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1ebb355e4d53a0dd9fea4e12e594eab19d6d6da563c310b50dcd52c9a1745282 | Text | 1,824 | 61 | hmmlearn
========
| |GitHub| |PyPI|
| |Read the Docs| |Build| |CodeCov|
.. |GitHub|
image:: https://img.shields.io/badge/github-hmmlearn%2Fhmmlearn-brightgreen
:target: https://github.com/hmmlearn/hmmlearn
.. |PyPI|
image:: https://img.shields.io/pypi/v/hmmlearn.svg?color=brightgreen
:target: https://pypi... |
06193e1ce34267abda166c695f8ab7ff59e7fc3f18744b1a35f00b030f0bbca4 | Text | 1,828 | 62 | # gcmc
Code to run GCMC simulations
## About the code
This is a python program for GCMC simulations of fluid with short-ranged potentials. For electrostatic interaction, a Gaussian truncated potential is used. See detailed documentation at the [Wiki](https://github.com/annatbui/gcmc/wiki/Home).
<p align="center">
<... |
cfef71c6fb3c7a1b829d52ac0752a2ffa76103fcf7ad35c1c6a0eecf08dadb5a | Text | 1,831 | 34 | # MuscleCoordinationRetraining
This repository includes 3 scripts which were used in the following publication to
1. create the input data for Monte Carlo simulations
2. run Monte Carlo simulations using parallel computing in Matlab
3. Summarize the muscle and joint contact forces from the simulations
Additionally t... |
e3a3d98ad64fb7d90dc8374cf0d3a3e9bef233bb589436e1a1ebddd476276e1a | Text | 1,831 | 27 | # Characterization of Atypical Ebola Virus Disease in Ferrets -- OMICS data
## Associated publication
This repository contains data and code that complements the following publication:
>Wenguang Cao, Shihua He, Helene Schulz, Jordan Wight, Michael Chan, Karla Emeterio, Guodong Liu, Jonathan Audet, Kevin Tierney, Kim... |
b624a325036c9fc60e2ce5949e36181ea00e38a6c3a59de3a27c472b9ada4b4e | Text | 1,834 | 30 | SUPPLEMENTARY MATERIAL FOR THE PAPER:
ARC-MOF: A Diverse Database of Metal-Organic Frameworks with DFT-Derived
Partial Atomic Charges and Descriptors for Machine Learning
=================================================================================================================
all_structures.tar.gz -- ... |
1276edfb3cfd87c55ee01d65915071960e20fa38b5bbfb8583983c3dbe7ad82d | Text | 1,839 | 26 | <!-- [![DOI]()]() -->
[](https://badge.fury.io/py/ephyspy)
[](https://github.com/berenslab/ephyspy/blob/main/CONTRIBUTING.md)
[![Tests](https://github.com/berenslab... |
16792bc1c7c5a631e70a118311b8d8780e631dda9e07eadc962abf28e56ba1a8 | Text | 1,842 | 48 | <div align="center">
# Intrinsic cortical geometry is associated with individual differences in local functional organization
F. Alberti, P.-L. Bazin, R. A. Benn, R. Scholz, W. Wei, A. Holmes,
V. Shevchenko, U. Klatzmann, C. Pallavicini, R. Leech, D. S. Margulies
[Preprint here](https://doi.org/10.21203/rs.3.rs-... |
cfb9040c158111ca48a838e1d1b12517e5d08d9c18e7508b30114c86a9b3970d | Text | 1,844 | 27 | # 7TAMIBrain
**A High-Resolution and High-Constrast 7T MRI template to segment Deep Grey Nuclei (on MP2rage T1map).**
The 7TAMIbrain dataset [Girard et al., 2021] (BIDS formatted, 60 qT1 MRI anonymized and cropped + DGN mask of segmentation) is publicly available on the OpenNeuro platform (Dataset ds003967, https://o... |
7a14cffa43beae19c3911c44d357c15220c4208f0078989f9576f43eec8faea4 | Text | 1,848 | 29 | <img width="191" height="20" alt="image" src="https://github.com/user-attachments/assets/abbe830d-b97b-4d42-9502-cb8bb0fdebc2" />
# MEA-bursts
An R script using Spike List csv files to analyse Axion MEA data.
This script generates data about Spike activity and Network bursting for multi-electrode data from Axion Mae... |
bdc4c7428c6d6159cb1894c849f7c32a95c995b5c10e7a3f14617efa7c0dd2d5 | Text | 1,862 | 70 | OHBA Software Library (OSL) in Python
=====================================
Python version of https://github.com/OHBA-analysis/osl-core.
Installation
------------
The recommended installation depends on your operating system. If you are installing on a Mac or Linux machine, we recommend:
```
git clone https://github.c... |
b014b2b1565aa6f7c79f89ce33af1875e201a1098250080e607eec076b484d6b | Text | 1,863 | 55 | Processed CAN Bus Dataset for Hybrid 1D CNN-BiLSTM with Focal Loss for Robust Intrusion Detection in In-Vehicle Networks
Author:
Malini A
Gerardine Immaculate Mary
Description
-----------
This repository contains the processed CAN bus dataset used in the research paper:
"Hybrid 1D CNN-BiLSTM with Focal Los... |
d19f379019c5c90b63f0e6df74f7e33cf2a6f48cc0fcdf908dab1277305bfe32 | Text | 1,866 | 58 | # STESH: A Spatial Domain Recognition Method for Integrating Spatial Transcriptome Multimodal Information Based on Graph Deep Learning
## Overview
Identifying spatial domains is the first important step in spatial transcriptomics (ST). Histological information can provide insights beyond gene expression profiles. T... |
0209d7e38d9e69872d0bf92ec1d4714391e77cd549f95d009da9b960aecff309 | Text | 1,867 | 43 | # benchmarkecogric
# ECoG RIC Benchmarking Pipeline
This repository contains code and example workflows for benchmarking Electrocorticography (ECoG) datasets using the **Recursive Informational Curvature (RIC)** framework. The pipeline includes preprocessing, feature extraction, visualization, and quantitative benchma... |
90eefd17bfcb17e81b0e900b6a02352b04c3d2f1179ae884eb201d6bbab4be91 | Text | 1,872 | 12 | # ibb_toolkit
Iowa Brain-Behavior Toolkit: An open-source MATLAB tool for inferential and predictive modeling of imaging-behavior and lesion-deficit relationships
The /tutorials folder contains MATLAB Live notebooks illustrating how to perform different kinds of modeling analyses using the toolkit. These tutorials ill... |
1311c091756babd0e03a7cd5b3ba408f721860b586d9d58d8f866d44d951af8d | Text | 1,884 | 41 | # Deep learning approach for probabilistic pulmonary function estimation from chest X-ray and peak expiratory flow rate
by
Christoph Killing,
Maximilian Wekerle,
Jayne Sutherland,
Mohammad Rassool,
Lindsay Zurba,
Olena Ivanova,
Salome Charalambous,
Celso Khosa,
Robert S. Wallis,
Michael Hoelscher,
Claire Cald... |
0dfe84d40b37807f1779130eed79bb87cfd5758588ea7061472d3f4a9bc95200 | Text | 1,891 | 73 | What is it?
===========
pyStim uses the [Psychopy] library to create visual stimuli for use in
our visual neuroscience experiments. It includes a graphic user
interface and is capable of running at a minimum of 60 frames/sec and
with the Texas Instruments LightCrafter 4500 DLP is capable of running
in excess of 180 Hz... |
7393a48b40879f1bb42f1dd3b5b3d0db803712c6338a3cb799d7e9c13b4159b7 | Text | 1,893 | 32 | ## Flow2Spatial reconstructs spatial proteomics through transfer learning
Flow2Spatial is the computational part of PLATO (parallel flow projection and transfer learning across omics data).
It aims to reconstruct spatial proteomics from the values of parallel-flow projections in PLATO. Leveraging transfer learn... |
e4cf74478a99d98ecb55e7170d7695bf39d667fb5a07b82677aef7c6e84fdeac | Text | 1,893 | 29 | # Zapline-plus
Zapline-plus is a wrapper for Zapline that automatically removes spectral peaks like line noise from your data while ensuring minimal negative impact, preserving both the non-noise spectrum and the data rank. It searches for noise frequencies, divides the data into spatially stable chunks, and adapts the... |
274ae0044001903d6bbc93cef4832faf0f5b3df96298dd8f695e4233c0dca334 | Text | 1,895 | 24 | # PP-Seq
This repo implements the point process model of neural sequences (PP-Seq) described in:
> **[Alex H. Williams](https://alexhwilliams.info) :coffee:, [Anthony Degleris](https://degleris1.github.io/) :sunrise_over_mountains:, [Yixin Wang](http://people.eecs.berkeley.edu/~ywang/), [Scott W. Linderman](https://w... |
5a1ad4a9c10113b5ba93c383627df86538c8751b6b3f6ac6e41b680bfc5fc10e | Text | 1,896 | 16 | # Online Saccade Detection
Code for the online saccade detection algorithm, as described in:
An adaptive algorithm for fast and reliable online saccade detection\
Richard Schweitzer & Martin Rolfs\
Behavior Research Methods; doi: https://doi.org/10.3758/s13428-019-01304-3 \
bioRxiv 693309; doi: https://doi.org/10.110... |
f5ad5b715f367f020066ee2983da1a2aee25020ced6a81436fac5cfbd6fcdba2 | Text | 1,897 | 31 | MetaNeighbor: a method to rapidly assess cell type identity using both functional and random gene sets
================
MetaNeighbor allows users to quantify cell type replicability across datasets using neighbor voting.
Please refer to its [online](./Documentation.md) or [pdf](https://bioconductor.org/packages/releas... |
1252e9d712faab77241d585e31dd8a5592905999e63db9a24b8b8a5fe3e35137 | Text | 1,910 | 19 | # edge-centric_demo
Demo code repository for [Faskowitz, J., Esfahlani, F. Z., Jo, Y., Sporns, O., & Betzel, R. F. (2020). Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture.](https://doi.org/10.1038/s41593-020-00719-y) In `example_code.m` you can find... |
5b2417683158cc8ad6a51fda04a41f8b880add368d692f87dc856e487023ac98 | Text | 1,918 | 25 | # DIP-DCM toolbox
This is a MATLAB toolbox for identifying parameter priors for Dynamic Causal Modelling (DCM) using a genetic algorithm (GA).
## Getting started
### Prerequisites
The spm12 toolbox is required, please download it from https://www.fil.ion.ucl.ac.uk/spm/
### Downloading
Download the folder
Add spm12 to... |
98f1088d8861979e6be43a12c56092baa79e242ff85b60803b063d16d83306ae | Text | 1,929 | 46 | # Optimization of Power Grid Load Forecasting Models Based on Deep Learning
This repository contains the implementation and experimental results for a deep learning-based framework designed to optimize power grid load forecasting. The approach leverages hybrid temporal encoding, a dynamic attention mechanism, and an a... |
9c6facad0b38b74481eaf8eecd4c6bb23d4807e0a93bc8ecfa01734f1838db05 | Text | 1,930 | 36 | # Analysis Script for Kransberg et al. (2025): Grid-Like Signal fMRI Study
## Repository Contents
This repository contains the R script (`GLS_analyses.R`) used for the primary statistical analyses reported in the paper:
* **[Failure to Detect Entorhinal Grid-Like Signals in a Pre-registered Human fMRI Study]**
* Kra... |
0a8cd376ef5c97e3428aeb497a6e9fe7a7157a7765b17cc1d273f1d1d6188b58 | Text | 1,934 | 46 | # scRNA-seq Analysis: iPSC Differentiation to Tenogenic Lineage
This repository contains the R code used for single-cell RNA sequencing (scRNA-seq) analysis in the following publication:
> Papalamprou A, Yu V, Jiang W, Sheyn J, Stefanovic T, Chen A, Castaneda C, Chavez M, Sheyn D.
> **Single Cell Transcriptomics-Info... |
f3f8c7f3723ca88145b825cf0a7179a6264af277ffca1e1aa0cc85fb8c5375d3 | Text | 1,937 | 52 | ## PubMed RAG for Ion Channels
Helpers:
- `excel2csv.py` to convert `human_IC_annotation_details.xlsx` file to `human_IC_annotation.csv` and `human_IC_annotation_sample.csv`.
- `extract_alternative_names.py` adds a column to the CSV files.
Steps:
1. Create Qdrant collections by running `create_chunk_vectors_qdrant.p... |
931d72c07456bb1a8c2500c20a2bb0f04e737346accec2d1e6b21908d6ad65e7 | Text | 1,948 | 40 | # Interpretable abstractions of artificial neural networks predict behavior and neural activity during human information gathering
Code and data for D'Ambrogio et al. (2025). This repository contains a complete analysis pipeline combining behavioral modeling, optimal policy computation, hybrid neural networks, and bra... |
923e4751ee6ceb86e9669829a817acebb2e37e368190aaf79b0d7fcd0cf53a70 | Text | 1,968 | 44 | # Oddball RNN
Computational modeling and analysis framework for training rate-based recurrent neural networks (RNNs) on oddball / go–nogo style tasks, with downstream population analyses including decoding and lesioning.
Please see https://www.biorxiv.org/content/10.1101/2025.04.09.648012v1 for more details.
## Inst... |
619e8aaffdac0acfd524ada93c0913d5b6f16e85ce513c1009cfedf502a9d4fc | Text | 1,970 | 70 | # CNN-Based Facial Landmark Detection for Orthodontic Cephalometry
Custom Convolutional Neural Network for automated 2D facial soft tissue landmark detection in orthodontic applications.
## Performance
- **Mean Error**: 0.54mm (frontal), 0.51mm (profile)
- **Success Rate**: 97.96% (frontal), 99.31% (profile) at 2mm ... |
90a589def710e5109d9dfe3d60a856556a27996ff5104d33b76636fef2ec82b4 | Text | 1,973 | 37 | # Generate pKa Dataset for Model Training
### Generate Calculated pKa data using Schrödinger's Epik version 2021
For package dependency information, visit [here](https://github.com/Xundrug/MolGpKa/blob/master/environment.yml) if you want to run scripts using MolGpKa.
Using `src/epik/ACD_CHEMBL_pka_short.smi` as an **e... |
00f11e12031e5856ee73415f338e0fbaebe8fcb2df075d26facd4117d57b3037 | Text | 1,974 | 42 | # Neural functional theory for inhomogeneous fluids - Tutorial
This is a tutorial for the methods presented in:
**Why neural functionals suit statistical mechanics**
*Florian Sammüller, Sophie Hermann, and Matthias Schmidt, [J. Phys.: Condens. Matter **36**, 243002](https://doi.org/10.1088/1361-648X/ad326f) (2024);... |
c22584330c29d32b712e5b32e96fa842243540c37a5583a6f0a2de28ddb27bc6 | Text | 1,974 | 57 | ## Files Description
The dataset is presented as a collection of .csv files, where each file represents one exercise performed by one person. The nomenclature of the files is the following: SubjectID_DateID_GestureLabel_RepetitionNumber_CorrectLabel_Position.txt
SubjectID: id uniquely identifying the person performin... |
bee0738aed8e640f9ecb0a7c0b6095f46e642c5e0bf23a6a925d32a9bd179f35 | Text | 1,990 | 16 | # ToothGenNet
A research series on deep generative modeling of tooth anatomy.
## Repositories
| Project (Repo) | Overview | Publication |
|---|---|---|
| [**A Latent Variable Deep Generative Model for 3D Anterior Tooth Shape (toothgennet-anterior)**](https://github.com/superbijk/toothgennet-anterior) | Unconditional... |
1c1b22c6a3f4501c16bd680815e5a3df9cfd2671cbb611c11495ae6dcaad49d2 | Text | 1,991 | 48 | Code accompanying the article: _Regional, functional and transcriptomic decoding of multidimensional brain structure alterations in obsessive-compulsive disorder_
This repository contains:
1. Method implementations in `mpm/`.
2. Synthetic examples in `examples/` that reproduce the analysis logic on toy data.
## Meth... |
f4a72f4ee93ebb0a265944e38a1aada0c3b1ce28b4ef2650bb1a4d0b710f3446 | Text | 1,996 | 49 | # critical_init
Code for [Pachitariu et al 2025](https://www.biorxiv.org/content/10.1101/2025.01.10.632397v1)
For Figures 2 and 3, the data will be shared upon publication of the paper (and is shared as a private, confidential link with the reviewers). The `demo.ipynb` notebook contains code to run an example simulat... |
eb39f81fca08919f70f5e42055337e9a0c5e9420d9811fa3368cd10dbab7dc64 | Text | 1,997 | 34 | PsPM-SCRV_6 dataset
===================
Repository Version: 2020.11.23
This dataset includes skin conductance response (SCR) measurements for each of 20 healthy unmedicated participants (10 males and 10 females aged 21.8+/-3.3 years) in response to 10 discomforting electric shocks. Stimuli are 0.5ms wide square curre... |
c84f67797c944ff13d5305165040a321d3b8e26f21fb2044e172e5d8c4acf000 | Text | 2,000 | 24 | # OMNI-P2x
OMNI-P2x is a universal neural network potential for excited-state simulations. It approaches TD-DFT quality predictions, e.g., for UV/vis absorption spectra at a fraction of cost. OMNI-P2x is faster and more accurate than semiempirical QM methods such as TD-DFTB.
# Usage
Up-to-date online tutorials are pr... |
6997ac38ab6767ac24cbefadc07f515bce1ef52317b34f6611ea3d383f956273 | Text | 2,001 | 82 |
# Machine Learning Biomolecular Absorption Spectra in Graphene Nanopores
This project implements a **machine learning (ML) pipeline** using high-throughput physically generated datasets for predicting optical absorption spectra of biomolecules (amino acids) confined within 2D material (graphene) nanopores.
## Key Fe... |
91ee2138d956d613c5caaa88ff5f64f57666ffa4126cceeb5f9539281bde3151 | Text | 2,001 | 57 | # Fast-Forward Lattice Boltzmann
This repository accompanies the paper "Fast-Forward Lattice Boltzmann: Learning Kinetic Behaviour with Physics-Informed Neural Operators", **accepted in principle at Nature Communications**.
## Installation
`pip install -r requirements.txt`
## How to run
located at `demo/` for three ... |
122e0eab57d366cb132e4a7439b63d8a2b6886050f6354cdf8acba7445fb25ea | Text | 2,003 | 61 | # 🧠 Bq/mL -> SUV and Normalization pipeline
This pipeline converts [¹⁸F]FDG PET DICOM data (in Bq/mL) to NIfTI format expressed in Standardized Uptake Values (SUV), followed by spatial normalization and 3 different intensity normalization methods using MATLAB and SPM.
---
# 📋 Requirements
To run this pipeline, yo... |
85d1c8234d2e189bad095945cd37604c6b2d533fc2e67fcc13b646a5f2acf4ca | Text | 2,008 | 40 | # Custom-code-for-Asaoka-et-al.-2026
This repository contains the custom Jupyter Notebook codes used for analyzing calcium imaging data presented in Figures 5 and 7 of the manuscript: **"Dissociable roles of prefrontal plasticity in decision making strategy and execution of habitual behavior"**.
## Overview
These pip... |
cca99729c14013c37c6c668248d3b5e46f162898753fa33e13fdd3bca5f06bef | Text | 2,013 | 41 | # Deep Audio Segmenter (DAS)
_DAS_ automatically annotates animal vocalizations in raw audio recordings using a deep neural network. It can be used through a graphical user interface, from the terminal, or from Python scripts.
## Installation
```shell
conda create -n das -c conda-forge python=3.14 ffmpeg uv -y
conda... |
7325da20fa2be96f3c63bb9086dbe773b4f1ff999450a4119e52bbc3900fd379 | Text | 2,014 | 52 | # CEST Field Strength Comparison: 3T vs. 7T in Glioma
Code for the manuscript:
> *Field Strength–Dependent Sensitivity of Chemical Exchange Saturation Transfer: A Methodological Comparison of 3T and 7T in a Clinical Cohort.*
> Milena Capiglioni et al., University of Bern, 2025.
---
## Requirements
- MATLAB R2022b o... |
1a7cb629bc4c3f8dec85670b020c3f75a4b81a2cd2de698e7691ed71a8e0fb0c | Text | 2,019 | 54 | # RecobundlesX pipeline
===================
[](https://github.com/scilus/rbx_flow/releases)
[](https://www.nextflow.io/)
[![Docker container badge](https... |
093f09fe8df6153c1286c4c9f9a5a482e400a5b8fb88738a59eaf7d340c2e1ff | Text | 2,028 | 35 | <p align="center">
<img src="archvelo_LOGO.jpg" alt="ArchVelo Logo" width="200"/>
</p>
ArchVelo is a method for modeling gene regulation and inferring cell trajectories using simultaneous single-cell chromatin accessibility and transcriptomic profiling (scRNA+ATAC-seq). ArchVelo extracts a set of shared **archetypal... |
594c1c9a0c2331cde7bfc0a52092a2028c6d82fa58f6cc49f20ca6c7ed1537f8 | Text | 2,032 | 43 | # DuBsUnmix: Deep Unfolding Blind Source Unmixing
## Project Structure
.
├── data/
│ ├── DATA_256.mat
│ ├── three-color brain/
│ ├── three-color simulation-cell/
│ └── three-color simulation-base/
│ ├── extraction.m # Spectral extraction
│ ├── trainset.m # Dataset generation
│ ... |
e392db4daabe1207b9a5357e2518771f1a3c2b9f552a17c64653ab8c3daad9f3 | Text | 2,043 | 20 | ## Longitudinal DNA sequencing analysis in CARE/GLASS datasets
### Overview
The Cellular Analysis of Resistance and Evolution (CARE) and Glioma Longitudinal AnalySiS (GLASS) consortiums both use bulk sequencing to study glioma evolution. The code in this respository was used to perform the pre-processing of whole exom... |
8ef6c3978f30862d74ddb60099eec3758fc8875d69d39781baac901cb0235ac1 | Text | 2,046 | 50 | <p align="center">
<img src="static/images/siibra-api.jpeg" width="600">
</p>
# siibra - API
Copyright 2020-2021, Forschungszentrum Jülich GmbH
*Authors: Big Data Analytics Group, Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH*
[![License](https://img.shields.io/badge/License-Apa... |
b745bb528394044482984126728f35dfbc74c4e9aff3cca8af29d8cbb80dd8ca | Text | 2,046 | 68 | # Opening the black box: a modular approach to spike sorting
Here python scripts and jupyter notebooks to reproduces figures from the paper :
**Opening the black box: a modular approach to spike sorting**
https://elifesciences.org/reviewed-preprints/110588v1
Theses scripts and notebooks are good examples for using... |
08cbb8cb379929c059501f7d9283cd84097afec76a82c698eb6acf7e180ff2d5 | Text | 2,048 | 55 | # Hypertension Prediction a Longitudinal Study
This repository contains the Jupyter notebooks used in our study:
**"A comparison of machine learning algorithms for predicting hypertension incidence based on longitudinal study."**
The code demonstrates data preprocessing, model training with multiple ML algorithms ... |
5458ccc10d6220c834715f50f9b4732ae7d177ef3ed4a4477153ed2dc0816415 | Text | 2,053 | 65 | # OHBA Software Library: Foundation Model Toolbox
This repository contains a **TensorFlow-based** tokeniser and foundation model (MEG-GPT) for parcellated MEG data. Note, a PyTorch version of the tokeniser and foundation model is currently under development:
- [EphysTokenizer](https://github.com/OHBA-analysis/EphysTo... |
0ec43fce16b2c01c2adba864b926f6c047acdca9190b64ca7512cb8314adbb59 | Text | 2,058 | 47 | # ROSMAP_MOFA_public_release
Public release of code and analyses related to **Multi-omics Factor Analysis (MOFA)** using data from the **Religious Orders Study (ROS)** and **Rush Memory and Aging Project (MAP)** cohorts.
This repository accompanies the preprint:
## Citation
> Scheidemantel LP, de Paiva Lopes K, G... |
0f33cf87b5586ad271b552ea8f609f576c441ff5392a315f5e539f1e8d0234f5 | Text | 2,059 | 42 | # Pole ratio - public
## Description
This repo contains the code belonging to the paper: Rotation-Based Metric on the Riemannian Manifold of SPD Matrices Applied to Source Data Selection for Brain-Computer Interface Transfer Learning by Frida Heskebeck, Bo Bernhardsson, and Carolina Bergeling. The repo has one script... |
bd35a14dbf982b0724775579a54e5cf32d0baa72bb1ae4ff4969f71440183451 | Text | 2,059 | 42 | # Gimbal Device
This repository contains the design files and assembly details for the **Gimbal apparatus** used in our recent publication. The device was developed to study human wrist rotations in both **kinematics** and **dynamics** experiments.
## 📂 Repository Contents
- **`BoM.xlsx`**
Bill of Materials (B... |
80370d9924341f7557874fca9afad0910beef65df410b9699cda48278503d59f | Text | 2,067 | 38 | # Pytorch Graph Attention Network
This is a pytorch implementation of the Graph Attention Network (GAT)
model presented by Veličković et. al (2017, https://arxiv.org/abs/1710.10903).
The repo has been forked initially from https://github.com/tkipf/pygcn. The official repository for the GAT (Tensorflow) is available i... |
1811e90d1892425683d4243c8d92cb0350b4b80322a8cf56e92ab387dd9acb7e | Text | 2,074 | 14 | # Active Dendrites Enable Robust Spiking Computations Despite Timing Jitter
Burger, T.S.J., Rule, M.E., O'Leary, T. (2023). Active Dendrites Enable Robust Spiking Computations Despite Timing Jitter. [bioRxiv](https://www.biorxiv.org/content/10.1101/2023.03.22.533815v1), 2023-03. [doi: https://doi.org/10.1101/2023.03.2... |
cbef550f1aaf1074ec2c90ede7d7ff0ba65e2774bd470fed799277773e1d464c | Text | 2,075 | 35 | The following SMILES strings (with stereochemistry removed) can be cross-referenced with Muravyev et al. [1] to obtain experimental detonation velocity measurements.
[1] Muravyev, Nikita V., Dominique R. Wozniak, and Davin G. Piercey. "Progress and performance of energetic materials: open dataset, tool, and implicatio... |
6ebd3ded89aefb227e148e07200a82a4784edf68fb2522dc5b48c91dad276c71 | Text | 2,081 | 45 | Source Code of 《Multi-modal data fusion for supervised learning-based identification of USP7 inhibitors: a systematic comparison》
---
### 1. Overall architecure
### 2. Requirements:
- Python >= 3.8
- numpy
- pandas
- scikit_learn
- pytorch
- tq... |
7625167bd65576ed01a662e4dd0fcb1de2537a7f4a6d035191ad02c220a5ca30 | Text | 2,082 | 46 | # ROSMAP_MOFA_public_release
Public release of code and analyses related to **Multi-omics Factor Analysis (MOFA)** using data from the **Religious Orders Study (ROS)** and **Rush Memory and Aging Project (MAP)** cohorts.
## Citation
> **Integration of aged brain multi-omics reveals cross-system mechanisms underly... |
cad9ba50d558fbe0dab36b4a5fa5ffec5a57101c173d6df84d81d5619c15e600 | Text | 2,082 | 39 | # Supporting Code and Predictions for Corn Grain Yield Prediction
This repository provides the code, prediction outputs, and limited saved model weights to reproduce the model comparison results and performance metrics reported in the manuscript:
**An interdisciplinary Machine Learning-Based Approach for Predicti... |
6bb539874158374fc1c4a28331b9ebe690095922c9024552ca2bb87076ffe463 | Text | 2,087 | 47 | # “Varying Patterns of Association Between Cortical Large-Scale Networks and Subthalamic Nucleus Activity in Parkinson’s Disease”
> Analysis code and scripts used for the manuscript:
> **Varying Patterns of Association Between Cortical Large-Scale Networks and Subthalamic Nucleus Activity in Parkinson’s Disease**.
--... |
244df45078c0877877e529bc9c1f5b1d0d52026d6a36230047f18eda2df20418 | Text | 2,097 | 69 | **Ventrolateral Prefrontal Cortex Learning and Decision-Making (Macaque fMRI Analysis)**
**Overview**
This repository contains MATLAB scripts used for behavioral and fMRI data analyses for the study:
*Ventrolateral prefrontal cortex in macaques guides decisions in different learning conditions*
... |
3d84eee0f51e6bbe573d5f7af4780494d9d9c8170a7767303ecfdceffa95dd4d | Text | 2,097 | 59 | # epinetmap
**Dynamic EEG network toolbox** — fragility, source–sink metrics, and DMD-mode
tracking from short-window linear models of intracranial EEG (iEEG/sEEG).
This toolbox accompanies the paper:
> Dubcek T, Ledergerber D, Koenig K, Elshahabi A, Polania R, Imbach L.
> *Bridging Computational and Clinical Strate... |
044dcfe65d8d061e7193cfbe45b74cbe1eaf03a7ee907f7b5a6a734fa589d5b1 | Text | 2,099 | 53 | We provide Matlab and VERILOG RTL implemntations for a language recognition algorithm
using hyperdimensional computing.
These programs are licensed as GNU GPLv3.
For MATLAB code, there are basically two main functions:
1. buildLanguageHV (N, D): that is a training function.
D is the dimension of hypervectors (in ... |
803e6c085541bd7a21c3a9a0dd1d4e23b3781c15e203413cc516b0365782c93c | Text | 2,100 | 69 | # Trust Gated Augmentation (TGA)
This repository provides the scripts used in the *Trust-Gated Augmentation (TGA)* manuscript to reproduce analyses and (optionally) retrain components.
TGA is a **fail-closed governance layer** for synthetic EEG augmentation under **subject-disjoint generalization**, designed to reduc... |
2bfa7b3f8f414ed2abea17727c0591b264eebe2583aff54b76bc18a378686fc0 | Text | 2,113 | 23 | # Epiphyte
[](https://www.mackelab.org/epiphyte/) [](https://www.mackelab.org/epiphyte/) [ aims to empower researchers worldwide to
explore and analyze multiple whole-brain datasets simultaneously. As the Allen
Institute and its collaborators continue to add new modalities, species, and
insights to the ABC Atlas, this groundbreaki... |
2358b9fe20e0af0a899e56f5221da021600112f28ccac5094530a0ad00cdc72c | Text | 2,115 | 19 | # 2025-08-Oropouche-virus-strains-brain
Code associated with the analysis in the article: Microcephaly-like phenotype triggered by novel reassortant and prototypic Oropouche Virus strains in brain organoids
**RNA-seq data analysis.**
Raw FASTQ files quality were checked with FastQC and aligned against the human tran... |
9d8a8569e0c4d1fc8077657d4d512de247c89163fe00f2e2e9a2fe0f98afd952 | Text | 2,125 | 51 |
# Neonatal EEG Pain Scoping Review – Data & Analysis Repository
This repository supports a scoping review of EEG-based studies of neonatal pain. It includes all the data, scripts, and visualizations used in the analysis and publication.
The repository is organized into three folders:
- `r/`: Main R-based data analys... |
cacae71d8b7d153783cb0e0a9c74d27eb72b381255bb8b5282b5903992cdb1ce | Text | 2,127 | 55 | **scTRAM**
===========
|PyPI| |PyPIDownloads| |Python Version| |License| |Read the Docs| |Build| |Tests| |Codecov| |pre-commit| |Black|
.. |PyPI| image:: https://img.shields.io/pypi/v/sctram.svg
:target: https://pypi.org/project/sctram/
:alt: PyPI
.. |Python Version| image:: https://img.shields.io/pypi/pyversio... |
bab8719f8c792037400ebd14814da90bfe308706c682c1313bd2f90fba287a9f | Text | 2,134 | 47 | This folder contains the data and evaluation code for
"Reservoir computing with collective dynamics of active colloidal oscillators"
2025, Veit-Lorenz Heuthe, Lukas Seemann, Samuel Tovey and Clemens Bechinger.
Instructions:
./exp_data contains the partially processed experimental data.
The raw experimental dat... |
ab71946d891dabd303fcd2d17024c5c594ee0926b176e089c387175d111a264d | Text | 2,149 | 30 | # Introduction
The semantic distance signature described in "Model-based semantic distance reveals adaptive coordination of distinct cognitive systems in flexible knowledge retrieval" is stored in this repository.
Through the integration of computational linguistics with machine learning, this study identified a robu... |
9ef78bf88bdc0ef3f2fbabae90e5d3021d69e0b428161703119a1bd9ca648727 | Text | 2,150 | 25 | # WTPL
The Within Trial Phase Lock analysis (WTPL) measures the rhythmicity of electrophysiological signals at specific time points and frequencies.
WTPL works by calculating the average phase difference between the signal at each time point and a family of time-points before and after it, defined by the user in units... |
74cc55969778b22900b89af9d4716cb33512054c42e5ea72fb6a9763d240e468 | Text | 2,155 | 33 | # Rare Variant Trend Test (RVTT)
This code is associated with the following manuscript. If you use any part of the source code, please cite us:
"Pathway-based Rare Variant Burden Analysis Identifies a Role for the Complement System in An Extreme Phenotype of Sepsis with Coagulopathy"
Pavan K. Bendapudi, Sumaiya Nazee... |
1931312523ee15c8daefcd90ecf61ca8a7d5ab415f8dbbb55ade65e05f690529 | Text | 2,156 | 81 |
# Machine Learning Biomolecular Absorption Spectra in Graphene Nanopores
This project implements a **machine learning (ML) pipeline** using high-throughput physically generated datasets for predicting optical absorption spectra of biomolecules (amino acids) confined within 2D material (graphene) nanopores.
## Key Fe... |
ba10ececebc14111f43fc3969125ea5f510c8e7919710f39de20e88260bfd702 | Text | 2,157 | 30 | # VERA [](https://zenodo.org/badge/latestdoi/265023008)
***V***ersatile ***E***lectrode Localization F***ra***mework was built to simplify electrode localization in ECoG and sEEG. As more and more invasive electrophysiological techniques become available, so do algorithms t... |
20872984c36231f6255a2d06f6ef5467281377d86328095629c8933ada03d97b | Text | 2,161 | 21 | Software package to enable Bayesian hierarchical model fitting of microstructural models to diffusion MRI data. The Bayesian hierarchical model assumes a Gaussian prior over a user-defined region (or regions) of interest. This Gaussian prior is estimated from the data, along with the posterior distributions for the mic... |
81bd12a8c96602ee3ce9eab069573de83e1e90337eb5bbd67d551d5070df84c6 | Text | 2,176 | 29 | # FLAIR-Brain-Age
3D T2-FLAIR brain age prediction model.
Seperate models trained on 1,394 healthy control 3D FLAIR and 3D T1w MRIs. 3D-Inception-ResNet was compared to DenseNet169 and Simple Fully Convolutional Network (SFCN) models. Details of training and results under review for publication and further infomratio... |
0a1cb8b81ad7c342724bde39a3ea15508f5494430a75ebf5b50d1e92ced90cdb | Text | 2,185 | 46 | # Lynxtrogression_v2
## Detecting Genomic Introgressions Among Lynx Lineages
In this repository you can find all of the workflows and scripts I wrote and ran in order to detect introgressed windows in the genomes of *Lynx pardinus* and *Lynx lynx* populations.
### Selecting Samples
I describe how samples are select... |
a970e83f02c216a5234cde1fa549cf011599dc4b24137b60c70d53b2701674d4 | Text | 2,189 | 51 | .. raw:: html
<img src="https://user-images.githubusercontent.com/33202701/187203672-e0415eec-1278-4b2a-a097-5bb8b6ab694f.svg" width="300px" height="200px" align="center">
|PyPI| |PyPIDownloads| |Docs|
Single-cell architecture surgery (scArches) is a package for reference-based analysis of single-cell data.
What... |
7211818e12ce95167e67d2c82316d9c28909c191232f4d7a90996007ef115d18 | Text | 2,193 | 37 | ## CAKE
CAKE: a flexible self-supervised framework for enhancing cell visualization, clustering, and rare cell identification
## Overview
Single cell sequencing technology has provided unprecedented opportunities for comprehensively deciphering cell heterogeneity. Nevertheless, the high dimensionality and intr... |
da349e9ab5cc29a3349439955f58a120b5d6e1481b6f161c6b28cc711e93a4e3 | Text | 2,195 | 51 |
<!-- README.md is generated from README.Rmd. Please edit that file -->
# SAHA
<!-- badges: start -->
<!-- badges: end -->
<u>S</u>emi-<u>a</u>utomated <u>H</u>and <u>A</u>nnotation for Single
Cell and Spatial Datasets
<img src="files/SAHA_logo_wbg.png" width="188"/>
<b>Beta Prior to Release:</b> If you chose to ... |
98792069b58c5e6732ca7374141e644a460d849539f4f58c3abbe1560a94990f | Text | 2,199 | 64 |
<!-- README.md is generated from README.Rmd. Please edit that file -->
# SpNeigh <img src="man/figures/SpNeigh_logo.png" align="right" alt="" width="120" />
<!-- badges: start -->
[](https://github.com/jinming-cheng/SpNeigh... |
5aff828e1a84249cc57d732b9c63c59755ce3c49f306d7d0e8cede5b38c02f29 | Text | 2,208 | 52 | # Custom MATLAB Code for Nociception-Evoked Anesthesia State Analysis
This repository contains custom MATLAB functions used for permutation cross-mutual information (PCMI) analysis and supporting utility functions in the study:
**Integrating multidimensional nociceptive-related cortical features for unsupervised asse... |
7ae8d8bff94a180779e98f1cc1ce5cdd92d61d98d8fba36e8d60292e2ff3aab7 | Text | 2,211 | 63 | # IMPC: Individual Metabolite Production Capacity
This repository contains code for computing Individual Metabolite Production Capacity (IMPC), a framework designed for quantitative analysis of metabolite biosynthetic potential at the individual level. For more details please refer to the paper
*"Machine Learning mod... |
3e1ea3f9c412ef9c2d241bc82cd8f533ab04615472ed68674ad70b1b8e2766d3 | Text | 2,216 | 12 | This repository contains code used in:
Minimal overlaps in responses to insecticides between pollinator species <br>
Alicja Witwicka [1,2], Federico López-Osorio [1], Courtney May [1], Yeahji Jeong [1], Yannick Wurm [1] <br>
1 Biology Department, Queen Mary University of London, London, UK <br>
2 Tree of Life, Wellco... |
edbbe393369032191ef2cf085bb8a016f1356d0ad2cd95b46e06d245b5178189 | Text | 2,219 | 57 | [](https://img.shields.io/badge/python-3.10-blue.svg)
[](http://lussac.readthedocs.io/)
[![Build status](https://github.com/Bar... |
da73b4798cab7d93dc3a953b61ade7150cc8dd2171ed5a679de3e2d8bce8d64a | Text | 2,222 | 12 | # EPS-Project
This repository includes all code used for data analysis and figure generation for the EPS NMO project.
The **"Transcriptomics-analysis"** folder includes the following files:
- The **"rna_seq_pipeline_v2.sh"** is a bash script with the analysis pipeline used for processing the bulk RNA-seq samples start... |
b741ce0b1165c3d112afee5b781efbe2bda671f691cab08df0d974dab17a8444 | Text | 2,233 | 44 | <img width=400 alt="BOLDswimsuite logo" src="https://github.com/jacobchausse/BOLDswimsuite/blob/main/boldswimsuite_logo.png">
# Installation Guide
## Getting Access
This public repository only contains the lessons, examples and documentation for the package, not the source code. To gain access to the code, please fi... |
085bccc6cb8dfbdeac5a2ef75779ab73b5c682cb310bde4ce8511a7a9b98de01 | Text | 2,240 | 91 | ## Text-to-Model: Conditional Neural Network Diffusion for Generating Personalized Models from Texts
### How to run the code
#### 1. Prepare the Data
Place the personalized models (P-models) used for training into the `./Gpt/checkpoint_datasets/` directory.
It's recommended to follow this filename format:
```
co... |
559f54627ae04f8c4e1202f65dbba3f185c84d23940a8c48feef91b58895f602 | Text | 2,261 | 39 | # Wuggy: A multilingual pseudoword generator
<p align="left">
<img src=https://raw.githubusercontent.com/WuggyCode/wuggy/master/assets/wuggy_simplified.svg alt="Wuggy Logo", width="200">
</p>
Wuggy is a pseudoword generator particularly geared towards making nonwords for psycholinguistic experiments. Wuggy makes pseu... |
f0fd609706c01fea2706b29960f603068bdea63cf36b0f3c0570fb213bd4ae59 | Text | 2,261 | 68 | # AFM-Fold
AFM-Fold is an implementation of **protein structure prediction from AFM (Atomic Force Microscopy) images**.
<!--  -->
## Installation
We recommend using Python 3.10–3.12 with CUDA-enabled PyTorch (tested with PyTorch 2.3.1). ... |
7f8501911e4ec4d8a60b4217691b00962101fb8ab8e2d1f4c22e401593fe6139 | Text | 2,266 | 58 | Mentalizing Signatures: Replication Code
===================================================
This repository contains the full analysis pipeline for the study:
Açıl, D., ..., Koban, L., et al. (2025). "Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples... |
d32c245069a50f952484b09901ec4cfd62ecdd276bdf8b1aeb8797085a40f98d | Text | 2,266 | 6 | # Mecp2_hippocampus_signature
Rett syndrome (RTT) is an X-linked neurological disorder caused by MECP2 mutations. Like other X-linked disorders, RTT patients have sex-specific differences in clinical presentation due to distinct cellular environments, where females have ~50% of cells expressing either a mutant or wild-... |
8053e461194d244c39a5729b6cda87d6aeb87c206d78da68a463f0973b873e63 | Text | 2,268 | 60 | Mentalizing Signatures: Replication Code
===================================================
This repository contains the full analysis pipeline for the study:
Açıl, D., ..., Koban, L., et al. (2025). "Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples... |
982704f554b73a2bf524441b74bb7217a9452882fc19f67127f7a77028d6ab3b | Text | 2,275 | 42 | # Neural rhythms as priors of speech computations
[](https://opensource.org/licenses/BSD-3-Clause)
[](https://www.doi.org/)
## Introduction
This repository con... |
a216fe04d7456d2593addef1ecd95acfebe222b27db3008c3217dd09b9ed3c0f | Text | 2,280 | 52 | ### Dev Environment
* Download Miniforge installers from [github](https://github.com/conda-forge/miniforge) or conda if you prefer conda. For the conda installation you can find instructions [here](https://docs.conda.io/projects/conda/en/stable/).
* Initialize conda. Before running conda you must run `conda init` fo... |
cb16cfb19082a63d31a33a693afce468ff1bbf874ee03f24f150b5dedfb8e06a | Text | 2,284 | 50 | # NERINE
This code is associated with the following manuscript. If you use any part of the source code, please cite us:
Nazeen, Sumaiya, _et al_. **NERINE reveals rare variant associations in gene networks across multiple phenotypes and implicates an SNCA-PRL-LRRK2 subnetwork in Parkinson's disease**. _bioRxiv_ (2025)... |
e9cd6ef379cc1702fcc253d16f6328ee8425380100a478b0a82123ae1bb31e59 | Text | 2,293 | 12 | # MT-UGAN
This repository contains the complete MT-UGAN pipeline and a link to the dataset presented in the paper "Segmentation and Classification of Hippocampal Subregions using Multi-Task Generative Adversarial Networks."
# Abstract
Accurate segmentation and identification of hippocampal subregions are essential for... |
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