2615d31edf1f695ed2f72ae2b786ded9734b9de76cf3780681aa1c886c523d4c | Text | 653 | 19 | # ctat-mutations
*******************
>Note, ctat-mutations is no longer being actively developed or maintained. Please explore available alternatives.
*******************
Click the [Wiki](https://github.com/NCIP/ctat-mutations/wiki) link at top for the ctat-mutation documentation.
Easiest to use leveraging Docker... |
f6afff160cc0923c0435cb4297c1b5156ac6469cc2ed558ba33bbce2f1646f91 | Text | 662 | 6 | # BT_missingdata
This repository includes custom scripts for data analysis for the paper: Genetic influences on missing data across experimental measures in infancy.
Analyses focus on the investigation of the etiological influences on missing data across different experiments in developmental cognitive neuroscience, u... |
6d0b6110bbe9d70083f656b0ebbf1ae38690a4e5ab1e14158ae81f1fb998e85e | Text | 678 | 10 | # pontibus
[](https://openfree.energy/)
[](https://github.com/OpenFreeEnergy/pontibus/actions/workflows/ci.yaml)
[![Documentation](https://readthedocs.org/projects/pont... |
cb2a3223c8dd3762e85ec17347eae452a4c480e26db1a2d4330e67e7f291775f | Text | 721 | 4 | # Correlogram-Uniformty-Peak-Count-Area-Left-of-Zero
This code quantifies firing dynamics from a recording of multiple neuronal signals by generating correlograms, then calculating correlogram uniformity, peak count, and area left of zero. The script also generates figures to show how these metrics, and thereby relati... |
14a0a4729742fa63de71031a2078b62606f17d4d3254206d4bc6afd8fd659828 | Text | 731 | 14 | # EarlyLate_RNA_eQTL
A code repository for custom scripts used in the analyses described in our manuscript "**Early and late RNA eQTL are driven by different genetic mechanisms**" (Sakaue and Raychaudhuri. to appear in Nat Commun.)
### Table of Contents
- 01_eQTL: cis-eQTL mapping
- 02_finemap_coloc: finemapping and... |
d7505ef1894bdcd45df303f8246ae4cd0b69e782647c657a355c55a09e89b571 | Text | 760 | 24 | # S1 Laminar Attention SE-BOLD Analysis
MATLAB scripts for traveling wave (TW) analysis and laminar qT1 profile analyses used in the study:
“Layer-Specific Attentional Modulation in Human Primary Somatosensory Cortex”.
## Requirements
MATLAB R2021a or later (tested on R2021a–R2023b)
## Contents
scripts/ – MATLAB scr... |
5b89348eb2ebb5600901d647f0e20f1d23c67dca289938373e0494058f593dcd | Text | 767 | 22 | # Exploring Chemoinformatics Aspects of Few-shot Meta-learning by Example of Infinite Dilution Activity Coefficient in Ionic Liquids Prediction
Corresponding author: Karol Baran (GdańskTech), karol.baran[at]pg.edu.pl
Manuscript status: submitted (2025)
Files and folders:
- data - directory with information on data ... |
23c761cc008e72031b0cf152aa7e83a49d288e388f4aa635121c33a06aaf8612 | Text | 782 | 30 | # Gut–Brain Axis in Alzheimer’s Disease
Code repository for metabolomics analysis and visualization in gut–brain axis research related to Alzheimer’s disease.
## Description
This repository contains R scripts for:
Correlation analysis (chord diagrams, heatmaps)
Group comparisons (boxplots, volcano plots)
PCA and ... |
353cde92b8cfc17360cf034d4f20d4be9d18c41916ce1cb9c5379b64243ebce9 | Text | 790 | 9 | Code files of the research paper entitled "An fMRI examination of the role of the Locus Coeruleus in state regulation in ADHD" by L. H. Drescher, J. M. Hall, J. O. Eayrs, R. M. Krebs, C. N. Boehler, & J. R. Wiersema
Code author: L. H. Drescher
File "TDT_full_setup.psyexp": Experimental paradigm of the Target Detectio... |
4d833e17a4deafc927db8122418e863c90697f50fb0d992f13d833a94f043790 | Text | 796 | 15 | # kimmdy-examples
A list of KIMMDY setups, runs, analysis scripts and figures to go along with the manuscript.
- [Introduction](./introduction)
- [Emulated reaction dynamics correctly predict radical reactions in small molecules](https://github.com/graeter-group/kimmdy-n-alkyl-radicals_... |
e7aae44b16ebc87fd0b2a640cda2b1056508cf44fff8c943c2fc80a82c0c3f2e | Text | 904 | 23 | This dataset contains GWAS summary statistics for three latent factors related to musculoskeletal disorders generated using genomic structural equation modeling.
The phenotypes are:
MSKdg: degenerative musculoskeletal disorder factor
MSKbm: bone mass factor
MSKai: autoimmune disorder factor
The summary sta... |
277252728085819d3847f93dbe1d88d22b3a10153080dc45623f0a241e844b1f | Text | 916 | 10 | Dataset needed to reproduce the results in the manuscript by "Generative Approaches to Kinetic Parameter Inference in Metabolic Networks via Latent Space Exploration" by S. Choudhury et al. (under review, a preprint available at https://www.biorxiv.org/content/10.1101/2025.03.31.646317v1)
The accompanying code is avai... |
da43431b628e9699bfba2b30c6076686bd2bf6c298cc2cb4b8f1bb0a6d2c3674 | Text | 924 | 11 | # TwinC
**Prediction and functional interpretation of inter-chromosomal genome architecture from DNA sequence with TwinC**
TwinC is a Python package for training, inference, and interpretation of trans-3D genome folding ... |
a5650a077ec5005f2f71ed5e1317b513ae47951f159da086e25e2000c77bac47 | Text | 937 | 21 | CG_Active_PO4.R was written in R to track lipid scrambling events during a coarse-grained trajectory.
To run this you must first extract the necessary Z value output file (listed below)
for PO4 bead z value position.
step7_PO4.out
Then place this file into a directory by itself.
When run, a file selection prompt wil... |
d5c0ecede8ffa63779dcb3cf7dcdf6de8b8511eebfa28dc00ff336f860fd8419 | Text | 956 | 16 | # Code repository for "‘Backpropagation and the brain’ realized in cortical error neuron microcircuits"
This repo contains experiments for error neuron microcircuits on .
The paper "‘Backpropagation and the brain’ realized in cortical error neuron microcircuits" by Kevin Max, Ismael Jaras, Arno Granier, Katharina A. W... |
157823bfb408089f283a6768d9f2cb9d8144b40ae1768908d1513c0a268aec26 | Text | 970 | 13 | # Sleep-Analysis
This is a set of code to analyze data for zebrafish tracking datasets.
There are two branches:
1) Format-Viewpoint Files, which is used to reformat quantized data from Viewpoint tracking experiments
2) Sleep_Analysis Code, which is used to pull out sleep/wake data and graphs.
The code requires the f... |
a789b567b04a7debc2461cc10046adb57e3b040e63c12c7357ba7f02ff499186 | Text | 984 | 14 | # ELongATE_CAG_sizing
This repository contains code for SPN CAG sizing from snRNA-seq expression values.
In this repository, you will find:
* **ELongATE_env.yml**: a yml file containing package versions for creating a conda environment
* **Models**: folder including *Phase_model.rds* and *CAG_sizing_model.rds* files,... |
cfaf9cde99641001f810237c1e5f1bd20dd27f58ce724aedcba66676d9cdb62a | Text | 991 | 21 | AA_Closed_P.R was written in R to track lipid scrambling events during an all-atom trajectory.
To run this you must first extract the necessary Z value output file (listed below)
for P atom z value position.
ZFC_P.out
When generated place this file into a directory by itself. (I ran this analysis locally on a... |
f8cbb4fc4de1d1cf83c45e95dc8d64238ae2dd4da30c9ac40f2b400b4e8ca35e | Text | 992 | 22 | CG_Closed_PO4.R was written in R to track lipid scrambling events during a coarse-grained trajectory.
To run this you must first extract the necessary Z value output file (listed below)
for PO4 bead z value position.
step7_PO4.out
When generated place this file into a directory by itself. (I ran this analysis locall... |
8961c305190ff6028b457665ffd6f43938e2faf3256331ef9fdcf4b727815588 | Text | 998 | 27 | # Binocular MRI Testing
Published at:
> Huang Y, Wang S, Qian Y, Kong L, Zhao P, Liu Y, Zarei SA, Zhang P, Andolina IM, & Liu H (2026) “Differential Effects of Balanced and Imbalanced Binocular Stimulation on Visual Cortex Responses in Amblyopic Children” Clinical Ophthalmology 20, 1-16 [doi.org/10.2147/opth.s590186]... |
24de74770ad384b534efc17531dc3b9301d4a2ec4c5ea40a0db8295900634cf4 | Text | 1,002 | 20 | # BAMSE Childhood Profiling
Code accompanying the manuscript:
“Longitudinal protein profiling of blood during childhood into early adulthood”
## Overview
This repository contains the code used to analyze longitudinal plasma proteomics data from the BAMSE cohort, with samples collected at ages 4, 8, 16, and 24 years.
... |
1c7fe60f41f65043d78fd85dd17627aa1d048dd0345b7cd29dfc76d3d33a9205 | Text | 1,027 | 24 | [](https://mybinder.org/v2/gh/IAGA-VMOD/IGRF13eval/main)
Python code and Gauss coefficients from the 13 generation of the IGRF candidate evaluation.
Originally submitted in October 2019.
Based on:
Alken, P., Thébault, E., Beggan, C.D. et al. Evaluation of candidate model... |
fc3abeb10237f6dfcc55992c01ef57cef4b2e9cf47c8dc8cfc9aed7a3e2cf473 | Text | 1,054 | 21 | AA_Active_P.R was written in R to track lipid scrambling events during an all-atom trajectory.
To run this you must first extract the necessary Z value output file (listed below)
for P atom z value positions.
ZFA_P.out
Then place this file into a directory by itself.
When run, a file selection prompt will ap... |
08998c09b49b8c61ea99ac83705a4b581d864cf3acf865dcf5e87db6d49fc67f | Text | 1,089 | 43 | <p align="center">
<img src="docs/assets/icon_MTB.png" alt="MTB Logo" width="200">
</p>
# Multi Task Battery (MTB)
A flexible Python toolbox for running multi-domain cognitive and motor tasks during fMRI sessions — all within a single scanning run. Built on [PsychoPy](https://www.psychopy.org/)
This project runs ... |
7dd5ddc2bd836fd8064ceab94cfad826b54c14540e2e7966495ee4392906eec8 | Text | 1,103 | 24 | Repository for 3 behavioral assays currently in use by the Linneweber lab as described in the paper
“Individuality across environmental context in Drosophila melanogaster (Mathejczyk et al., 2023)".
https://www.biorxiv.org/content/10.1101/2023.11.26.568741v1
<br>
<br>
This repository contains a part list for off-the-s... |
9a79c3f6c2b328062395b8e8ebcf11ecbb0af39b7a2dc0659431a21d86aae835 | Text | 1,109 | 26 |
.. image:: https://github.com/griffithslab/whobpyt/raw/main/doc/_static/whobpyt_logo_shire.png
:target: https://github.io/griffithslab/whobpyt/examples/index.html
:alt: whobpyt
:align: center
*WhoBPyT* is a PyTorch-based Python library for mathematical modelling of large-scale brain network dynamics, obtuse... |
d881de1af110b16b11c3fe3bab298a6037b03b207c91b6364198ec70cc1eae47 | Text | 1,167 | 18 | Example raw datasets for DH-PSF microangiography study
Title of associated study:
“Double-helix optical point spread function enables real-time mesoscopic 3D functional microangiography in the living mouse brain and skull”
Description:
This repository contains representative raw imaging datasets acquired using ... |
37d952f9450a83d9b17c90947d406f8f7db0bfa0d67e2df04790e372bfec8ff4 | Text | 1,220 | 16 | We compared 60 multi-echo (ME) and 30 single-echo (SE) rsfMRI preprocessing pipelines in 358 healthy adults. Pipelines included ICA-AROMA, FIX, ME-ICA, and ME-optimum combination, with or without additional nuisance regression (Friston 24P, CSF/WM, global mean signal regression [GMSR], or RAPIDTIDE). ME generally outpe... |
9a5e7c434593797e5acba0d5c7f83ebee216b1500202dcb2f4334a85089371aa | Text | 1,237 | 30 | # Ubergraph
Integrated OBO ontology store
- Merged set of mutually referential OBO ontologies:
- Uberon anatomy
- Cell Ontology (CL)
- Gene Ontology (GO)
- Biospatial Ontology (BSPO)
- Phenotype and Trait Ontology (PATO)
- Human Phenotype Ontology (HPO)
- Monarch Disease Ontology (MONDO)
- Chemical Ent... |
600fad4ea4b5c7884754f669b26f23f6a4003bf853622e3239b01b4f9faea57b | Text | 1,280 | 19 | # Molecular determinants of input-output connectivity in mouse caudoputamen
This repository contains a set of python scripts for performing analyses on anterograde, retrograde and single neuron data used in Wang et al.
### Installation and dependencies
All analysis and visualization code has been written in Python3.... |
939123028a7a7380fc8b90e28e34ca6083a900fe31b5f8beaf8c3df8037670e9 | Text | 1,292 | 41 | Polynomial Perceptron (PP) – Reproducibility Package
This repository contains the source code and experimental scripts used in the study.
--------------------------------------------------
DATASET SETUP
--------------------------------------------------
The datasets used in this study are publicly available and must... |
f100a8a155e388422b8a992f0f11b5f4e6ca1877738fe9dd49ae3a25c019c7e1 | Text | 1,404 | 12 | # TwinC-Manuscript
**Prediction and functional interpretation of inter-chromosomal genome architecture from DNA sequence with TwinC**
## Introduction
In this repository, we store scripts to reproduce the analyses p... |
f1e2d96fb09044f6fe5cbf07cad24ff7294b061eafbfb3eb3577526859e036b1 | Text | 1,424 | 46 | # Hardware for EthoPy
Welcome to the **Hardware for EthoPy** repository! This collection includes all hardware information required to build the setups described in EthoPy.
## What's Inside
This repo includes one folder for each behavioral system supported by EthoPy with:
- **Instructions** – step-by-step guides to ... |
1b81d23d7f3ce7944765dfc325d3107a2c74585605e8edae556e79f7372289dd | Text | 1,465 | 6 | **A Spatially Resolved Single-Cell Atlas of the Human Fetal Olfactory System**
*Yvon Mbouamboua, Kevin Lebrigand, Sreekala Nampoothiri, Marie Couralet, Marie-Jeanne Arguel, Ludovica Cotellessa, Cécile Allet, Vincent Prevot, Pascal Barbry and Paolo Giacobini*
**Abstract**
The human nasal region arises from neural cres... |
96b2d3f0d52e1fafb091296596d807dca099f186775b92e0e342f037beb46904 | Text | 1,467 | 37 | # Anipose
[](https://badge.fury.io/py/anipose)
Anipose is an open-source toolkit for robust, markerless 3D pose estimation of animal behavior from multiple camera views. It leverages the machine learning toolbox [DeepLabCut](https://github.com/AlexEMG/DeepLabCut) t... |
a1f41d012cd05b3d463d8f3379a2149b29ad68a87ee430bab4207bbb1d0246d5 | Text | 1,467 | 32 |
# psychofit
[](https://coveralls.io/github/cortex-lab/psychofit?branch=master)
[](https://github.com/cortex-lab/psychofit/actions/workflo... |
01112c6548eba417fd9e90da5761a2a2d628f21d8bf1eae2d62026c6592f92b9 | Text | 1,551 | 20 | # Alignment and Quality Control Plugin for Roddy
This plugins contains alignment and quality control related [Roddy](https://github.com/eilslabs/Roddy) workflows:
- PanCancer alignment workflow for whole genome (WGS) and exome (WES)
- Bisulfite core workflow (WGBS) using [methylCtools](https://github.com/hovestadt/me... |
e435b1bca03f0dac080f02ef2672979705daf431c1cd111f22b64f9adf673a6c | Text | 1,551 | 38 | Medical Image Registration ToolKit
==================================
The Medical Image Registration ToolKit (MIRTK) is a research-focused image processing toolkit,
developed at the [BioMedIA](https://biomedia.doc.ic.ac.uk/) research group. It provides a
collection of libraries and command-line tools to assist in proc... |
a471fcd849eba33ec720b7f520f4a77b03d68396e95592bfec80f0122499c5bf | Text | 1,591 | 33 | # NeuroSA-HO: Data and code for Higher-Order Neuromorphic Ising Machines
This repository contains the **data and code** used in several experiments from the paper:
**“Higher-Order Neuromorphic Ising Machines — Autoencoders and Fowler-Nordheim Annealers are all you need for Scalability.”**
## What’s included
- **CPU... |
553404e512e288bbe582998e0d66d7fa21da30ebed8716deda99cf888308cf24 | Text | 1,635 | 18 | # kpMoSeq_analysis
Analyze and plot kpMoSeq dataframes
This code was written for the analysis of data in Liff et al., 2026 (https://doi.org/10.7554/eLife.92882.2).
This code assumes that you have already run kpMoSeq (https://keypoint-moseq.readthedocs.io/en/latest/) and have generated the following files from your da... |
97f79b2d70d93a8bf2d5e4fe3596c4bf3fdc7038745f294ffe6e2494b1cd184f | Text | 1,680 | 28 | ### Fiber Photometry data analysis for dual color recordings with a TDT System
This Jupyter notebook [Fiber-Photometry-Analysis-PinkyCaMP](Fiber-Photometry-Analysis-PinkyCaMP.ipynb) is designed to analyze fiber photometry data recorded using a TDT system.
The notebook builds on methods adapted from Thomas Akam and La... |
ca77992a2c7c84c2b6a691a9cbb9b40607dc112897c2ba068eecb29468e2ac6a | Text | 1,739 | 98 | # Structure–Function Coupling/Decoupling (Graph-Spectral Framework)
This repository contains code used in:
**Xing Qian et al. (2026)**
Altered salience network structure–function integration underlies the decline in cognitive flexibility during aging
PLOS Biology
---
## Overview
This implementation is based on... |
2702eeac02e87ac8680dc85be73c5c72125c25084dfb7970e4596bd56f6111fd | Text | 1,766 | 49 | # Activity-dependent neuromodulation and calcium homeostasis cooperate to produce robust and modulable neuronal function
## About this repository
This repository contains all code and data involved in **Activity-dependent neuromodulation and calcium homeostasis cooperate to produce robust and modulable neuronal funct... |
5abf0b4d746a2ed59acc9b06ee6160d02208d7c98102a2c712769182c09cb3a2 | Text | 1,784 | 50 | # TEP_Physcis_CRNN
Physics-guided residual learning and calibrated CRNN pipeline for early warning industrial fault detection on the Tennessee Eastman Process (TEP) dataset.
This repository contains the notebook, generated experiment outputs, and result folders used to reproduce a staged workflow for data governance,... |
713def05e76e2320853538cde27e024cf9d756ee5da24eda1f46e614750773b1 | Text | 1,823 | 63 | # BCR repertoire analysis in anti-IgLON5 disease
Code and analysis scripts for the study:
**"Structural basis of IgLON5 autoantibody recognition in autoimmune encephalitis"**
---
## Repository contents
This repository contains the scripts used to perform the analyses and generate the figures presented in the public... |
05134fc2a1fb48cbba5a32bc8004207ea36cf31b4b97277ccb6d963b24a360f0 | Text | 1,825 | 17 | ## **Description**
We provide example codes for several methods described in our paper, including the construction of cross-species prediction models, interpretability analysis of CNNs, identification of hPICAs (human Predicted Increased Chromatin Accessibility regions), and CNN-based prediction of the functional effec... |
55c61e624fe1617d83bb68f1e89ab276f68599111d1c59907227830f298c1fad | Text | 1,833 | 31 | # mammal-lipids
This depository contains code to generate the main results and plots in the paper that analyzes coevolution between mammalian brain and milk.
The scripts include:
data_normalize.R - normalizes the raw intensity data matrixes of fatty acids (FAs) based on quantiles.
milk_FA.mds.R - performs ... |
157809f9495488aa41e52c15b1052df0afb4d15c6b0da2ccca57c869884f16d2 | Text | 1,841 | 52 | minc-stuffs is repository that houses scripts and bits of code that are useful for performing calculations on and otherwise extracting information from minc files. Contributions are welcome from the entire minc community.
This code is licensed under the 3-clause BSD License.
http://opensource.org/licenses/BSD-3-Clau... |
e653fca14f94e25d5734237206a1507994b19cb7d8ee5ebbd3a31d4317da5115 | Text | 1,851 | 32 | # Convergent and Selective Representations in the Insula
This repository contains analysis scripts for the study, Kwon et al. (2025) "Convergent and selective representations of pain, appetitive processes, aversive processes, and cognitive control in the insula"
## Overview
This study analyzes functional convergence... |
7e9bb5deff70df0c5c5cd2e5502f8846016947627f899dab4ea5313086965cfb | Text | 1,856 | 20 | # Huang2025_ModelVariabilityWithEmbeddings
This repository consists of scripts for reproducing results in the "Modelling variability in dynamic functional brain
networks using embeddings" manuscript.
## Requirements
- Scripts for preprocessing data depends on the [osl-ephys](https://github.com/OHBA-analysis/osl-ephys)... |
f8bd330bd8d8b8d93f66b3fac83c57e6336980d20a8123b6c9b9956735b6345d | Text | 1,885 | 18 | 
---
[](https://github.com/OpenFreeEnergy/alchemiscale/actions/workflows/ci-integration.yml)
[
# Mass spectrometry imaging and explainable machine learning uncover the brain's lipid landscapes
- 🔍 Explainability tools for visualizing annotated regions in MSI
- 🗺️ Tools for mapping m/z values associated with region categories using ML
# Usage examples... |
d8c459f9760307a066e49fa0d357905e91118cee6eec0ea1b56cbd4eb8cdfc58 | Text | 1,896 | 13 | # Overview
The zipped folders are organized as follows:
- `data` contains every external file that might be used during compilation;
- `deprecated-code` contains scripts that are no longer needed/relevant but were still used in the development of the project;
- `figures` contains scripts that were used to produce the ... |
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