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43f2b9140afdb57ad2f0d25624f0527c6de642ebc27f47330eec608e946ae33a | Text | 1,809 | 49 | # parcellate
*Note*: This version is frozen to that used to generate the results in Shain & Fedorenko (under
review). To use the current version of the repository, run `git checkout main`.
This codebase provides a command-line interface for functional brain parcellation of volumetric
fMRI data. An analysis is specifi... |
534d731401ba8efffd215ce90b0eb057d888d50fdd0eb1d2c395ae57bdcf8faf | Text | 1,826 | 57 | ### DUAL USE IN CHEM: exploring ways to censor chemical data to mitigate dual use risks.
As we explore strageties to mitigate dual use risks in predictive chemistry (DURPC), we present our data-level mitigation strategy: Selective Noise Addition.
In pursuit of public distribution of chemical data in safe ways, we test... |
4ae3981c9b046781b0d027820ed8e6f8ca0750a5f79d94028195056291be3e85 | Text | 1,836 | 14 | **Read Identifiers:** All files use '_R1' and '_R2' to denote Paired-End (Forward and Reverse) sequencing reads, respectively.
1. hyperconnected_network
- **Contents:** Contains the bound, unbound, and initial libraries corresponding to the design of hyperconnected and multivalent interaction networks (Fig. 6).
- **... |
30e59e3b381bad6dcbf798ddbab64da48fd2b7dbb3e39ffbe4c393b82b540c5f | Text | 1,854 | 32 | # Code Repository
This repository contains the MATLAB (.m) scripts developed for the research presented in the article:
Alessandro Petrini, Claudio Conti, and Davide Pierangeli,
"Degree-of-polarization modulation for high-dimensional optical computing",
Nature (2026). https://doi.org/10.1038/s41586-026-10891-z (2026)... |
b794d62ca4429a5e59b3120075a064ee7f39df77459be59dc6a33cad365ee75b | Text | 1,856 | 41 | ---
# Allegro-E3D Extension
## Overview
This repository provides an extended model of [Allegro](https://github.com/mir-group/allegro), an extension of NequIP framework, detailed in [https://arxiv.org/abs/2506.07579](https://arxiv.org/abs/2506.07579).
## Description
This project extends the Allegro model, which is it... |
3b4aa1e3458f58b41198908bdad9468ec276cb291d7f6bba9230af461f1683ee | Text | 1,897 | 38 | Steps to repeat the analysis from paper:
1. Preparation
- Download EEGLAB from: https://sccn.ucsd.edu/eeglab/download.php
In my case, it was placed in the project folder under eeglab2022.1. Otherwise, modify the EEGLAB path in the MATLAB scripts accordingly.
- Install the BioSig plugin in EEGLAB (via the EEGLAB ... |
c0a5adae009ad7303c93ad9e9071f751aa9be2680aff6ff382b874e937a51b04 | Text | 1,904 | 65 | ## Signal probability along line
[](https://zenodo.org/badge/latestdoi/457620356)
This program aims to summarize the probability of finding a signal along a line from multiple samples.
To use it, run __main__.py.
You will need @pandas, @numpy and @PyQt5 to run this prog... |
f8a89064309fb972dabee7bc4000f7f4c45b66bdfa4d2585f4bc14df2c0877fa | Text | 1,921 | 33 | # qbic-pipelines/rnadeseq
**Downstream differential gene expression analysis with DESeq2 package**.
[](https://www.nextflow.io/)
[](http://bioc... |
abba87c4b7a71ca454f49f758a52327499cdf0ecfc96a0c22210a51cfe2cff32 | Text | 1,960 | 43 | # PCI<sup>ST</sup> (Python and Matlab)
A short library for calculating the state transitions Perturbational Complexity Index (PCI<sup>ST</sup>).
The main function of the `python` library is `calc_PCIst()`, which is composed of two functions corresponding to the two steps involved is the computation of PCI<sup>ST</sup... |
d71aec952d7b1cf0016f414c4782558695ba924abc58cde37e58cd649f2017b8 | Text | 1,986 | 28 | # Chen_Loubiere_2025
System requirements:
- Custom scripts generated for this study were written in R (version 4.4.1) using the R studio IDE (https://www.R-project.org/).
- No special hardware should be required.
Installation guide:
- R and RStudio can be downloaded at https://posit.co/download/rstudio-desktop/... |
a93548bdf01a2b0fb6f96a28b9720e09cadca8772c8ba487ad6928cf6f67a7d6 | Text | 2,059 | 26 | # PRINGLE
This repository contains datasets and Jupyther notebooks associated with our work *"A toolkit for mapping cell identities in relation to neighbours reveals conserved patterning of neuromesodermal progenitor populations" French et al 2025 (in revision)*.
## Purpose
PRINGLE is a collection of Jupyther notebo... |
2161da9995a02083f3c7f9d785d8dc69f5311561357f7ca25eec6f443df48541 | Text | 2,072 | 45 | # Amacrine cells
## Table of Contents
1. [Project Overview](#project-overview)
2. [Repository Structure](#repository-structure)
3. [Getting Started](#getting-started)
4. [Usage](#usage)
5. [Cite](#cite)
## Project Overview
This repository contains analyses for our paper, **"The extreme diversity of retinal amacrine c... |
102b5772fd20a4bb094784d60b7ad0aefd80c1d88f1e56f50c1056fa034bb810 | Text | 2,074 | 45 | # Amacrine cells
## Table of Contents
1. [Project Overview](#project-overview)
2. [Repository Structure](#repository-structure)
3. [Getting Started](#getting-started)
4. [Usage](#usage)
5. [Cite](#cite)
## Project Overview
This repository contains analyses for our paper, **"The extreme diversity of retinal amacrine c... |
71e52b2125e0da63fa662cf7ce8bffb9c90ff2646204ee417fd4839461baec1f | Text | 2,075 | 10 | # Morphometric Similarity in Psychosis- data and code
[](https://zenodo.org/badge/latestdoi/151554225)
This repository contains code to analyse morphometric similarity matrices from patients with schizophrenia and healthy control subjects, as reported by [Morgan et al, 2... |
adb031a9bcc8e901a83879f96870d07250fea3f39331c26c8f7ace975f829384 | Text | 2,083 | 68 | # Villeneuve Laboratory PET Pipeline (VLPP)
VLPP is an open-source software for analyzing PET images combined with freesurfer.
VLPP is builded with the [Nextflow framework][nextflow] which enables scalable and reproducible scientific workflows.
## Usage
`vlpp.nf --pet <> --freesurfer <> --participant <> [-c <>]`
#... |
b8faa0a54239d968e7b191359d2e46029d741906a16384711c6e6212c0b5fddd | Text | 2,092 | 32 | # Wilson-Lein-2D-Image-Astrocyte-Reactivity-and-Morphology-Pipeline
The core function of this code is to analyze astrocyte reactivity via biomarker expression and morphological parameters using 2D images of fluorescent-stained brain tissue. It is designed to be used with images stained with glial fibrillary acidic prot... |
5749ecaf389580e4c712568fb9ec93c6d6dc7c3952cd473178a035df9938795c | Text | 2,106 | 48 | # How to control for confounds in decoding analyses of neuroimaging data ("MultiVoxel Confound Analysis", MVCA)
Code for simulations and empirical analyses for our [article](https://www.biorxiv.org/content/early/2018/03/28/290684) on dealing with confounds in decoding analyses of neuroimaging data. The data (preprocess... |
6fae5a4eec2f6f16064df298155c466f6a101c0a2520198ebdc6d51a57669821 | Text | 2,107 | 7 | This repository provides a complete workflow for generating PK/PD or tumor-growth datasets and training Neural-ODE–based deep learning models on them. It includes utilities for simulating realistic pharmacometric data, preparing datasets, building models, and evaluating model performance through diagnostics such as VPC... |
c0a2f5cebd94a0a127f611701666a919631aa4fd387b1b6df8e04e08666e786b | Text | 2,115 | 68 | # NEMO
Neuronal Embeddings via MultimOdal contrastive learning (**NEMO**) is a self-supervised algorithm for extracting neuron embeddings from electrophysiological recordings to predict the underlying cell-types and brain regions.
Publication: [In vivo cell-type and brain region classification via multimodal contrast... |
b5a64aabf44585c03a1887ee18c7ffe950b8b49c0bb3abace7fd9286fbdfba11 | Text | 2,125 | 91 |
# [IMAG] PANDA: Patch-based Unsupervised Deep Learning for Brain Anomaly Detection via Age Prediction in Fetal MRI
*Imaging Neuroscience*
---
### 🎯 **Multi-Disease Fetal Brain Anomaly Detection Using Brain Age Prediction: A Patch-based Deep Learning Framework**
<p align="center">
<img src="Figure 1.png" width="... |
6287341d30a6b9de3c5499712543b9b817d95e4ea40a676433567db5515812b2 | Text | 2,143 | 90 | # koopman-for-memory-consolidation
Data-driven Koopman operator analysis for fMRI-based memory consolidation dynamics.
This repository implements a structured computational pipeline for modeling latent neural dynamics using Koopman-based methods (including LKIS variants) applied to fMRI data.
---
## Overview
The p... |
5b842851570b00f75f8aee962ed776dba6974de07635856f34baf57ad51fc042 | Text | 2,147 | 55 | # TCR-CoM
<img src="images/tcr_com.png" width="1000">
For questions about running the script or for reporting bugs, please contact:<br/>
*__Brian Baker__(brian-baker[at]nd.edu)*<br/>
or<br/>
*__Esam Abualrous__(e.abualrous[at]fu-berlin.de)*<br/>
-------
### Description
Calculates the geometrical parameter... |
be850ffbf71531b78f12c678342ef88c57dae3020f5195dab18a65e2e38f9cd1 | Text | 2,155 | 57 | # Dual-echo pCASL ETLAS2 processing
This folder contains the dual-echo pCASL processing scripts used in ETLAS-2.
## Files and what they do
- `dual_echo_pcasl_ETLAS2_scripts.py`: Core processing functions (motion correction to template, scaling image creation, design matrix generation, and calibrated-fMRI GLM fitting)... |
c26c0de71a4da0b7ce76610441aa762e9442a38ab38c4f125c9e720cc1a9ca94 | Text | 2,166 | 64 | # nicheformer
This is the official repository for **Nicheformer: a foundation model for single-cell and spatial omics**
[](https://www.biorxiv.org/content/10.1101/2024.04.15.589472v1)
A rendered Jupyter book version of this repository wil... |
6e69e809522c880f093bb8c674351211f939969f594ea8658e64df674371d73f | Text | 2,203 | 57 | # Histology Tissue Fold Dataset
**Version:** 1.0
## Description
This dataset was developed from histological teaching slides obtained from the Department of Histology and Embryology, Faculty of Veterinary Medicine, Firat University. It consists of **2,127 hematoxylin and eosin (H&E)-stained histological images** col... |
25a31776facf3eb7677b2a9eaa8fad0b42365e869736d712d25c4752a9cdbc1f | Text | 2,207 | 46 | # AODF
GPU-accelerated python implementation of ODF filtering algorithm for asymmetric ODF estimation in diffusion MRI. The method is presented in [Poirier et al. (2024)](https://doi.org/10.1016/j.neuroimage.2024.120516).
> [!IMPORTANT]
> AODF filtering is now available as a [**Scilpy**](https://github.com/scilus/sci... |
e233cee5a475fd503410b708f736b6c7826bb1a52e51c9847dff524f6da29cba | Text | 2,224 | 50 | # scGPT-spatial: Continual Pretraining of Single-Cell Foundation Model for Spatial Transcriptomics
[](https://www.biorxiv.org/content/10.1101/2025.02.05.636714v1)
## 🟩 </ins>TL,DR Highlights 🟩
✨ Spatial-omic foundation model ✨ ✨ Contin... |
cc45444e8bf1afa4dbf1b2a5891cae61ce929bdfe24b9ce165ff08cf1f84e125 | Text | 2,232 | 67 | # AMP-BMS
## About
AMP-BMS is a multiscale neural network potential trained on QM/MM data with electrostatic embedding for the simulations of biomolecules in the condensed phase. This repo was used for our [recent publication]() together with a [dataset for multiscale neural networks](https://www.research-collection.e... |
863f513d40d5f266cdbec55ae9b0bea676aa703e7fc111bef8a7e2c28074e0d2 | Text | 2,252 | 46 | # Nanopore sequencing of cell free DNA identifies methylation and fragmentation profiles from cerebral spinal fluid from lung cancer brain metastases
This project analyzed the cfDNA fragmentation, methylation (5mC) and hydroxymethylation (5hmC) profiles from cerebrospinal fluid (CSF) in non-small cell lung cancer (NS... |
e09440e26dc3ff5d1811c58af016ab299549507060ed0d9fe53f1dbaa2910835 | Text | 2,267 | 32 | Raw data for - The neural distribution of vasotocin, oxytocin, dopamine and serotonin in two Australian skinks with contrasting social lives
Repository contents
.zip files
Each zip file contains a single scanned slide. Once downloaded, users can open the .vsi file using the free software OlyVIA which can be
do... |
faed0543ab0e2921f9f0d33d60331b0731df14367da9488a81d512e507691fdb | Text | 2,290 | 51 | # FunBurd
FunBurd is designed to test the association between variants aggregated across a gene set and a given trait. This repository contains all code and data required to reproduce the figures and statistical analyses presented in the project.
<p align="center">
<img src="/FunBurd_Logo.png" alt="Project Logo" wi... |
8893671df02df4bab6b18b1a9501790ae0acebf994e93a9473afe4b5941cb98b | Text | 2,293 | 45 | [](https://zenodo.org/doi/10.5281/zenodo.10224300)
# PhaseNO
Phase Neural Operator for Multi-Station Phase Picking from Dynamic Seismic Networks.
## Update Log
**Version 1.0.1 (March 31, 2025):**... |
db7e00e1adcf735281504f847e143ea8a7a1bde16d1ab2b65b3d4c4844277af3 | Text | 2,328 | 38 | # Tractfinder training streamlines and atlases
Tract orientation atlases are a component of the tractfinder white matter tract mapping tool. Install the tractfinder module here: https://github.com/fionaEyoung/tractfinder
Source dataset (raw diffusion and T1w MRI data) available here: [OSF | EEG, fMRI and NODDI datas... |
e0d8e7463e1cc9b38de6b75a75059787f498790bfa0b871f9b61994bcb110f78 | Text | 2,367 | 55 | # LFODet:Lightweight Few-Shot Object Detection with Meta-Learning in Remote Sensing Images
This repository provides the source code of **LFODet: Lightweight Few-Shot Object Detection with Meta-Learning in Remote Sensing Images**. LFODet is designed for few-shot object detection in remote sensing images and is evaluated... |
fdd1eba6359a4adc83d4b549f2528c9ea655f07eafabaad122d74768d9f123d7 | Text | 2,367 | 35 | # HappyML Introduction
HappyML is a machine learning library for educational purpose. This library simplified many aspects of machine learning including preprocessing, model creation, data visualization...etc. This library is for experimental purpose and does not recommend to use in production.
HappyML 是一個教學用的機器學習函式... |
1704a227ab17922ced5736862fbfaaba7a1a4ae1ea679a08a554df4ae3a851bd | Text | 2,392 | 69 | # DTCR
DTCR is a novel TCR generation model based on discrete diffusion. This model leverages corruption scheme to simulate the TCR mutation process and integrates advanced TCR-epitope binding prediction model to simulate the affinity screening process of TCRs,
providing a flexible and controllable framework for precis... |
780234383f6b61317bfc498f311e1c53683ce3634839dcb90bf43d1d5e89159d | Text | 2,411 | 24 | MT pipeline for FSL
GH, last reviewed 14 Feb 2026
Purpose:
Co-registration of 3D MRI to individual space in acpc orientation for calculation of MTsat1, T12, and B1+ 3
Data requirements and structure:
Dicom 2D images converted to NifTi 3D volumes in arbitrary units [a.u.], that is, of consistent scaling (default o... |
fe6834805bb8d1f8d5293f2813c904b7fb467bc595a6e8dd7e01d23d5dfd3e59 | Text | 2,413 | 53 | # Analysis scripts for: Subthalamic stimulation modulates working memory-related cortical dynamics in Parkinson's disease
Python and R analysis scripts for EEG and behavioral analyses of working-memory-related cortical dynamics in Parkinson's disease during subthalamic nucleus deep brain stimulation.
This repository ... |
3a35c17eb7728559f30829eb6ddfdc4d8c4889a24cfc845f5e2e5f0be9800491 | Text | 2,419 | 63 | # OpenMindServer
OpenMind prototype server code.
## Overview
This project contains the server code written for the OpenMind prototype. The
server uses gRPC to define an API for client consumption. The server is written
in C# using .NET Framework, _not_ .NET Core. The gRPC implementation is based on
the nati... |
2f260be8a8b96f03df12052443820b5cdbdbd1d0c8fae6a1a8f98dd9b078916b | Text | 2,447 | 63 | # cest-kidney-ph-kinetics
Dynamic renal CEST MRI analysis pipeline for pH mapping, kinetic modeling, and voxel-wise kidney function assessment, with uptake–plateau–decay modeling of renal probe handling.
## Citation
If you use this code in your research, please cite the following article:
Mohanta Z, Tressler CM, Go... |
7a768fd6a01e37ed18d6cc595589bb2b72cf0a678f592ce29595dd305fc388b0 | Text | 2,468 | 57 | # Drop-seq
Java and R tools for analyzing [Drop-seq](http://mccarrolllab.com/dropseq/) data
Drop-seq questions may be directed to [dropseq@gmail.com](mailto:dropseq@gmail.com).
You may also use this address to be added to the Drop-seq Google group.
See [Releases](https://github.com/broadinstitute/Drop-seq/releases)... |
2d9f442397bf34da266decd560054265a4a4a44545fc645b1e5b3b51aaa80747 | Text | 2,478 | 122 | # MitoTimer Aging Analysis
## Project Overview
This repository contains the data analysis workflow, statistical testing, and figure generation for a Drosophila MitoTimer aging study.
MitoTimer is a fluorescent reporter that shifts from green to red as mitochondria redox state fluctuates. This project examines mitoch... |
6940f47b3bb277daf26ebe8fe632ffdbd3ca36755d95b9130d5ca042b59e2609 | Text | 2,539 | 23 | # Development of Auditory and Sponatenous Movement Responses to Music over the First Year of Life
General Description
============================
This contains the code for the manuscript "Development of Auditory and Sponatenous Movement Responses to Music over the First Year of Life" (https://doi.org/10.7554/eLife.1... |
276daeb2152903f9e1e5788f6fe3843acd338a5705f040ebd926aadc63f17908 | Text | 2,542 | 45 | ## Overview
This repository contains scripts for converting data to a BIDS-compliant format, preprocessing, analysing, and plotting data from the *Naturalistic Neuroimaging Database 3T+ (NNDb-3T+)*. The accompanying paper, which describes the tasks, MRI protocols, quality control procedures, and more, is available [he... |
936425143029a6b1bd0d92cf7db3d092f34ac05d98f10a3782b01b207c7c93f4 | Text | 2,585 | 63 | # Quattrocento LSL App
**Quattrocento LSL App** connects to an **OTB Quattrocento amplifier** and streams the data to the network as a **[Lab Streaming Layer (LSL) stream](https://labstreaminglayer.org)**.
# Requirements
Quattrocento LSL App requires Windows 10 or newer.
# Installation
There is no special installa... |
8c53a70755be84039768bbc10130d417150d9e9aaeb0f34208da53760479c9c6 | Text | 2,600 | 41 | # stFormer: a foundation model for spatial transcriptomics
## 1. Introduction
stFormer incorporates ligand genes within the spatial niche into transformer encoder of single-cell transcriptomics, and outputs gene embeddings specific to the intracellular context and spatial niche. These gene representations can serve as... |
02e30ef09bd664c6301e663229932958752ee05cf5250dbd4a1902fda5e93a8f | Text | 2,601 | 64 | # Analysis Scripts Overview
This repository contains scripts used in the study [Unsilenced inhibitory cortical ensemble gates remote memory retrieval](https://www.biorxiv.org/content/10.1101/2024.07.01.601454v2) to process calcium imaging data, perform statistical and information-theoretic analyses, analyze behavioral... |
e99eb843cd2faf8e95b376b9aee77b697fc0b796c0a519ff98fbd34f04e13475 | Text | 2,606 | 41 | # CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
[](https://www.biorxiv.org/content/10.1101/2024.11.01.621087v1)
[](https://gith... |
7364da5b622c8c178a3035dda7c1629bc22d766a6e63c57a3bf39041b26c0746 | Text | 2,629 | 53 | # Tractography.jl
<img src="inria.png" alt="Logo" align="right" width="120" />
<img src="neuromod.png" alt="Logo" align="right" width="90" />
| **Documentation links:** | **Build status** | **Coverage** | **Version / Stats** |
| :-: | :-: | :-: | :-: |
| [![][docs-stable-img]][docs-stable-url] [![][docs-dev-img]][do... |
db2ff1a9d1759bd13994774514ea72b8bb8a32c1c958dd77691e1b0bf0a2a01f | Text | 2,630 | 82 |
<!-- PROJECT LOGO -->
<br />
<p align="center">
<a href="https://github.com/liuchuwei/PGLCN">
<img src="_plot/logo.png" alt="Logo" width="800" height="240">
</a>
<h2 align="center">PGLCN</h2>
<p align="center">
Biological informed graph neural network for tumor mutation burden prediction and immunother... |
cb16f9264f286a948e36942976a876ba1734ab297d6ec89450b1958273057d60 | Text | 2,638 | 73 | # PrL Calcium Analysis Code 2026
This combined code archive contains the custom analysis code for the PrL calcium analysis manuscript. The archive keeps the MATLAB graph-theory analysis code and the R machine-learning analysis code in separate folders so that each workflow can be reviewed independently.
## Repository... |
798d94626f7cde1e3d3988898b053e76e602cbc7b058bd06ca15a4ea2e8af453 | Text | 2,643 | 43 | ## Overview
This repository contains scripts for converting data to a BIDS-compliant format, preprocessing, analysing, and plotting data from the *Naturalistic Neuroimaging Database 3T+ (NNDb-3T+)*. The accompanying paper, which describes the tasks, MRI protocols, quality control procedures, and more, is available [he... |
0f6e1d52259b137eb2377a0b3de0cc3d7b2e5795b865e6008857aa0e4807d960 | Text | 2,662 | 74 | # Disinhibitory Signaling Code
This directory contains the training and analysis code accompanying:
> Aquino TG\*, Kim R\*, Rungratsameetaweemana N. **Disinhibitory signaling enables flexible coding of top-down information.** *bioRxiv* preprint: <https://www.biorxiv.org/content/10.1101/2023.10.17.562828v2.full>.
>
> ... |
f72fd8659ef04e8c7a767c7e5933e511fa46b1bfd7bccd46d7596eaa7f75ce34 | Text | 2,684 | 55 | Predicting Human Gaze Beyond Pixels
===================================
Matlab tools for "Predicting human gaze beyond pixels," Journal of Vision, 2014
Juan Xu, Ming Jiang, Shuo Wang, Mohan Kankanhalli, Qi Zhao
Copyright (c) 2014 NUS VIP - Visual Information Processing Lab
Distributed under the MIT License.
See L... |
4ea0c67145166a778690b3d550ae866a07d529fb708799122f5a77a2259534eb | Text | 2,689 | 22 | [](https://doi.org/10.5281/zenodo.20443376)
[](https://github.com/PTRRupprecht/Cell_Detection/blob/master/LICENSE)
[](https://doi.org/10.5281/zenodo.16830879)
This repository contains scripts used in the study [Unsilenced inhibitory cortical ensemble gates remote memory retrieval](https://www.biorxiv.org/content/10.1101/2024.07.01.601454v2) to process calci... |
73631641dd683660a425fa7ab7bac9bbc8338cc1f9be4b83329c1a399c0a9cea | Text | 2,713 | 55 | # MALDI-ST: A deep learning-based framework for rapid bacterial strain typing using MALDI-TOF mass spectra
This is the code repository of the [paper](https://www.medrxiv.org/)
```
This study introduces MALDI-ST, a deep learning framework for rapid bacterial strain typing using MALDI-TOF mass spectrometry data. Evalua... |
65f60ee8ed79fd472256b50741e8040d62b2e38db1cef572c4a18a584814c736 | Text | 2,741 | 44 | # Transfer Entropy (TE)
Transfer entropy from Y to X, where X,Y are two random processes, is an asymmetric statistic introduced by [Schreiber2000], which measures the reduction in uncertainty for a future value of X given the history of X and Y. Or the amount of information from Y to X. Calculated through the Kullback... |
1c7c47ae2761293e17f5db3c8476f7bddd14df24f00df3e7bf830787c0a8a262 | Text | 2,770 | 58 | <p align="center">
<a href="https://doi.org/10.1038/s44386-026-00064-3"><img src="https://img.shields.io/badge/npj_Drug_Discovery-10.1038%2Fs44386--026--00064--3-orange.svg" alt="Paper DOI"></a>
<a href="https://doi.org/10.5281/zenodo.18344673"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.18344673.svg" alt... |
f636152e9d037d04bcdab34a8a3a827d6da5754e4372c814749bb38ebd289f77 | Text | 2,773 | 44 | # FUMA results for AD, PD, and LBD
This deposit contains processed, summary-level FUMA and MAGMA output files supporting the manuscript:
Disease-predominant loci across Alzheimer's disease, Parkinson's disease and Lewy body dementia: evidence from the UK Biobank prospective cohort, conditional GWAS and colocalization... |
4083e2cd96fb1c6145c32e8bdf8e6bcc588463ecc683ff97b7b74a6c19341a6a | Text | 2,785 | 52 | # sctransform
## R package for normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression
The sctransform package was developed by Christoph Hafemeister in [Rahul Satija's lab](https://satijalab.org/) at the New York Genome Center and described in [Hafemeister a... |
7de62e20d163741b3e8311064395f1a07a4fd5d1e726deb4fc469471a184941a | Text | 2,842 | 45 | # danalyzer
danalyzer is a MATLAB toolbox for the analysis of sleep electrophysiology data. The toolbox contains a GUI (graphical user interface) for visualising sleep EEG time series data with the primary function of sleep scoring an visual artifact rejection. Also included are a series of functions for performing st... |
380761749f601e3ce2c4edd91337e16c8df2a90901d1043e82222c3d6388fc37 | Text | 2,858 | 47 | Single_Subject_Grey_Matter_Networks
===================================
Matlab scripts that extract single subject grey matter networks from grey matter segmented T1 weighted images
% READ_ME.txt: About contents Extract_individual_GM_networks
%
% Author: Betty Tijms, 2012. Version 20150902
% UPDATE NOTE
% The batch_... |
53352a3d59fed58bd829277276755f7e34d8776be348781bc11607e8df0b044a | Text | 2,887 | 27 | # 📋 Compositional Complexity in Text and Images
This functional magnetic resonance imaging (fMRI) study aims at studying compositional processing across text and image modalities based on text-image pairs from the [Common Objects in Context-Actions (COCO-A)](https://www.vision.caltech.edu/~mronchi/projects/Cocoa/) da... |
eef11108de58278ead1020add2677f6bdb616b96e36e3d9dd84184b56d5b8f32 | Text | 2,909 | 74 | # DTI-NODDI
Daisuke Matsuyoshi (National Institute for Radiological Sciences ([QST-NIRS](https://www.qst.go.jp/site/qst-english/)) and [Araya, Inc.](https://www.araya.org/))
Implementation of diffusion tensor image based neurite orientation dispersion and density imaging (DTI-NODDI) written in Python.
# Installation... |
f544d7f1732991b89bc2445eda47a8d098935151ef9d251f28083fbd55f86a1f | Text | 2,910 | 74 |
This repository contains the code and data used to generate the analyses described in [paper title]. There are three stages of computational work required to reproduce the findings in the paper. These are (1) Data Acquisition, (2) Data Transformation, and (3) Data Analysis. Data Acquisition relies on the accession and... |
5f0b5921ae60de41fe5725300ce55230122b7c64f1b9a1b3d8f0ea95fa0eb07b | Text | 2,959 | 56 | # Surface tools
Welcome to Surface tools! a collection of tools for surface-based operations
Equivolumetric surfaces: creates equivolumetric surfaces based on the ratio of areas of the mesh surfaces, without the trouble of dealing with volumetric operations.
<img src="https://github.com/kwagstyl/surface_tools/blob/ma... |
461a36561ed57643d82286d972f2cf2fc152e46876f3b0578aa0eaf6085b2b3b | Text | 2,971 | 66 | # gutBrainPipeline
Analysis package for gut-brain processing
# gutBrain_cellSelection_example.ipy
This notebook runs through example use of the pipeline, assuming all relevant data has been placed in an identified folder. The necessary data are:
1. cells0_clean.hdf5
2. volume0.hdf5
3. eP.26chFlt-v10
4. parameters.pic... |
b5e572d81cd61f2a38b1eb4d2356b6ceca0feffe6e9bb9999cd716e5ce52c203 | Text | 2,985 | 59 | C++ code of predictive-coding-inspired variational recurrent neural network model (PV-RNN)
1. Tested environment
-OS: Ubuntu (20.04)
-gcc/g++ version 11.2.0
2. Installation guide
This code requires only gcc/g++.
3. Demo and Instructions
The file structure is below.
“network.hpp”: Network hyperparam... |
43fd78d03df9f02e77725a85a27a73264151026283a7f9b34805c6c4303819da | Text | 2,986 | 78 | # cis-eQTL
# --------
group:
AA (African American)
PR (Puerto Rican)
MX (Mexican American)
All (Pooled)
AFRHp5 (AFR high)
AFRLow (AFR low)
IAMHp5 (IAM high)
IAMLow (IAM low)
files:
AA.cis-eQTL.tar.gz
PR.cis-eQTL.tar.gz
MX.cis-eQTL.tar.gz
All.cis-eQTL.tar.gz
AF... |
9c6ca7e08ea6182a56ffafeb8ccf4db374b4331ac51d562cc5dbae045ac1e645 | Text | 3,012 | 60 | ## Hierarchical Optimization predicts training-induced Plasticity in the Macaque Inferior Temporal Cortex
by Lynn K. A. Sörensen, James J. DiCarlo, Kohitij Kar
*Last updated: April 2026*
### How to use this repository?
Step 1 and 3 should take a few minutes. Step 2 and 4 depend on the speed of your network connecti... |
b814505daf268784b9aeb62a75e221449fe095771b3e302d7a924f8526c8b7d2 | Text | 3,016 | 45 | # IDIR
Code for the MIDL 2022 paper [Implicit Neural Representations for Deformable Image Registration](https://openreview.net/forum?id=BP29eKzQBu3). In this work, we register medical images using differentiable deformation vector fields represented in multilayer perceptrons. We show how this allows us to include vario... |
c1e5166e7cd6cf20543bb50da479b254a96ab143f6436ce1e9ca237b650da8ec | Text | 3,057 | 68 | # PIEZO1 MINFLUX analysis
Matlab scripts and datasets for "State-dependent binding of the wedge domain controls inactivation of the mechanosensitive ion channel PIEZO1"
by Stefan Lechner, Clement Verkest, Lucas Roettger and Nadja Zeitzschel
Contact: s.lechner@uke.de / c.verkest@uke.de
This set of Matlab scrip... |
df918edf426c976452c5aba520c318ae694a93dad1ad6a890a0ea814cd0b88ce | Text | 3,067 | 54 | Philistine
============
A Python package for Phillip's helper and utility functions, especially for EEG and statistics.
Status
--------
|pipeline status| |coverage report| |documentation status| |license| |pypi|
.. |pipeline status| image:: https://gitlab.com/palday/philistine/badges/master/pipeline.svg
:target:... |
3f5c8094ebc8cb053f6eac93e019c2c66f148beed954d3e67e5fd376f7cdf2ad | Text | 3,070 | 54 | Philistine
============
A Python package for Phillip's helper and utility functions, especially for EEG and statistics.
Status
--------
|pipeline status| |coverage report| |documentation status| |license| |pypi|
.. |pipeline status| image:: https://gitlab.com/palday/philistine/badges/master/pipeline.svg
:target:... |
b2733009c2cd4e29d0f5ebf0e998bf2303a64ee87eee54b308dfb91e5de0b08c | Text | 3,090 | 57 | LEAD-DBS
========
LEAD-DBS is ***NOT*** intended for clinical use!
## About Lead-DBS
LEAD-DBS is a MATLAB toolbox facilitating the:
- reconstruction of deep-brain-stimulation (DBS) electrodes in the human brain on basis of postoperative MRI and/or CT imaging
- the visualization of localization results in 2D/3D
- a ... |
dffa1d393f889363fcd78dacae1a7619e4b13e1d6a929bd60159939ea13b67a2 | Text | 3,103 | 58 | # Swin Transformer (Tensorflow)
Tensorflow reimplementation of **Swin Transformer** model.
Based on [Official Pytorch implementation](https://github.com/microsoft/Swin-Transformer).
## Requirements
- `... |
ffaaf0a81a51b82af97bc5d52465945af725772de8f2c0d98961fe197b543ddf | Text | 3,112 | 45 |
<p align="center">
<img width="200" src="https://github.com/sqjin/CellChat/blob/master/CellChat_Logo.png">
</p>
# CAUTION
We have updated CellChat to v2 and migrated CellChat to a new repository. This repository will be NOT updated and maintained any more. Please check the new repository [jinworks/CellChat](https:... |
ced5a378f056d91f8ed3e1cb17fdd7f6f3dfd68fb7928b2b2d5c9b92dcbc43e2 | Text | 3,119 | 70 | # AutoStereota
Gradient index (GRIN) lenses can be used to image deep brain regions
otherwise inaccessible via standard optical imaging methods. Brain tissue aspiration
before GRIN lens implantation is a widely adopted approach. However, typical brain
tissue aspiration methods still rely on a handheld vacuum needle, w... |
0d4bc7f92df63b1a1fa82a810bf3bee517f6fc9c5e2e16f259f4d84eb1cf68af | Text | 3,128 | 103 | ## Study Description
Cortical depth-dependent analysis of BOLD responses to a passive sensorimotor stimulus in neonates and adults
Neonates were divided into four age groups: preterm (<37 weeks PMA, n=8),
early term (37–38 weeks PMA, n=8), mid-late term (>38 weeks PMA, n=7),
and adults (n=4).
---
## Repository Cont... |
7ddf0d5859f8e08734672ed00fc5bb2dfef4405581d87e113ce2ed3012bc4fde | Text | 3,141 | 148 | # Echo-DFCNN
## Overview
Echo-DFCNN provides inference code for echocardiographic video analysis to estimate:
- `GLS` (Global Longitudinal Strain)
- `LVEF` (Left Ventricular Ejection Fraction)
The open-source inference entrypoint is `src/run_inference.py`, with:
- Single-GPU or CPU inference
- Built-in example dat... |
e6414fdfd87007b736465d41c6e9fb544af2ddf11df633c20900c5afe6be082b | Text | 3,143 | 75 | # MSDA-Bench
<p align="center">
<img src="static/cover.svg" alt="MSDA-Bench cover: pipeline benchmark, configuration heatmap, and session-role dashboard" width="100%">
</p>
**Multi-Source Domain Adaptation Benchmark for Cross-Session EEG Classification**
An interactive dashboard for comparing how different source ... |
09e9bc678a397d3ca7e15013a7eb6368418531640a62e53e9aa1865bdf622559 | Text | 3,159 | 62 | # myPLS
myPLS toolbox - PLS analysis for medical image processing
### Set up
*Requirements:*
• Matlab 2017a or higher
• SPM for saving results onto volume
• Slover to display slice maps
• Function ploterr (Copyright (c) 2008, Felix Zoergiebel) for bar plots
*Getting started:*
• Please have a look at the exampl... |
4454680cbe611ede29c2d19da3a000d874ec145ca3f36be9659545c0e5015101 | Text | 3,242 | 71 | # Universal Cell Embeddings
This repo includes a PyTorch [HuggingFace Accelerator](https://huggingface.co/docs/accelerate/package_reference/accelerator) implementation of the UCE model, to be used to embed individual anndata datasets.
## Installation
```
pip install -r requirements.txt
```
## Embedding a new datase... |
ea2d18046f052a5a0c0bda1a13f542d91c4117c9955c5b5b36a2d99c1b6ddd05 | Text | 3,255 | 33 | # Overview
This repository contains the code for the article ["Stable clique membership in mouse societies requires oxytocin-enabled social sensory states"](https://www.biorxiv.org/content/10.1101/2025.08.26.672298v1).
The data generated in this study are still under active use, so we provide here a limited dataset a... |
b84f341e0b3ce0c73c45790e30cf9f6ff4b9743ead720208c32ddf02032dd2ad | Text | 3,292 | 95 | # ReliST
ReliST is a reliability-aware risk layer for spatial transcriptomics deconvolution.
It reads spatial expression data and base-model deconvolution outputs, then produces
spot-level risk scores that indicate where predictions should be trusted, reviewed,
down-weighted, or withheld from downstream interpretation... |
d0a79205de9664dc941adbac139a578093c12cb6a198b17f5f076c20b2d1ffaa | Text | 3,297 | 84 | # BouchardEtAl_2026
Code to generate the figures in Bouchard et al. 2026, *Region-specific weighting of sensory intensity and reward prediction error by dopamine signals*. iScience, 2026
## Overview
Multi-site fiber photometry (GRAB-DA) recordings of dopamine release across the dorsal
striatum (DS), lateral nucleus ... |
d2618376c88a9115c79f217458f88e8c32a782b3250fce5414995fb55ebf3ea4 | Text | 3,297 | 87 | # Mathematical Modeling for a Primitive Form of Habituation in an Amoeba
This repository contains the official C++ implementation of the numerical simulations and the Python scripts for parameter estimation in our manuscript:
> **"Mathematical Modeling for a Primitive Form of Habituation in an Amoeba"**
> Kota Nishi... |
7ceed740efd4b2f0213546a18e1ebea1393cfdbdcb6e631f9887e155c52ed849 | Text | 3,357 | 64 | # Arp3 neuronal polarization — analysis code
Code accompanying *Lin et al., **"An intrinsic cytoskeletal oscillator
establishes neuronal polarity"***.
This GitHub repository is the **active-development mirror** of the code
component of a Zenodo deposit. For the full archive — Source Data
spreadsheets, raw representat... |
79100fedfb53a6ee354b06e789320a67cfe60d49e9b86327712d2e3a91ddc529 | Text | 3,367 | 54 | # Exploring the Impact of T2-weighted MRI Fat-Saturation on Radiomics Stability for Brain Radionecrosis Prediction after Skull-Base Proton Therapy: A Pilot Study
Original repository supporting the article submitted to Cancers [MDPI]
### **Citation**
[Exploring the Impact of T2-Weighted MRI Fat Saturation on Radiomic... |
0db0b7f5d928e888ce7ef1091e8694368fc2ca2ee33c5ae62cba196a966fbbd6 | Text | 3,372 | 87 | Overview of project contents
03_data
01_raw_data
Clinical_data.csv
Demographic data, clinical scales, and d2 and CBTT test results (T1: first session, T2: second session)
Data from from perceptual experiments
One folder per subject, subfolders for apparent motion (AM) and transparency-from-motion (... |
496e24017d55b3a9702d0b861170cf41bce1647262e4aed1e7b43c3e6a27e6eb | Text | 3,389 | 86 | # BouchardEtAl_2026
Code to generate the figures in Bouchard et al. 2026, *Region-specific weighting of sensory intensity and reward prediction error by dopamine signals*. iScience, 2026
[](https://doi.org/10.5281/zenodo.21498194)
## Overview
Multi-site fiber photometr... |
7f452605f75f3b16dac204aea35853bbc1fb829bc2488fa6160de68c6ee9d23e | Text | 3,402 | 71 | # TSNFA Monte Carlo Simulation
Companion repository for the manuscript:
> **Restoring CFAR Validity for Single-Channel IoT Sensor Streams: A Monte Carlo Comparison of CFAR-Family and Sequential Detectors under Cortex-M0+ Constraints**
> S. Makovetskyi, O. Zhelanov, V. Kauk, and L. Thomsen. Submitted to *MDPI Sensors*... |
804f10a98773b23954cff15eb8c031292ec43a1db5838f7eaba90b9ee196309f | Text | 3,403 | 71 | # TSNFA Monte Carlo Simulation
Companion repository for the manuscript:
> **Restoring CFAR Validity for Single-Channel IoT Sensor Streams: A Monte Carlo Comparison of CFAR-Family and Sequential Detectors under Cortex-M0+ Constraints**
> S. Makovetskyi, O. Zhelanov, V. Kauk, and L. Thomsen. Submitted to *MDPI Sensors*... |
18c4f5168b55d9bfda17f8c45d9b3a00f5c7068e63560421dcbde527a5287633 | Text | 3,450 | 65 | # StanfordCars
The Stanford Cars dataset was proposed by Krause et. al in *3D Object Representations for Fine-Grained Categorization*. The citation is at the bottom of this document.
It seems that most online resources, e.g., [1](https://github.com/sigopt/stanford-car-classification), [2](https://github.com/cyizhuo/... |
699c565eb9b17823578f26af454956558bb6a82f869e68381cb8d6410793c0b6 | Text | 3,508 | 44 | This code produces the non-anonymized version of the CNN / Daily Mail summarization dataset, as used in the ACL 2017 paper *[Get To The Point: Summarization with Pointer-Generator Networks](https://arxiv.org/pdf/1704.04368.pdf)*. It processes the dataset into the binary format expected by the [code](https://github.com/... |
6a62082f70787c477fd61ffa6c3f8d1a8b6cacf106d79362516edef9a7b7179d | Text | 3,526 | 47 | surfplot
========
.. image:: https://zenodo.org/badge/380025008.svg
:target: https://zenodo.org/badge/latestdoi/380025008
``surfplot`` is a flexible and easy-to-use package that makes publication-ready brain surface plots. Users can easily set the plot views and layout, add multiple data layers, draw outlines, and... |
702eb50c9aa3e0ab3a8bcd251eca90ab8dd4cf3833d9bcdf25db218ce669e3e3 | Text | 3,547 | 115 | STAR 2.7.11b
==========
Spliced Transcripts Alignment to a Reference
© Alexander Dobin, 2009-2024
https://www.ncbi.nlm.nih.gov/pubmed/23104886
AUTHOR/SUPPORT
==============
Alex Dobin, dobin@cshl.edu </br>
https://github.com/alexdobin/STAR/issues </br>
https://groups.google.com/d/forum/rna-star
HARDWARE/SOFTWARE REQU... |
0c192b489d0fb1ea5dbb661fb0e00206511525c191b5fc42ddd7edee3b8fa408 | Text | 3,564 | 98 | # KC Lifestyle-Based Machine Learning Classifier
This project applies machine learning (ML) approaches to identify lifestyle, demographic, and behavioral factors associated with keratoconus (KC) and to develop a lifestyle-based KC classification framework. The code is implemented in Python and utilizes multiple librar... |
24fac93ad4403a60c0e3ab1e98a9e9d0aa9a74142d7f46da2019b9f00e80b95e | Text | 3,566 | 122 |
# VCboost: reducing false positives in long-read variant calling for SNP and indel detection in challenging genomic regions
Email: holyterror@163.com
----
## Introduction
VCboost effectively filters out a substantial number of false positive sites, leading to a significant improvement in accuracy and F1 score w... |
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