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|---|---|---|---|---|
3c95aedbb3481ef29ef3b794daa9b136abca51d401bd85b1392cfd6683ceaf86 | Text | 3,921 | 75 | # A detailed kinetic model of Eastern equine encephalitis virus replication in a susceptible host cell
## Requirements
1. Anaconda
2. If you are using Windows, you will need to install WSL ([Instructions](https://learn.microsoft.com/en-us/windows/wsl/install))
3. Figure visualization notebooks _individually_ require ... |
dfaae239a91e8c7232ff9e5d5abb3071cf3966895d89affd633efcf4fcb919f8 | Text | 3,923 | 70 | # Object detection models for acid-fast bacilli screening
[Paper](https://journals.asm.org/doi/10.1128/spectrum.00602-25)
## Models & Datasets
Our trained models, as used to generate the results in our paper, [are available on Huggingface](https://huggingface.co/arup-ri/afb), as are the [datasets they were trained an... |
eed6d307cb912d60ea922788a8c3c5073e4187e84e1b0996497320715a17f487 | Text | 3,931 | 83 | # AI-Powered Mobile App for Nuclear Cataract Detection
This Android mobile application is part of the research described in the accompanying scientific article.
Author: Alicja Anna Ignatowicz
Supervision: Tomasz Marciniak
It implements a deep learning–based classifier to support the assessment of cataracts using o... |
b39bcd9ebc4c53cdc91b392c6068c2b529f30c5eee5766fd11acdf08b10d904f | Text | 3,950 | 86 | # dOccLS — Molecular and haemodynamic effects of LSD in the human brain
Code and data accompanying the dOccLS manuscript. This repository contains everything
needed to reproduce the receptor occupancy and fMRI Global Correlation (GCOR) analyses.
## Repository structure
```
code/
├── run_gcor_pipeline.m Main M... |
4ba9291b3730135d53a2433577aa4a674df938e52ad782cd799a4f53e0d47401 | Text | 3,956 | 46 | # Microsaccade bias shift vs. maintain experiment
Experimental code for an orientation change detection task, designed to measure microsaccade bias during covert attention, programmed in Python.
> ### Paper
> This code relates to the published paper: [Microsaccades track shifting but not necessarily maintaining covert... |
bf9ae3e8bc51604a8176b8044995759eaa86ced345227d4cf53832354c215ee4 | Text | 3,972 | 42 | # A Flexible Low-Complexity DNN Solution for Power Control in Cell-Free Massive MIMO
This repository contains the dataset and code to reproduce results of the following papers:
G. García-Barrios, M. Fuentes, and D. Martín-Sacristán, “A Study on the Robustness of a DNN Under Scenario Shifts for Power Control in Cell-F... |
2fca1ef13c98016c939792953da11c0f6bb2df540967585518a643f136990256 | Text | 3,992 | 40 | The repository contains some python scripts for training and inferring test document vectors using paragraph vectors or doc2vec.
Requirements
============
* Python2: Pre-trained models and scripts all support Python2 only.
* Gensim: Best to use my [forked version](https://github.com/jhlau/gensim) of gensim; the latest... |
91c2824be92644162de7f952c014902812759173fd3a99d298e0c8aa4bf34b29 | Text | 4,006 | 69 | # Deep-learning models of the ascending proprioceptive pathway are subject to illusions
## Authors
Adriana Perez Rotondo\*, Merkourios Simos\*, Florian David, Sebastian Pigeon, Olaf Blanke, & Alexander Mathis
\*These authors contributed equally to this work.
EPFL - École Polytechnique Fédérale de Lausanne, Switzerl... |
6bf338d4d72abed621b54a420c5a5d7c71cfb07023ad1414c671606d32227097 | Text | 4,015 | 75 | # ijp-jacop-b
[](https://github.com/BIOP/ijp-jacop-b/actions/workflows/build.yml)
[](https://maven.scijava.org/#browse/... |
2f36a5c7d3435f81c111741cdf3f71110ff5da64976f7ba1b511402234bae742 | Text | 4,024 | 75 | # Symmetries and Synchronization from Whole-Neural Activity in *C. elegans* Connectome
This repository accompanies the paper **"Symmetries and synchronization from whole-neural activity in *C. elegans* connectome: Integration of functional and structural networks."** It contains the Python code and analysis scripts us... |
c2736859d7bd74459feb44f9a0c64e0bfc8253d1fc9e3d54b73b00b7e4175092 | Text | 4,035 | 71 | slugFind, or MPC approach as it is referred to in its accompanying manuscript, infers neuronal spiking as a function of calcium imaging data.
Corresponding Author: Nicholas A. Rondoni
nrondoni@ucsc.edu
Please reach out if you have any questions about this software implementation!
This direct... |
94add18a29df4729af487c69939a67dde95738ea2e1c443b3784cbe0f9fba412 | Text | 4,036 | 92 | # SpinDoctor Toolbox
SpinDoctor is a software package that performs numerical simulations of diffusion magnetic resonance imaging (dMRI) for prototyping purposes.
## Software requirements
The SpinDoctor Toolbox has been developed in the MATLAB R2020b and tested with MATLAB R2018a-R2021a.
SpinDoctor requires no add... |
1da63e137849eda76097d7526269cf42779dd8214c6c298da142366765542536 | Text | 4,048 | 75 | [](https://zenodo.org/badge/latestdoi/296102080)
# spynal: the Simple Python Neural Analysis Library
Tools for preprocessing and basic analysis of systems/cognitive neurophysiology data in Python
Covers typical preprocessing and basic analysis steps in neural analysis w... |
ab26d589f40b64233818942e35cc36997abdc81c90c23f7d3413d7f22cf53991 | Text | 4,049 | 56 | # A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
This is the official repository for the paper "[A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?](https://arxiv.org/abs/2302.11640)" (ICLR 2023).
### Datasets
In the paper we intro... |
6abb53045a40dce7285ec439181c3651b5df5951e357af490de41ee9ddd89b6b | Text | 4,064 | 89 | # SFGPI BIDS
## Overview
This repository contains BIDS-converted MRI data for:
Hall-McMaster, Tomov, Gershman* & Schuck* (2025). Neural evidence that humans reuse strategies to solve new tasks. *PLOS Biology*.
## Usage
### Get data
```bash
$ datalad clone git@gin.g-node.org:/sam.hall-mcmaster/sfgpi-bids.git
[INFO ... |
76031d8a13e87d4b01d09d6f8d24ddabef081fe8b807b40c6fbdb5e7deafd691 | Text | 4,076 | 58 | ### ct2print voxels to mesh
A basic example of converting a voxel-based image to a simplified mesh. This interactive drag-and-drop web page allows you to create meshes that can be used with a 3D printer.
**No data is sent to a server. Everything happens in *your* browser window, on *your* machine.**
](https://pypi.org/project/water-benchmark-hub/)
[](https://opensource.org/licenses/MIT)
. Informative neural representations of unseen objects during higher-order processing in human brains and deep artificial networks, Nature Human Behavior. https://doi.org/10.1038/s41562-021-01274-7](https://www.nature.com/articles/s41562-021-01274-7.epdf?sharing_token=J-u6zur5pR... |
51e2fc073b1eb69c0328cfa392b76756cbfd19e83e1e54c6fb1e6f22c20806a5 | Text | 4,147 | 101 | <h1 align="center">CeyeHao: AI-driven microfluidic flow programming using hierarchically assembled obstacles in microchannel and receptive-field-augmented neural network</h1>
<h4 align="center"><a href="https://doi.org/10.5281/zenodo.13363708"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.13363708.svg" alt="DOI... |
24a3844bf0800ece3dd04607367fac56db0db413866ad8e9932bfd663aff0930 | Text | 4,168 | 73 | # SSEC-JHU SnapMine
[](https://github.com/ssec-jhu/snaptron-query/actions/workflows/ci.yml)
[](https://codecov.io/gh/ssec-jhu/snaptron-query)
[
## Overview
SeNMo is a deep learning model designed to enhance the analysis of multi-omics data in oncology. This repository contains the code and instructions for training, fine-tuning,... |
0a1845d0bfb4e1299a94fc533f368c1b5ad04e9d8e6708550a90417235f5c303 | Text | 4,227 | 96 | # REGNN
REGNN (Relation Equivariant Graph Neural Networks) is a graph deep learning framework for spatially resolved transcriptomics data analyses on heterogeneous tissue structures.
### Software Requirements
#### OS Requirements
``` REGNN ``` was tested on on Windows 11 12th Gen Intel(R)... |
fceb4aa04d2071666743be91b6de4bc4b0b86581a00d9feea91290af796abb42 | Text | 4,230 | 130 | # Nonlinear Multi-Head Cross-Attention Network and Programmable Gradient Information for Gaze Estimation
The Pytorch Implementation of “Nonlinear Multi-Head Cross-Attention Network and Programmable Gradient Information for Gaze Estimation”.
## Requirements
We build the project with python=3.8.
```python
conda create... |
4f463c3c889ce5d08a3981f2a253e830dedafa400656813ee4f4f9353b980783 | Text | 4,231 | 46 | We prepared the following data files associated with the paper “Spatially resolved epigenomic profiling of single cells in complex tissues” published in Cell (DOI：10.1016/j.cell.2022.09.035):
1. H3K27ac_RPE1_rep1.xlsx, H3K27ac_RPE1_rep2.xlsx， and H3K27ac_RPE1_rep3.xlsx- containing the 3D positions of the decoded H3... |
a59085d016c88b32b6b1dffff49fe1cda708f1fc1826287bcf21c04a55745f10 | Text | 4,231 | 56 | # Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation
By Bhavana Jonnalagadda
## Quickstart
### Run evaluation notebooks
If you'd just like to be able to run the code that does model analysis, comparison, or plot generation, the data is available and saved as var... |
229cd02b414597a5ac9b4a273d922fccf3d0c86cedc2c7065838bcaf1fd5eb78 | Text | 4,240 | 121 | # RxnRep
Self-supervised contrastive pretraining for chemical reaction representation ([RxnRep](https://doi.org/10.1039/d1sc06515g)).
<p align="center">
<img src="rxnrep.png" alt="rxnrep" width="600">
</p>
## Installation
```bash
git clone https://github.com/mjwen/rxnrep.git
cd rxnrep
conda env create -f environmen... |
fb9a15364b536898b359d52a2c9d324fa684ac74ef885eb9f3348335ce0329e5 | Text | 4,244 | 115 | # ACES-GNN
This repository contains the code for the paper "ACES-GNN: Can Graph Neural Network Learn to Explain Activity Cliffs".
## Dependencies
The code was developed and tested on Python 3.10.10 using CUDA 11.4 with the following Python packages installed:
```
pytorch 1.12.1
torch-geometric 2.3.0
scik... |
6a4f36f6ffab3c7e4af0afd831de33529d5641bf0164914c4e6855925a32c9f6 | Text | 4,272 | 105 | 1. GA optimization
Main_GA_neuromechanical_dorsoventral_switch.m
% This file is for GA optimization
% Optimizaiton process could be saved to ./graph/opt_process.fig manually
2. Evalutation of optimized results
opt_func_eva_quasiStatic.m
plot_muscle_deformation.m
plot_membrane_potential.m
animation_script.m
... |
bccd83214103e1ecd3ebd397e5fe50e0f687d0876bcdbd4a59df39b2c7c7d1d0 | Text | 4,276 | 86 | <img src="./doc/yfinance-gh-logo-dark.webp#gh-dark-mode-only" height="100">
<img src="./doc/yfinance-gh-logo-light.webp#gh-light-mode-only" height="100">
# Download market data from Yahoo! Finance's API
<a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/badge/python... |
b450fa2434d68d397cc7dbccf500730720a1a790c49ef55116ac4b7d377fcd92 | Text | 4,282 | 70 | 
# BrainFusion
**BrainFusion** is an open-source, Python-based platform developed by the Medical Information and Neuroimaging Laboratory (MINILab) at the School of Biomedical Science and Engineering, South China University of Technology (SCUT), which designed to streamline the ex... |
e7525bc5d5d81844b1058387162bd67961705f37fae471ad6143220bb7d3978d | Text | 4,283 | 156 | # Neur-Ally
**Neur-Ally** is a deep learning model for predicting the regulatory effect of neurologic single nucleotide variations
## Dependencies
* Python version = 3.8.16
* OS = Ubuntu 20.04.4
### Python Libraries
... |
5c8d74760d92376413c68f4140c3380b367c5084ab2153bbabe1d657b6484f80 | Text | 4,293 | 53 | --------------------------------------------------------------------------------------------------------------------------
Thalamic parcellation using K-means for Nuclei in Infant Thalamus (KNIT)
--------------------------------------------------------------------------------------------------------------------------
... |
bb6557d58e78a917daf1240f6108fbcbc490225b766d26bc410d04ce74dbec52 | Text | 4,293 | 63 | # NarrativePuzzle
## Description
This repository contains the code for the paper **"Hippocampal Systems for Event Encoding and Sequencing during Ongoing Narrative Comprehension"** by Park et al. (2025).
The paper investigates how the hippocampus contributes to encoding individual events and sequencing them into a coher... |
3115e6b3649f2025d1bcc7e8fec47759f714a93afa5b375e6d87fd4f8b1f1a09 | Text | 4,368 | 125 | # gnn-explainer
This repository contains the source code for the paper `GNNExplainer: Generating Explanations for Graph Neural Networks` by [Rex Ying](https://cs.stanford.edu/people/rexy/), [Dylan Bourgeois](https://dtsbourg.me/), [Jiaxuan You](https://cs.stanford.edu/~jiaxuan/), [Marinka Zitnik](http://helikoid.si/cm... |
bdeff0a8a16f5bf8467777c5172758214603979a321a33097cba4233feab0149 | Text | 4,375 | 162 | # CryptoGat201_2023_suppdata
This repository is supplementary data accompanying the bioRxiv preprint:
> A trade-off between proliferation and defense in the fungal pathogen Cryptococcus at alkaline pH is controlled by the transcription factor GAT201.
> Elizabeth S. Hughes, Laura R. Tuck, Zhenzhen He, Elizabeth R. Bal... |
aa0928fe079de0ad37bd0ea7b8a48592f9a3b4761b6587acfb0fd7fd8eaa67dc | Text | 4,384 | 35 | # simpletracker - A simple particle tracking algorithm for MATLAB that can deal with gaps.
*Tracking* , or particle linking, consist in re-building the trajectories of one or several particles as they move along time. Their position is reported at each frame, but their identity is yet unknown: we do not know what par... |
180493436cb640d170b79d083c5ca7a057f39b15976f656a6e2c907b9c9f5208 | Text | 4,393 | 96 | CONTENTS AND COPYRIGHT
This directory contains the entire source tree for the
UCSC Genome Browser Group's suite of biological analysis
and web display programs as well as some of Jim Kent's own tools.
All files are copyrighted, but license is hereby granted for personal,
academic, and non-profit use. Please see the LI... |
e8fb1c0edb6bfc30dfef81e60c8e456e4546d98a73bd21ec1331008a7d74cc30 | Text | 4,396 | 70 | # Cochlear-Nucleus-AM-coding - PLOS Biology version
The data and code for envelope coding in the cochlear nucleus. This requires MATLAB. It also contains some C (Mex) code which has been compiled for 64-bit Windows (so some work required to run elsewhere).
This is ALL the data and code to go from spike times to publi... |
eb4854f1c89438de392695107e1ab3812249ed4fe5067fb97b789449d9896f77 | Text | 4,425 | 126 | # ACML (Asymmetric Contrastive Multimodal Learning for Advancing Chemical Understanding)
## Requirements and Installation
### 1. Create virtual environment
```
conda create -n acml python=3.9
conda activate acml
```
### 2. Install pytorch with CUDA 11.7
```
pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 ... |
455ed104ec6275ff9884c3c124370aefe1e20ffa289f847efe78f88d32ca5660 | Text | 4,468 | 82 | # BrainDataAlchemy
Code to mine for the summer Brain Data Alchemy meta-analysis projects.
## Pipeline from Summer 2026:
This code is all within the MetaAnalysis_GEOData_2026 folder:
https://github.com/hagenaue/BrainDataAlchemy/tree/main/MetaAnalysis_GEOData_2026
Currently, this code is preliminary, as we are updatin... |
53af1f067d4801f03969251501be587bcf8a3fd1afec9cb66e74492499e78e76 | Text | 4,469 | 68 | # TRFE-Plus: Thyroid Region Prior Guided Attention for Ultrasound Segmentation of Thyroid Nodules [journal](https://www.sciencedirect.com/science/article/pii/S0010482522010976)
Previous TRFE-Net in ISBI-2021: Multi-Task Learning for Thyroid Nodule Segmentation with Thyroid Region Prior [conference](https://www.research... |
23823a6c1fe79bcadd6bc17461d4b890b23b9bd70ffb0193ef598d6b8f94cfb8 | Text | 4,504 | 115 | # ACES-GNN
This repository contains the code for the paper "ACES-GNN: Can Graph Neural Network Learn to Explain Activity Cliffs".
## Dependencies
The code was developed and tested on Python 3.10.10 using CUDA 11.4 with the following Python packages installed:
```
pytorch 1.12.1
torch-geometric 2.3.0
scik... |
77946c5fec6da92f3bc364bfe3a6a851af8c33e3efecab3474b78ad64719006a | Text | 4,515 | 96 | # Neurodocker
[](https://github.com/ReproNim/neurodocker/actions/workflows/pull-request.yml)
[](https://hub.docker.com/r/repronim/neurodocker... |
9910c247d68ca1d21079c272997a7dec552a48056bea96c9e2ec9a69d09340d1 | Text | 4,516 | 67 | # Individual differences of neurophysiological brain activity are heritable
## Introduction
Brain-fingerprint is a novel technique used to explore the inter-individual differrences in the brain activity. Previous research demonstrates that we are capable of accurately differentiating individuals in a cohort bas... |
cc2f519d31bc938bf55477e314899452c69cb7d4a8e84ad3d7e4d97872a9dcd5 | Text | 4,530 | 158 | # Neur-Ally
**Neur-Ally** is a deep learning model for predicting the regulatory effect of neurologic single nucleotide variations
Please cite the article "**Neur-Ally: a deep learning model for regulatory variant prediction based on genomic and epigenomic features in brain and its validation in certain neurological d... |
efea7cd2c661ce641b6511fc4d136946e31e1e25e468acdebe252957973d69c6 | Text | 4,548 | 112 | # Data Description Report
## Effects of a Single tDCS with Mirror Therapy Stimulation on Hand Function in Healthy Individuals
**Associated publication:**
Wójcik M, Vlček P, Siatkowski I, Grünerová-Lippertová M (2025). *Effects of a single tDCS with mirror therapy stimulation on hand function in healthy individuals*... |
eb3cf193829c7ca7f657c1c2e2e8dd5a8b6017a63f870052755495954e4f2070 | Text | 4,554 | 81 | # Distribution Matching for Brain Connectivity Harmonization
## Overview
This repository contains the implementation of a distribution-matching approach to harmonizing structural brain connectivity across different sites and scanners. The method aims to align the statistical properties of connectivity data from differ... |
cc4da1de9a81cde688318f41b2f1a2638473305037b73be6974098b81263743d | Text | 4,571 | 79 | <img src="imgs/dmsfold_logo.png" width="200" height="200"/>
# DMS-Fold
[](https://huggingface.co/LindertLab/DMS-Fold/tree/main) [](https://huggingface.co/datasets/Lindert... |
455fdbe1b5afb0365a1def00ca51c74a233b478e3c9336f8247cccd4af2e8341 | Text | 4,591 | 128 | # Forecasting Models for Irrigation Analysis 🌱
This repository contains machine learning models for forecasting irrigation-related time series data. The project implements and compares various deep learning architectures for time series forecasting, utilizing state-of-the-art methods to enhance accuracy and performan... |
0c7adac66019653e7d11d91e7a6bfa543c3f9795293a035753b5f23a839ba131 | Text | 4,612 | 87 | # SeaMoon: Prediction of Molecular Motions Based on Language Models
SeaMoon is a deep learning framework that predicts protein motions from their amino acid sequences. It leverages embeddings of protein language models, such as the sequence-only-based [ESM-2](https://github.com/facebookresearch/esm) ([Lin et al. 2022]... |
860be1ec4d3d9caf935746b2a8d040be642af1f094192cfc49c1ffa686014a64 | Text | 4,633 | 90 | # SEPARATE
### Spatial Expression PAttern-guided paiRing And unmixing of proTEins
## Installation
#### Clone the repository
```
git clone https://github.com/NICALab/SEPARATE.git
```
#### Navigate into the SEPARATE folder
```
cd ./SEPARATE
```
#### Creat conda environment
```
conda env create -f environment.yaml
```... |
a687038255bf4b6acb1aae3b25a38607e525594ff7b2ccb8f1d73d0e33299f17 | Text | 4,670 | 109 | Sentence Supramodal Areas Atlas (SENSAAS)
================
## Reference
**Labache, L.**, Joliot, M., Saracco, J., Jobard, G., Hesling, I., Zago,
L., … & Tzourio-Mazoyer, N. (2019). A SENtence Supramodal Areas AtlaS
(SENSAAS) based on multiple task-induced activation mapping and graph
analysis of intrinsic connectivit... |
09d5e4950e5a201ee93ec5f87e1d9d981aaafe2ca4559f7eb1124bfabca4a92c | Text | 4,702 | 87 | # SeaMoon: Prediction of Molecular Motions Based on Language Models [](https://doi.org/10.5281/zenodo.15616636)
SeaMoon is a deep learning framework that predicts protein motions from their amino acid sequences. It leverages embeddings of protein language models, such as t... |
95c8ece7233559475a5797453227b88d0698673fdb65c94bcf867b2af89fe617 | Text | 4,722 | 53 | # Click-ExM data process and example
Matlab code and example files for manuscript *Click-ExM enables expansion microscopy for all biomolecules, by De-en Sun, et al*.
Uploaded and last edited by Yujie Shi (yujieshi@scripps.edu) Oct-06-2020.
## Introduction
The script `Process_click_EXM.m` in this repo is created for e... |
10cf5870a9238ec6436c45510a801c5b8e8db52b7c7f9eba5fc71abf34e4a656 | Text | 4,776 | 124 | # README #
## SerialFIB ##
A Modular Platform for Streamlining Automated Cryo-FIB Workflows
SerialFIB is developed at the Max Planck Institute of Biochemistry, Research Group CryoEM Technology and the Mahamid group, European Molecular Biology Laboratory (... |
305c4d5ebaced3f1ae796d8df5001e491d327742d0887126c3e40ddac28c80b4 | Text | 4,798 | 96 | # SBDD-benchmarking
Testing of traditional and 3D deep learning SBDD methods through the development of a benchmark
## Overview
Four SBDD methods are evaluated using this benchmark: DiffSBDD, Pocket2Mol, LigBuilderv3, and AutoGrow4. The model-based methods DiffSBDD and Pocket2Mol are first re-trained on a set of the B... |
4f5f0a542098edeff0a589706c53dbaad6cd614c73ba693ee7fa6a7a28ba26b7 | Text | 4,799 | 143 | # morphometrics
[](https://github.com/morphometrics/morphometrics/raw/main/LICENSE)
[](https://pypi.org/project/morphometrics)
[ dataset release, 2024
<hr>
<h1>About the TCP data release </h1>
**Title**: The Transdiagnostic Connectome Project: a richly phenotyped open dataset for advancing the study of brain-behavior relationships in... |
6ddda876b3b37754ab03296a2f19228e9b67e68b9fc230f844f66e0725e40e09 | Text | 4,804 | 65 | # brain2print
This is an extension of [brainchop](https://github.com/neuroneural/brainchop) that converts voxel-based MRI scans to 3D meshes that can be printed. **No data is sent to a server. *Everything* happens in your browser window, on *your* machine**.
## Usage
1. Open t... |
80256744fc66e7c8bdde400ac70572c32d5a438e5ac4481534c1ac7c480cba8f | Text | 4,805 | 98 | # X-RAI: Scalable 3D Reconstruction From Single Particle X-Ray Diffraction Images Based on Online Machine Learning
This repository is the official implementation of [X-RAI: Scalable 3D Reconstruction From Single Particle X-Ray Diffraction Images Based on Online Machine Learning](https://arxiv.org/abs/2312.14432)
.
## Folder descriptions:
1. `/Utilities`: This fo... |
f68a8286753e354b24c92e0f343b2d006c0597125a2f0113ae9696589826a8cd | Text | 4,943 | 95 | [](https://doi.org/10.5281/zenodo.14278557)
# minis-quantal-analysis
This repository contains quantal analysis Matlab code for [minis](https://github.com/dervinism/minis) software. It contains all the analysis code required to reproduce main Figures 1, 2,... |
fbc63d39fbd3ba9c89974cfcfa48451eef4b270edebbee8d46a58f6b265ae2b2 | Text | 4,943 | 95 | [](https://doi.org/10.5281/zenodo.14288653)
# minis-quantal-analysis
This repository contains quantal analysis Matlab code for [minis](https://github.com/dervinism/minis) software. It contains all the analysis code required to reproduce main Figures 1, 2,... |
fff2afa883aa5be32ab21e6216c3db649dbda0f7bfd959f37c84186145827b18 | Text | 4,972 | 144 | # PyMRItools
Toolbox for MRI sequence programming, reconstruction, simulation, processing, and analysis using Python.
## Installation
### Pip
You can install the `PyMRItools` package directly from GitHub using Python 3.10 and `pip`.
We advise
[working in a virtual environment](https://packaging.python.org/en/latest... |
376b16ff27b3c7878396297442842135d4bea52e698cc2823aa0833b74df6259 | Text | 4,983 | 93 | # HCP PIPELINES
This repository contains pipelines used to analyse HCP fMRI data with subject-level analytic pipelines using FSL and SPM and different parameters. It also contains scripts to perform group-level analysis with one sample t-test (within group).
## Table of contents
* [How to cite?](#how-to-cite)
... |
7ac6a964a73c3b6d694ad91c13343454a2c0f7c4599b1eda4a54ea259a6fae09 | Text | 5,003 | 124 |
<!-- README.md is generated from README.Rmd. Please edit that file -->
# PAVER: Pathway Analysis Visualization with Embedding Representations
<!-- badges: start -->
[](https://github.com/willgryan/PAVER/actions/workflows/r... |
e7555bb5c55f290ec5da031012a2366dfd75a5f07aff17c071e8e180a3c65201 | Text | 5,007 | 78 | [](https://doi.org/10.5281/zenodo.15376110)
# Code for "Personalised Regional Modelling Predicts Tau Progression in the Human Brain", Chaggar et al 2024
This repository contains the code used in the paper Chaggar et al., 2024
for the analysis of ADNI data.
## Code inst... |
61e29f76fbc621cbed003ed9704a22693e1448b755d0a03eca3ec563dd02e954 | Text | 5,063 | 98 | # GenoTools
## Published in G3: [https://www.biorxiv.org/content/10.1101/2024.03.26.586362v1.full.pdf](https://doi.org/10.1093/g3journal/jkae268)
[](https://zenodo.org/doi/10.5281/zenodo.10443257)
[](https://ba... |
26df52df3fbe4fae627a02f71ca98c2390d934790efc9128f5064631edb3e359 | Text | 5,084 | 169 | [](https://github.com/acquire-project/acquire-python/actions/workflows/build.yml)
[](https://github.com/acquire-project/acqui... |
29adc1254f0aa6b40cc37b0822883e45a0d1600505a3dadccf8865b8056a500a | Text | 5,094 | 65 | # HERGAI
You will find herein the files related to our *Journal of Cheminformatics* paper:
**Tran-Nguyen, VK., Randriharimanamizara, U.F. & Taboureau, O. HERGAI: an artificial intelligence tool for structure-based prediction of hERG inhibitors. J Cheminform 17, 110 (2025)**
Full-text link: https://doi.org/10.1186/s1... |
b57e3dec550cdcf4b1ecebc456b58227e4755841f757c1eb6f133e72a49a1f94 | Text | 5,098 | 67 | ========================================
BIDScoin: Coin your imaging data to BIDS
========================================
.. image:: ../bidscoin/bidscoin_logo.png
:height: 260px
:align: right
:alt: Full documentation: https://bidscoin.readthedocs.io
:target: https://bidscoin.readthedocs.io
.. raw:: html
... |
2b37bbb7a7a632a0eed51e5e9e1b0d6049a76bc5bcd79814cd549f93effa39c5 | Text | 5,102 | 37 | # Code supplement to the CNV covariance study
[](https://lbesson.mit-license.org/)
[]([https://doi.org/10.1101/2024.05.21.24307729](https://doi.org/10.1101/2024.05.21.24307729))
Thi... |
cf82f35ec97aad5cb47c90dbd76acd787e02f6d43526544707c9172bfd963659 | Text | 5,113 | 59 | # myMixedModelsTrajectories: Trajectory fitting using mixed models regression
Mixed effect model toolbox for the analysis of longitudinal data
This toolbox allows to fit models of different orders (from constant to cubic models) to data with repeated measurements. The purpose is to estimate developmental curves over a... |
8c7671c2acf6ca1da282d0ea6f2f5f0a7b47f0397db36909900db55650b61341 | Text | 5,144 | 117 | # Parkinson's Disease Cohort Study: Clinical and TMS Data Analysis
This repository contains a database with clinical and transcranial magnetic stimulation (TMS) measurements, along with the R code used for statistical analysis of a cohort of patients with Parkinson's disease (PD). The data and analyses are associated ... |
c2d415b5ecd127a75433b83856484392505ebe172a8488ea56cd3ea4fc408e95 | Text | 5,170 | 120 | # CFZ-Net-training
Deep Learning for Capillary Free Zones (CFZ) Segmentation using OCTA Images. The implementation uses Python and PyTorch.
## Overview
This GitHub repository hosts the implementation of CFZ-Net, a deep learning model developed in PyTorch for segmenting capillary free zones (CFZ), arteries, and veins ... |
9cda9a5c35928daa5e124d54fb40b4cfe7dfd84ce3ecb0d689b642968effb25b | Text | 5,188 | 92 | # ImageQualityMetricsMRI
**Assessing the Influence of Preprocessing on the Agreement of Image Quality Metrics with Radiological Evaluation in the Presence of Motion**
Published in MAGMA:
Marchetto, E., Eichhorn, H., Gallichan, D. et al. Agreement of image quality metrics with radiological evaluation in the presence of... |
5165dc2f7d5a5a1b35f7c82e25ad071fa03bd5d1f637d7113b6d61dda396e921 | Text | 5,198 | 54 | README for STR Profiles and Incest Detection Study
Summary
The study focuses on developing a predictive model based on STR (Short Tandem Repeat) profiles of mother and child to detect incestuous relationships. By using allelic frequencies from the USA and Saudi Arabia, STR profiles were generated, resulting in datase... |
b99b6c4f0d30e3ec645a3e5855a93db89f97cc594634ec19d364108bc3cefce7 | Text | 5,204 | 97 | # Welcome to QSM
For deep learning-based QSM methods, check out the other github repo: [deepMRI](https://github.com/sunhongfu/deepMRI)
The repository is for reconstructing Quantitative Susceptibility Mapping (QSM) images from MRI. The codes cover image recons for single-echo SWI or multiple-echo GRE sequence as well a... |
b0e1417f5da2c6c76761deefc787fa4c6b41bea59649dc13175ee814fd59a2ba | Text | 5,215 | 127 | # **UTOM**: Unsupervised content-preserving transformation for optical microscopy.
## Contents
<img src="images/logo4.jpg" width="600" align="right">
- [Overview](#overview)
- [Repo Structure](#repo-structure)
- [System Environment](#system-environment)
- [Demo](#demo)
- [Results](#results)
- [Issues](https://github... |
d83cac8e7baeb85f6bc6a2206af23b26dd1d1ae0de85a12544cd574b51026686 | Text | 5,255 | 55 | # NowcastPNN
This repository contains all code required for reproducing the results corresponding to the thesis paper titled "Attention-Based Probabilistic Neural Networks for Nowcasting of Dengue Fever in Brazil". The paper proposes a novel neural network (NN) structure, based on the popular attention mechanism and o... |
d4d9d64b435e116d9e1ee95c1f2bd5b774ae28b8fb14d7c3df5893eb8fd8a309 | Text | 5,257 | 129 | # Domain Adaptation-Enhanced Searchlight: Enabling brain decoding from visual perception to mental imagery
This repository contains the full code for the paper "Domain Adaptation-Enhanced Searchlight: Enabling brain decoding from visual perception to mental imagery" (Olza A., Soto D., Santana R., 2024).
[](https://doi.org/10.5281/zenodo.17043463)
<a href="https://www.nature.com/articles/s41540-025-00570-6" > <img alt="Publication badge" src="https://img.shields.io/badge/Publication-de_Rooij_et_al._(2025)-e30613?logo=google-scholar&logoColor=%23FFFFFF&link=https%3A%2F%2Fwww... |
fdd72841022c7d7099f8fe04db2836057dbabad317dc7e1c6130e0af68fcb91f | Text | 5,349 | 138 | # Generative Adversarial Template Construction
### [Project Page](https://www.neeldey.com/deformable-templates/) | [Paper](https://arxiv.org/abs/2105.04349)
Tensorflow 2 code repository for *Generative Adversarial Registration for Impro... |
2cd74b04cd833012233e25607d965677ca3506936ee5df25247aa5d68307aefe | Text | 5,362 | 118 | [](https://github.com/genecell/PIASO/stargazers)
[](https://pypi.org/project/piaso-tools)
[![Total downloads](https://static.pepy.tech/personalized-badge/piaso-tools?period=to... |
f6f01b1bdd60b3cbda89fac3d9241978372a04f4a4a158a078d785da631113df | Text | 5,380 | 93 | <div align="center">
# EpInflammAge
</div>
Repository with source code and [Gradio Application](https://huggingface.co/spaces/UNNAILab/EpInflammAge) for EpInflammAge model.
## Paper
**EpInflammAge: Deep Epigenetic-Inflammatory Clock for Disease-Associated Biological Aging** by
[A. Kalyakulina](https://orcid.org/00... |
c6e6f3fd6c0556d83573a5561f497d1fe712a02ce8413a6cb14c2160c5e74620 | Text | 5,388 | 110 | # dmlib
[](https://doi.org/10.5281/zenodo.3714951)
Python library for calibration and control of deformable mirrors (DM). This
library implements the methods described in detail in this
[tutorial](https://doi.org/10.5281/zenodo.3714951) from
[aomicroscopy... |
184989539a0ae194995e9483a7a9619f3d72a11924dcd575a0f81d53aee0eec8 | Text | 5,409 | 97 | # DeepAdapter
## A self-adaptive and versatile tool for eliminating multiple undesirable variations from transcriptome
Codes and tutorial for [A self-adaptive and versatile tool for eliminating multiple undesirable variations from transcriptome](https://www.biorxiv.org/content/10.1101/2024.02.04.578839v1).
## Install... |
ef0575973ce22ee750ddb4b5f1c4759238627a065288b198e02fb6483420ca26 | Text | 5,434 | 86 | # Kubric
[](https://github.com/google-research/kubric/actions/workflows/blender.yml)
[](https://github.com/... |
caf856e66741e33ee56ddb2674cab01c6718c464168b96ce95cc1d529a29c69e | Text | 5,475 | 49 | # L-Dopa induced changes in aperiodic bursts dynamics relate to individual clinical improvement in Parkinson's disease
---
This repository includes the code and figures associated with the manuscript below:
Hasnae Agouram; Matteo Neri; Marianna Angiolelli; Damien Depannemaecker; Jyotika Bahuguna; Antoine Schwey; Jea... |
62fcfcbb7f8190e12045d983ecf84309cea5afb97d07fbe34427e6e460f63331 | Text | 5,488 | 96 | # End-to-end topographic networks (All-TNNs) as models of cortical map formation and human visual behaviour
**Authors: Zejin Lu, Adrien Doerig, Victoria Bosch, Bas Krahmer, Daniel Kaiser, Radoslaw M Cichy, & Tim C Kietzmann**
🔗 You can find our paper [here](https://doi.org/10.1038/s41562-025-02220-7) 🔗
### Abstrac... |
b5d498a202c90d6db7beb91b3e978ecccf0734c0ab815c6147a22c17971b01cd | Text | 5,522 | 89 |
Data for manuscript: Insight Predicts Subsequent Memory via Cortical Representational Change and Hippocampal Activity
Authors: Becker, Sommer, Cabeza (2025)
Abstract:
Despite the need for innovative solutions to contemporary challenges, the neural mechanisms driving creative problem-solving, including representa... |
9175432651f4f69887e7a07f84b281d3e78019ba5d6ffa40b1d6d0bc1e972a08 | Text | 5,559 | 89 |
Data for manuscript: Insight Predicts Stronger Functional Connectivity and Subsequent Memory via Cortical Representational Change and Hippocampal Activity
Authors: Becker, Sommer, Cabeza (2025)
Abstract:
Despite the need for innovative solutions to contemporary challenges, the neural mechanisms driving creative ... |
48bca0febc081c0d6affe898acf25e0e6bb6d8a83f4da42c779a84a88e93e82a | Text | 5,574 | 140 | # Repository for "A Competitive Disinhibitory Network for Robust Optic Flow Processing in Drosophila"
**Authors:**
Mert Erginkaya $^{1,2}$, Tomás Cruz $^{1,3}$, Margarida Brotas $^{1,4}$, André Marques $^{1}$, Kathrin Steck $^{5}$, Aljoscha Nern $^{6}$, Filipa Torrão $^{1}$, Nélia Varela $^{1}$, Davi D. Bock $^{7}$,... |
f2e5f1c7223fefce45de8d69c54cb57a4bb3ee64cbb4ce3461ed940cd97d99f4 | Text | 5,586 | 54 | # AIMI Annotations Initiative - Prostate MRI Segmentation
## Overview
This AIMI Annotations initiative task was to provide automated segmentation of the prostate from T2 MRI scans for the [ProstateX](https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=23691656) collection in the [NCI Imaging Data Commo... |
6e259f1604f85231b6b6db2ccb884ef383b56084335ff13f0d07319010a3e488 | Text | 5,596 | 111 | [](https://github.com/Pyomo/pyomo/actions/workflows/test_pr_and_main.yml?query=branch%3Amain+event%3Apush)
[]... |
df9ae217907ceecd37571efd47824b259bdcb17dca6445ab000ad5475d28caa4 | Text | 5,675 | 170 | [](http://faculty.uml.edu/Hunter_Mack/)
# PaDELPy: A Python wrapper for PaDEL-Descriptor software
[](https://badge.fury.io/gh/ecrl%2Fpadelpy)
[![P... |
ec999afc594fd1a754e060bfcc4fdc854a4afd868bede73dbf8243df0847bcaf | Text | 5,719 | 99 | # *Euprymna berryi* visual system single cell transcriptomics
Here we provide additional information such as scripts and data for the Japanese bobtail squid *Euprymna berryi* project.
## Project Description
The cephalopod and vertebrate visual systems are a textbook example of convergent evolution with unknown mole... |
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