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947db2970cf268adb3f5f34dff8174aa22de2ddeee21d034d8333f3f7208301d | Text | 1,702 | 57 | # FEARTUS
FEARTUS contains the analysis code and behavioral data for the threat learning and extinction experiment involving transcranial ultrasonic stimulation (TUS) of the human amygdala and hippocampus. The repository includes:
- Trial-level skin conductance response (SCR) analyses
- Cluster-based permutation te... |
96c837d3fbf597ce370be9e34a87526c0c077887dabf6cd57ded5867f407d697 | Text | 1,724 | 33 | # Monitoring Single Vesicle Acetylcholine Release with 1D-CNN
This repository contains code and resources for the AI model developed in the study:
**"Monitoring Single Vesicle Acetylcholine Storage and Sub-quantal Release by Living Neurons and Organoids"**.
We developed a **One-Dimensional Convolutional Neural Netw... |
7ce0d24f76a5037d3d406af1ef762c8deca988a98a34eab03d9eded9ea88b588 | Text | 1,733 | 27 | # Forouzandehmehr2026-hiPSC-CMs-Model-hiMCES
A computational model of human iPSC cardiomyocytes electro-mechano-energetics with a new oxygen consumption component
This repository contains code associated with:
W. Li, M.A. Forouzandehmehr, D. McLeod, M.R. Pozo, Y.W. Heinson, M.W. Kay, Z. Li, S. Morotti, E. Entcheva, R... |
8495b967316bb80a49db5a17dd9563ca69316c435057dbfe40bce2de52a47758 | Text | 1,733 | 24 | # Neuroimaging-and-Neuromodulation
Neuroimage has been used to investigate how the brain works for decades. But only in the past 10 years, fMRI has become a promising way to guide clinical treatment, such as repetitive transcranial stimulation (rTMS) for major depression disorder. In this background, we initiated a Ne... |
c01b9c55dc38a9043d32fc1956aadbab5d667d29b21503c2ebc770a755fbf40c | Text | 1,736 | 69 | # hipsternet
All the hipster things in Neural Net in a single repo: hipster optimization algorithms, hispter regularizations, everything!
Note, things will be added over time, so not all the hipsterest things will be here immediately. Also don't use this for your production code: use this to study and learn new things... |
3553ea69a5b9f8f76ab6fa3a45f645bc5f7048ded750f8f7a655d0a4c27bda3e | Text | 1,740 | 19 | [](https://github.com/arbor-sim/arbor/actions/workflows/test-matrix.yml)
[](https://github.com/arbor-sim/arbor/actions/workflows/test-pip.yml)
[ at its core. The wheel axel is the shaft of a continuous potentiometer so that the exact positio... |
35cb61d1e977ca3d3e82417e568d3bb3e0c4f9771d2069456d7c4571bb4c9693 | Text | 1,754 | 38 | # PredictED: Multi-Modal Graph Neural Networks for Endocrine Disruptor Prediction
An innovative graph neural network framework that leverages bidirectional cross-attention to integrate molecular structural information with mechanistic pathway knowledge for robust prediction of *in vivo* endocrine disruption endpoints.... |
4cb74a4700800242b2b9e50b0b6f4ecbc6a4dcd59695c898bf4d564d2a8ef666 | Text | 1,764 | 12 | # A Copula-infused Graph Neural Network for Cell Type Classification in Single-cell RNA Sequencing Data
Cell type identification using single-cell RNA sequencing (scRNA-seq) is critical for understanding disease mechanisms, improving disease diagnosis, and advancing drug discovery. This process involves classifying sc... |
81eb2794c0004b13b5fce045754fbb1572db5f9ee32479e48d0dbc01ed24df65 | Text | 1,778 | 62 | This repository contains the computational analysis code for the publication:
Foertsch et al., Stage-specific Epigenetic Priming Amplifies Gene Activation During Lineage Commitment.
The repository is organized per figure, with each folder containing scripts, processed data, and plots used to generate the results in th... |
f2bc683ac99aae3e75fa34c6980878cb4cb6c812355579c31fba74f25fb4c56e | Text | 1,790 | 26 | This repository contains the code and data for the paper: **"How do infant brains fold?: Sulcal deepening is linked to development of sulcal span, thickness, curvature, and microstructure."** Tung, S.S., Yan, X., Fascendini, B., Tyagi, C., Reyes, C.M., Ducre, K., Perez, K., Allen, A., Horenziak, J., Wu, H., Keil, B., N... |
898a3440adefd974a80e9167d342aaf2f51cb80155ea6b772ea981e5322a0cbc | Text | 1,798 | 27 | # Photostimulus Optimizer
Fast photostimulus optimization for holographic optogenetics using non-negative basis function regression
Please see the accompanying manuscript from MA Triplett, E Baumler, A Prodan, R Stonis, DS Peterka, M Hausser, and L Paninski (2025): https://www.biorxiv.org/content/10.1101/2025.07.31.66... |
1d5f5ebd109851244fca0ea25b3b6d6b084c85b4c82c9b892f262486cf48fd35 | Text | 1,807 | 51 | # Unrolled-blind-SIM
Fast and generalizable blind-SIM reconstruction using an unrolled neural network
## Paper
### High-speed blind structured illumination microscopy via unsupervised algorithm unrolling
*Zachary Burns<sup>1</sup>, Junxiang Zhao<sup>1</sup>, Ayse Z. Sahan<sup>2,3</sup>, Jin Zhang<sup>2,4,5</sup>, Zh... |
903986a38338bb383846a6ad38cdf62d233f1ccd46ff8ee4b6ea45e6fcbf178b | Text | 1,808 | 69 | # SpectrumReconstruction_ResFCN
## Features
- **Residual Architecture**: Implements both identity and dense residual blocks for better performance
- **Regularization**: Includes L2 regularization to prevent overfitting
- **Custom Loss Function**: Combines MSE with L1 loss for improved prediction accuracy
- **Learning... |
bcbbe62aa7df3a350a8c93ca68c09160f941307c54919d612b9927d04e59faa7 | Text | 1,810 | 34 | # MotionCorrectionDWSSFP
This repository provides software associated with ongoing work performing motion-estimation in DW-SSFP. The software is subject to change at any moment whilst the project is under development. For any questions, please email benjamin.tendler@ndcn.ox.ac.uk.
---
This repository contains examp... |
83c55ca63c425bfed626605fb3b4dabd5a2fbf62955a6a9eabda2f1854023bce | Text | 1,812 | 47 | ### Description
This repository contains code and data used for the publication *"Schmid et al. (2025), The variability of motor neuron reflex amplitude estimates in motor unit pools depends on the phenotype distribution and discharge statistics"*
### Installation
1. You need a working MATLAB installation
2. Clone th... |
cb7f5cfc4d7773995cbc7431b988598a4caad9d791976d0deffa4855f8ccc487 | Text | 1,816 | 17 | fmri_rawdata:
For each subject:
"epi*.nii": The raw data for task runs. Each subject contains 12 task runs.
"stat_task*": Files containing beta values and T-values after preprocessing and GLM analysis for each task run.
sort_roi : Contains "roi.nii" files.
stimuli_usedForGLM: Text f... |
3e4b2956bbe45d1690edaef8959b5e26005880e1e01efd6730437a7938cd563c | Text | 1,830 | 37 | # Cell Communication Energy (celcomen)
Causal generative model designed to disentangle intercellular and intracellular gene regulation with theoretical identifiability guarantees. Celcomen can generate counterfactual spatial transcriptomic samples by simulating the effect of local perturbations, such as gene activation... |
6e30925ca85de4ce3ca21b0f608dd449ff9b90362364f3a6cf8280762a7c4b66 | Text | 1,831 | 45 | # Texture preference task: a rapid and training-independent behavioural assay to evaluate somatosensory perception in freely moving mice
Paper: Royea, J., Djerourou, I., Sanliturk, B., Albert, C., & Vanni, M. P. (2026). Texture preference task: A rapid and training-independent behavioural assay to evaluate somatosenso... |
d17d14e31c9ade7bec5f35ff0d67e6d6d2e982224d74f69c3c2c35bacd775a8c | Text | 1,832 | 15 | This repository contains the following data:
- [data_analysis_scripts](https://github.com/noahlorinczcomi/gent_analysis/tree/main/data_analysis_scripts)
- R scripts used to analyze data in [preprint](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5080346)
- [gene_test_results](https://github.com/noahlorinczcomi/... |
864e42bf87d3a281b38e595f89196564f7223359585592e689769a72e8f8957e | Text | 1,833 | 8 | EEG and fNIRS data are provided in the FIF format, which is compatible with the MNE-Python library (Gramfort et al., 2013). In addition, EEG recordings are also available in EDF format, and fNIRS recordings in .snirf format. The fNIRS .snirf files are accompanied by event files as .txt tables, containing arrays of even... |
80f40767ffab07ccc5a29309f037fe41b8d63955518709afdc6da316458e75e6 | Text | 1,840 | 35 | # Converter Utilities for the ACCV LINEMOD Dataset
The LINEMOD dataset is widely used for various 6D pose estimation and camera localization algorithms.
Unfortunately each author chose to convert the original data into an own file format and only support loading from that data.
This repository therefore provides a s... |
09bfff80d03b891deaf8cacc584a8d83e4f9a5fa4a59a69eec24e528a31c3c3b | Text | 1,848 | 56 | # GliaPharm SA - Loïc Lengacher - 27.08.2025
--ELECTROPHYSIOLOGY SIGNAL ANALYSIS--
A python application with a graphical user interface (GUI) for visualizing and analyzing electrophysiology data stored in HDF5 (.h5) files.
It works with files generated from an application called SPOC linked with an electrophysiologic... |
d9ea41519567ece4a430865bf02cb306a18fbbf73b6bdbe128cbdff8226fd704 | Text | 1,859 | 38 | # mriphysio
Utility classes and functions for handling the following:
- Respiration waveform reconstruction from complex-valued or phase-only EPI timeseries
- Siemens/CMRR MRI physiological DICOM
- Siemens MPCU logs
## Respiratory waveform from complex or phase-only EPI timeseries
The installed python package provide... |
915326aad2fd5fdd9e310c8e38d6d2d2464a89272d820cb11a847e9edfe49015 | Text | 1,867 | 34 | # Bruin-2026-MP
Code accompanying the following publication:
> Han, L. K. M.*, Bruin, W. B.*, et al. (2026). **Structural brain differences associated with panic disorder: an ENIGMA-Anxiety Working Group mega-analysis of 4,924 individuals worldwide.** *Molecular Psychiatry*, 31(5), 2402–2417. https://doi.org/10.1038/... |
45c7a8488790dc452d89daabb9218b69cf93e060806e3c25027b1890142da990 | Text | 1,877 | 39 | # Frontotemporal bursting supports human working memory
> Omelyusik, Vladimir, Tyler S. Davis, Satish S. Nair, Behrad Noudoost, Patrick D. Hackett, Elliot H. Smith, Shervin Rahimpour, John D. Rolston, and Bornali Kundu. ["Frontotemporal bursting supports human working memory."](https://www.sciencedirect.com/science/ar... |
44d72470fdfcbb8ce5dfde11f1d30ee1a32715460e7eefdf88033487192959ae | Text | 1,878 | 62 | # KIBREED_public
A genomic prediction project for plant breeding applications using both **R statistical models** and **Python deep learning (CNN)** approaches with specific version requirements.
## Prerequisites
- **R**: Version 4.0.5
- **Python**: Version 3.8.11
## Environment Setup
### 1. Verify Language Versio... |
4f74718efbf693d92942b238e3c20a128c33013748e93b2cab57c5e967080a2b | Text | 1,878 | 58 | # FlexPINN Micromixer project – Extra Codes and Results
This repository contains **sample codes, geometries, and additional results** from a project where we used **Flexible Physics-Informed Neural Networks (FlexPINNs)** to simulate a **3D micromixer** with various fin shapes, orientations, and Reynolds numbers.
The ... |
348610f44e96046972c19d16f920c140da5108a4c4c8fc0e78b45bae0b045835 | Text | 1,880 | 67 | # Pytorch -- Multitemporal Land Cover Classification Network
##### A (yet barebone) Pytorch port of [Rußwurm & Körner (2018)](http://www.mdpi.com/2220-9964/7/4/129/htm) [Tensorflow implementation](https://github.com/TUM-LMF/MTLCC)
Please consider citing
```
Rußwurm M., Körner M. (2018). Multi-Temporal Land Cover Clas... |
3e570b8e6f4bf482872c31754e7e30200346b82fdf4c9a39738e500f80370195 | Text | 1,881 | 35 | # FVT4DWI: FVTool for Diffusion-weighted Imaging
## Quantification of Structural Brain Connectivity via a Conductance Model
This is a toolbox to study structural brain connectivity using a combination
of differential Maxwell’s equations and Kirchhoff’s circuit laws, resulting in
an equation similar to the heat equa... |
24b5ca13b14be7ff9bbb28cc131efa2aa914a5547a0fcbd78ef27f4e6e95f064 | Text | 1,882 | 39 | # Toward super-resolution reconstruction of diffusion-relaxation MRI using slice excitation with random overlap (SERO)
#### Felix Mortensen1, Jakub Jurek2, Jens Sjölund3, Geraline Vis4, Ronnie Wirestam1, Malwina Molendowska1, Andrzej Materka2, Filip Szczepankiewicz1
1 Department of Medical Radiation Physics, Lund U... |
4f6aa38d7e74d05bfea2e1ca3975e2275a2cd0dc6bf10b41a904fe96a1fd4dd7 | Text | 1,885 | 34 | ## Quantification Pipeline of Fluorescent Cells within in vitro images
This pipeline can be used to perform analysis and quantification on images of in vitro images to determine how many fluorescent cells are present as a fraction of the total number of cells stained with DAPI. The median brightness of those cells can ... |
b2907bf7613871ca182907c48fe55af736446a5fa8c0720a2ce5c471f5bf8fdf | Text | 1,912 | 74 | # labdata-tools
Utilities to copy data to and from the data server through python using rclone.
Run custom pipelines from defined data locations.
### Command line:
#### Delete local data
``labdata clean_local -w 4``
Deletes all data from the local directory that is the same on the remote and is older than 4 weeks.... |
d07eb8dcdde94c4d1e4b2c0d4075ebca69fd524cbe65a205c943571dab7e9cd2 | Text | 1,914 | 34 | # DANST: a Deep Domain Adversarial Neural Network based approach for Cell-type Deconvolution in Spatial Transcriptomics
## Overview
Spatial transcriptomics is an emerging technology that can analyze gene expression profiles of tissues while preserving spatial location information. However, current spatial transcript... |
3f0d3e1aa30ac25f951a290272b7cc061f45536e9efe819c90e55d5d536d5cd3 | Text | 1,920 | 33 | <img src="http://t-neumann.github.io/slamdunk/images/slamdunk_logo_light.png" width="300" title="Slamdunk">
### Streamlining SLAM-Seq analysis with ultra-high sensitivity.
[](https://github.com/t-neumann/slamdunk/releases/latest)
[](https://doi.org/10.5281/zenodo.17737517)
A genomic prediction project for plant breeding applications using both **statistical models** and **deep learning** approaches.
## Prerequisites
- **R**: Version 4.0.5
- **Python**: Version 3.8.11
## Environ... |
85e5f3b4261f9100b8d1ca887cffcdb89d19259bb829a6aa24fe5c849839a7b0 | Text | 1,922 | 50 | # Phenotypic Feature-Based Identification of Tea Geographical Origin Using Lightweight Deep Learning
[](https://doi.org/10.1038/s41538-025-00690-7)
[](https://doi.org/10.1038/... |
4303ffa6a3119af5097d59223abb9d61d55290effaa816e6b782b88259efd03d | Text | 1,939 | 51 | # Dynamical Modulation of Hippocampal Replay Sequences through Firing Rate Adaptation
Here is the code to reproduce the results in the main figures in this manuscript.
- To reproduce figures related to the computational model, stay at the `main` branch.
- To reproduce figures related to the experimental data analysis... |
e73d94a6b3533a6a4c43a7ad1af5a0b863f5501a6e4294dbecae514cc0ed57ca | Text | 1,953 | 44 | ### DiaNN R Package
A package containing a number of convenient functions for dealing with feature quantification data. The package has been developed primarily to support DIA/SWATH-MS data analysis with DIA-NN https://github.com/vdemichev/DiaNN and allow for MaxLFQ-based protein quantification (https://doi.org/10.1074... |
e63255673f5b7c474ffb6c30a83504f2b6c4a8c4d72d94c96a1744c143eb86c3 | Text | 1,957 | 24 | MyeliMetric:
MyeliMetric is an open-source toolkit, developed using the Python platform. It provides a streamlined, validated pipeline for post-segmentation analysis of the g-ratio—a vital metric for assessing myelin sheath thickness relative to axon diameter. Traditional g-ratio workflows often suffer from statistica... |
afb10fb4cb578c6541b11f0ca853e28cbecfcf6937852f5bc83e4a08f7656568 | Text | 1,958 | 37 | # GenAI empowers point-of-care MRI: high-fidelity synthetic imaging with multi-site validation
This repo contains the official Pytorch implementation for SynPoC Model.
**Environment** <br /> <br />
Please prepare an environment with python>=3.8, and then run the command "pip ins... |
33fc24809396bd9d8468bf2f1323ea0028f97a77127c1c3c204a750428188776 | Text | 1,959 | 41 | # MEGNET
[](https://github.com/nih-megcore/MegNet/actions/workflows/megnet-actions.yml)
This repository is a fork of the code listed below in the original code reference. This repository adds an automated processing w... |
9e0057a3b49cacd464a2ebd94d3e5a1eef33763667536e0bc1595d25d717d315 | Text | 1,977 | 19 | # ANOVA, Volcano, and DEx Barplot of Coexpression Module Members
Fast parallel ANOVA+Tukey statistics with 0 fallback option, volcano plot, and module-aware stacked barplot
Compatible with the Seyfried Systems Biology Pipeline.
Sample pipeline input which benefits from fallback p value calculation when unreliable ANO... |
4c0fc3135e5783508fb77f655332c65f61de77e121b8fc759c9fd836ae7c19d2 | Text | 1,981 | 47 | <p align="center">
<img src="Logo.jpg" alt="TCRLens Logo" width="300"/>
</p>
# TCRLens: Structure-Aware Equivariant Graph Learning for TCR-pMHC-I Recognition and Immunogenic Epitope Discovery
We introduce TCRLens, a structure-aware deep learning framework that models residue-level interactions across five critical i... |
1dddbe0e16425a704d7bbc18ec764a8e88fdd20100a46a09333f2beab73a93c6 | Text | 1,982 | 18 | # Predicting Migration Barriers
This repository contains the trained models that are part of the manuscript, "Leveraging transfer learning for accurate estimation of ionic migration barriers in solids" by Reshma Devi, Keith Butler, and Gopalakrishnan Sai Gautam. The manuscript is currently available at this [DoI](http... |
01c90a116a0311b5007c601606a8f21fd631cf6bd39d18e70406b3a247dbf504 | Text | 1,992 | 65 | # Adjoint Propagation (AP) Framework
Zhuo Liu (CTTC, SME, USTC) et al.
Our paper has been accepted by eLife. (https://doi.org/10.7554/eLife.108237)
Please cite as:
```bibtex
@article{zhuo2026,
author = {Liu, Zhuo and Shu, Hao and Wang, Linmiao and Meng, Xu and Wang, Yousheng and Li, Xuancheng and Wang, W... |
77c1fe68c4472726b34562e1460443c4a0fb2de8cc378967e9106a849a68bfa9 | Text | 1,992 | 46 | # Dataset for:
**Evaluating the electrical stimulation of bone cells based on an induced transmembrane potential model and intracellular calcium levels**
---
This repository contains all the **data and scripts** used to reproduce the results in the above-mentioned paper. Each folder is self-contained and inclu... |
d72138e41da45d32ded7aa9458fc306825f0528b62d6719b821566675754d496 | Text | 2,010 | 14 | # EmpathyPsychopathy
This repository is associated with the following article:
Marcin A. Radecki, J. Michael Maurer, Keith A. Harenski, David D. Stephenson, Erika Sampaolo, Giada Lettieri, Giacomo Handjaras, Emiliano Ricciardi, Samantha N. Rodriguez, Craig S. Neumann, Carla L. Harenski, Sara Palumbo, Silvia Pellegrin... |
2d8debaba5d50810927a0cc6937738b0d8e9e49cbb2fc2d8660181cf4cd46a9d | Text | 2,011 | 74 | # gMRI2FEM
`gmri2fem` is a python package for processing of human glymphatic MRI-images, i.e. contrast-enhanced brain images, with special focus on concentration-estimation and conversion into `dolfin` for mathematical modelling of brain tracer transport using the finite element method.
The data functionality was devel... |
4685d8ee9bb947deb076a8c6db56f219137cd44b2e32dab492e29dcadbc26105 | Text | 2,014 | 41 | # edge2evc
The open source code for our paper "edge2vec: Learning Node Representation Using Edge Semantics".
## How to use the code
### Dataset
The dataset we offer for test is data.csv. The data contains four columns, which refer to Source ID, Target ID, Edge Type, Edge ID. And columns are seperated by space ' '.
F... |
e8c49beffa8b4bda7259c28c047496b8ab5bd99bdb472d50a2f3254895650e61 | Text | 2,021 | 29 | # Multi-Organ Network Analysis
This repository contains code used to generate the results of the article titled "Multi-Organ Network of Cardiometabolic Disease-Depression Multimorbidity Revealed by Imaging Phenotypic and Genetic Analyses".
## Analysis Pipeline
The analysis workflow follows the methodology described ... |
94c62fdfd132e1c1be02a3dc90c0bf399dac4f31020e037399fe47b7fdaf70fb | Text | 2,025 | 37 | ##Project Title
Generalized Linear Model Simulations
##Description
The data were recorded form mice both during exploration and REM sleep and included in the Excel file. The number of neurons is variable for each mouse and depends on experimental conditions (see C. Blanco-Centurion, S. Luo, D. J. Spergel, A. Vidal-Or... |
71af73586abe512a065f40454341542071570841c7b92f6861c9f775c03b06ba | Text | 2,042 | 11 | # NICE-Net: a Non-Iterative Coarse-to-finE registration Network for deformable image registration
In this study, we propose a Non-Iterative Coarse-to-finE registration Network (NICE-Net) for deformable registration. In the NICE-Net, we propose: (i) a Single-pass Deep Cumulative Learning (SDCL) decoder that can cumulati... |
e70375845f56bf7dd0db17ac1907b7bb34c04e7362f31b92e869f020f4458cac | Text | 2,043 | 37 | ##Project Title
Generalized Linear Model Simulations
##Description
The data were recorded form mice both during exploration and REM sleep and included in the Excel file. The number of neurons is variable for each mouse and depends on experimental conditions (see C. Blanco-Centurion, S. Luo, D. J. Spergel, A. Vidal-Or... |
0888c231529e1692330b193795a91f950a67711dbd37585447cea3ced7ee798d | Text | 2,046 | 37 | # General
Repository associated with the following article:
Roussel Philémon, Zhou Mingyi, Stringari Chiara, Preat Thomas, Plaçais Pierre-Yves, Genovesio Auguste (2025) **In vivo autofluorescence lifetime imaging of spatial metabolic heterogeneities and learning-induced changes in the Drosophila mushroom body** eLife ... |
1367214c8f88b576bf280c8957d0221ff00262f1c16859493e3ad02cee5827d4 | Text | 2,050 | 44 | # Mechanical Compression Induces Neuronal Apoptosis, Reduces Synaptic Activity, and Promotes Glial Neuroinflammation in Mice and Humans
This repository contains all code and accompanying files required to reproduce the analyses and figures from:
**Zarodniuk, M., Wenninger, A., et al.**
*Mechanical compression induc... |
fe9e834e9bef27f79ca100907b99bc97ecdaa6070bf395cb8cddcd9cbead7aeb | Text | 2,052 | 47 | # nmri-meg-eeg-pipeline
This is a collection of Matlab scripts deviced my member of AG Focke (https://neurologie.umg.eu/forschung/arbeitsgruppen/epilepsie-und-bildgebungsforschung/) wrapping around Fieldtrip and other common tool for scripted MEG and EEG analyis.
The provided repo should contain all relevant Matlab s... |
e49cc3bc89eb8e23d9518962ab69f03f7aa2a2ee36b972d613093fca5783cca7 | Text | 2,063 | 49 | # GenROC_Public
Public repo for GenROC Project working with Dr Karen Low
## HPO Code
All the Python files + notebooks for doing analysis on HPO (Human Phenotype Ontology) related things: https://hpo.jax.org/
### HPOFunc.py
A python module for various functions for processing HPO codes.
Main functions of note:
###... |
6d8cab0ef46dc067ca8ef8a42aa3f8339a5cf24bb7c478fd4a073083ad58d636 | Text | 2,064 | 34 | # first_blood
1D and 0D combined hemodynamic simulator for human circulatory system utilizing method of characteristics and MacCormack scheme. The main purpose of the project is research and education at the Budapest University of Technology and Economics, Faculty of Mechanical Engineering, Department of Hydrodyanmic S... |
e34cd9c0f4485c58805d1d196a2beb9b0460f842f4c04d204c675960f62fd3f5 | Text | 2,067 | 43 | # PpaPred
### Prediction Pipeline for foraging behaviours of *Pristionchus pacificus* based on PharaGlow
#### Steps:
1. Download git repository:<br>
with ssh: `git clone git@github.com:scholz-lab/PpaPred.git`
2. Install environmnet:<br>
`conda env create -f requirements.txt -n PpaPred` or `conda env create -f environ... |
458f3aafd8784e9f0debe10280af482016a2024ffc5119dd1c515b3df95c1a8b | Text | 2,075 | 38 | # D-PINNs for Pharmacokinetics
## Overview
This repository contains code for the publication "A Physics-Informed Neural Network Approach for Estimating Population-Level Pharmacokinetic Parameters from Aggregated Concentration Data". It implements Distributional Physics-Informed Neural Networks (D-PINNs) for learning ... |
2c5c94134a3fb7aaa39181cd9a74d9e7ce3367130d305954ba9632c565fc614e | Text | 2,080 | 70 | # G-NECNet
The source code of article 'G-NECNet: A Deep Learning Model for the Detection of Gastric Neuroendocrine Carcinoma'.
## System requirements
This code was developed and tested in the following settings.
### OS
- Ubuntu 20.04
### GPU
- Nvidia GeForce RTX 2080 Ti
### Dependencies
- Python (3.9.6)
- Pytorch ins... |
7f53a6edae75f31bc5a10fc3cc9bb8e1c1723958f676d62cd9ac3df171170192 | Text | 2,084 | 46 | # pyAFQ
Automated Fiber Quantification ... in Python.
For details, see [Documentation](https://tractometry.org/pyAFQ)
For further analysis of results, see [AFQ-Insight](https://github.com/richford/AFQ-Insight)
## Citing _pyAFQ_
If you use _pyAFQ_ in a scientific publication, please cite our papers:
Kruper J, Richi... |
a055429814dc8e69262d8ee10093bb780e92cdde6ed2cc3dbed599580de86aa8 | Text | 2,086 | 44 | # White Matter Volume and Microstructural Integrity Associated with Fatigue in Relapsing Multiple Sclerosis
This repository contains the data and R scripts used in the analyses presented in the paper:
**Alejandra Figueroa-Vargas A., Navarrete S., et al.**
**White Matter Volume and Microstructural Integrity Are ... |
93517d893abbdaea375e0f65c5c5757778109042012f43f1ca88b8f4510e45a7 | Text | 2,087 | 28 | # SimNIBS Memoslap utils
A. Thielscher, 23/05/2025
The uility functions are used in MemoSLAP (https://www.memoslap.de) project 9 to plan personalized transcranial electric stimulation montages.
They need a working SimNIBS installation (http://www.simnibs.org). You need to provide m2m-folders with the personal head mo... |
6d8fea744ed78ab22c64cc4599038b96cb423e3b36248a2cd5b8da83478b9d5e | Text | 2,089 | 34 | # SAM2-segmentation
This repository offers a Colab Notebook for segmentation of time-lapse image with SAM2 model.<br>
ref: Notebook in *Meta Research* repository (https://github.com/facebookresearch/sam2/blob/main/notebooks/).<br>
## Instructions
1. Create a directory named `Colab Notebooks/SAM2-segmentation` direct... |
9f4f76f27bca55bade629795e779e2acd7a32b05c8c32cb56a99c0dd66be268d | Text | 2,097 | 64 | # EEG-Based Cognitive Workload Estimation using Random Forest Regression
This repository contains the Python implementation used in the study:
**“Estimating Cognitive Workload in Robot-Assisted Surgery Using Time and Frequency Features from EEG Epochs with Random Forest Regression”**
The code implements an end-to-en... |
96f024124f40583ded879009699d273baf3017f50eb09970959d2e5aeebcd922 | Text | 2,098 | 35 | Splotch
===================
Overview
-------------
Splotch is a hierarchical generative probabilistic model for analyzing spatial transcriptomics data [1].
Features
-------------
- Supports complex hierarchical experimental designs and model-based analysis of replicates
- Full Bayesian inference with Hamiltonian Mont... |
e77948f6b5a281136e44d55087acd989dead37ca4983c2502e724d16cd15080b | Text | 2,100 | 50 | # easy_hcr
This is a set of jupyter notebooks made to automate the creation of probe pairs for hybridization chain reactions (HCR). It relies and is heavily based on [insitu_probe_generator](https://github.com/rwnull/insitu_probe_generator) by Ryan Null
These notebooks feature
+ Automated blasting and probe pair... |
249cdc4339c95189f8b3605e0b40c084697e0045bf33ce6067b25d397b515eee | Text | 2,117 | 31 | # Multi-Organ Network Analysis
[](https://doi.org/10.5281/zenodo.17669873)
This repository contains code used to generate the results of the article titled "Multi-Organ Network of Cardiometabolic Disease-Depression Multimorbidity Revealed by Phenotypic and Genetic Analyse... |
a23512fb101e9b59ad8fe9842491d35ef560514565359d39adf4c5ac9eee194d | Text | 2,121 | 32 | # Analysis for simplified GUIDE-seq
### This fork of the *umi* [package](https://github.com/aryeelab/umi/wiki) is intended to be used with [GUIDE-seq simplified library preparation protocol](https://dx.doi.org/10.17504/protocols.io.wikfccw)
The simplified GUIDE-seq protocol produces libraries that
1. Can be run o... |
a2d23b6931789e6aef398e992a1395f4188eda855553414e91c8008546c7419f | Text | 2,126 | 29 | # Processing of resting state functional connectivity measurements
This is the code repository which was created for the paper “Longitudinal 7T MRS Study of Glutamate and GABA Dynamics in Alzheimer's Disease Progression: From hyper- to hypoexcitation”, Göschel L, 2026.
## 1. Preprocessing (fMRIPrep; see slurm_scripts/... |
06a0e0b00c276e2f3838d1923be52cd6f1437b806dfc1bb6cc1f935d9721afd5 | Text | 2,130 | 41 | # SVbyEye <img src="man/figures/SVbyEye_online.png" align="right"/>
<!-- badges: start -->
[](https://github.com/daewoooo/SVbyEye/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->
===================================... |
8ddf91c043d2b2d5fb44f887478399ffb511e30f91aa584c14a1dad8542b88b7 | Text | 2,130 | 67 | ### FairOdds-AUC
FairOdds-AUC is a fairness-scaled AUROC metric that multiplicatively penalizes equalized-odds gaps across user-specified sensitive attributes. It enables a single, tunable score that balances utility and fairness via a nonnegative temperature parameter λ.
Formula:
- FairOdds-AUC = AUROC / (1 + λ · GE... |
47784719d9c9b6477d9c6f33378d6d062d76671bd34db4b5882cd171b6bb96fb | Text | 2,154 | 18 | # LOAD_Subtyping
## Background
Late-onset Alzheimer's disease (LOAD) is the most common form of dementia, typically developing after the age of 65. It primarily affects memory, cognitive function, and behavior. This condition is characterized by the gradual accumulation of amyloid-beta (Aβ) plaques and neurofibrillary... |
4951ed9e540d939c8e1c1967c06e947da44ac7490e5ae2766b8ac18cd021f2a1 | Text | 2,155 | 50 | # Machine-Learning-on-Second-Harmonic-Generation-Microscopy-Images
This repository contains the machine learning pipeline developed for the quantitative analysis of liver collagen remodeling using Second-Harmonic Generation (SHG) microscopy images. The methodology is based on the study titled "Quantitative analysis of ... |
5dfc5fb5797d601dea9059a342f16ba812ed7e81088966f2dab16cdca0086c24 | Text | 2,157 | 69 | # **UniGraphPTMs**
**1.Catalog description**
data: Data storage
src: Main code storage
model/embedding: Weight storage
------
**2.Requirements**
```
pandas
scikit-learn
transformers
matplotlib
umap-learn
```
Please download torch version>=2.0 or above to avoid version conf... |
d9be5184cd934f4fff83f9b9ec1e5c20a00cd2e961e295c04e469ff68d29a6f3 | Text | 2,160 | 51 | ## A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19
### Network proximity code
The proximity code can be found in the `proximity/` folder. First, you need to decompress the file `HumanInteractome.7z` in the same folder.
* HumanInt... |
c7b6aff3a35719728abec38ab102cf6fc7ce2dddc54001667d5f6a22db5d8398 | Text | 2,166 | 29 | # Processing of resting state functional connectivity measurements
This is the code repository which was created for the paper “Longitudinal 7T MRS Study of Glutamate and GABA Dynamics in Alzheimer's Disease Progression: From hyper- to hypoexcitation”, Göschel L, 2026.
## 1. Preprocessing (fMRIPrep; see slurm_scripts/... |
e810a789c5b46199b06fdfe8be0104e56b10e09acbbe979b0d0ce8686b39666e | Text | 2,173 | 47 | # Repository Overview
This repository contains code to generate figures for the paper:
**Evidence accumulation from experience and observation in the cingulate cortex**
## System requirements
- Code has been tested in MacOS version 12.7.6 and 15.3.1
- Python version 3.9
- The list of python dependencies is included ... |
9139715acad5a2da83f459cffe5ab792661a7a205b98749a9e46ab2a740c7c61 | Text | 2,177 | 49 | # IntrinSynC
Intrinsic & Synaptic Companion (IntrinSynC) is a toolkit for analysis of intrinsic properties and evoked synaptic currents from patch-clamp recordings.
## Citation
If you use or adapt this code, please cite:
**Ganesh, S., Canty, T. M. & Sabatini, B. L.**
***A silent Kv channel subunit shapes PV neur... |
45870869664561057ae4ad92562e1fd6dd0145f8b76503bba2bb5fea356139d2 | Text | 2,178 | 45 | # Insulin Signaling Drives Tissue-Specific Transcriptomic Programs in Drosophila
This repository contains the full computational workflow, processed data, and figure scripts associated with the manuscript:
**"Insulin signaling engages divergent transcriptional mechanisms in neural and metabolic tissues"**
*Roshni J... |
143b0a12113d8f7f82b6782463b5bc456b09b00674863224326435c7b2edb4de | Text | 2,194 | 52 |
# InterBrainDB - Living Literature Review Database on Hyperscanning
## Purpose
This repository is dedicated to hosting a living literature review tracking emerging research on multimodal
hyperscanning in contexts with a digital component. The platform includes various categories, such as interaction scenario, type o... |
545a855c68b6811e41462cd0add3977fb89bf97abd3e809a49a263e0a1bca042 | Text | 2,202 | 49 | # IntrinSynC
Intrinsic & Synaptic Companion (IntrinSynC) is a toolkit for analysis of intrinsic properties and evoked synaptic currents from patch-clamp recordings.
## Citation
If you use or adapt this code, please cite:
**Ganesh, S., Canty, T. M. & Sabatini, B. L.**
***A silent Kv channel subunit shapes PV neur... |
468b343698b1801f4ba30801d123665ebbe00c94c203a98cbb5d0a5cb64d2d80 | Text | 2,218 | 39 | # Quantum Phase Classification via Quantum Hypothesis Testing
This repository contains the source code and datasets used in the research article:
> **"Quantum Phase Classification via Quantum Hypothesis Testing"**\
> *Akira Tanji, Hiroshi Yano, Naoki Yamamoto*\
> *(Submitted)*
---
## Repository Structure
... |
9314d5954c08acc3207e2a8ca66aff8f6fa690caf14a4f81bcc7c2cb19401220 | Text | 2,218 | 46 | =====================================================================
DeepCardioSim: Advanced Deep Learning for Cardiovascular Simulations
=====================================================================
This repository contains code for deep neural networks and operator models designed for rapid cardiovascular s... |
8c69955e74d08a531ab2fc5e98ac86903e6d53dd8edb55f96743880d9ea9f9f2 | Text | 2,231 | 10 | # NICE-Trans: Non-iterative Coarse-to-fine Transformer Networks for Joint Affine and Deformable Image Registration
Recently, Non-Iterative Coarse-to-finE (NICE) registration methods have been proposed to perform coarse-to-fine registration in a single network and showed advantages in both registration accuracy and runt... |
5ee62178aa06eef5e528617e27cb836d77444af738a94121cb240070ec585c99 | Text | 2,236 | 58 | # Otransfer_PtCeO<sub>2</sub>
This repository contains scripts for the preparation, simulation, and analysis of O<sub>2</sub> uptake on Pt/CeO<sub>2</sub>-Al<sub>2</sub>O<sub>3</sub> systems.
The work employs neural network potential (NNP) models to study oxygen activation and lattice oxygen transfer dynamics across... |
2a7af73fc53f089f3ec2920c5e4e1b5eadb21d49014ab89cb9d9aa0775461760 | Text | 2,248 | 56 | # DoubletDetection
[](https://zenodo.org/badge/latestdoi/86256007)
[](https://doubletdetection.readthedocs.io/en/latest/?badge=latest)
DoubletDetection is a Python3 package to d... |
37615b854279b38053a96576464f3e3c7ec2c35d8d24a753762d233ef5617c37 | Text | 2,248 | 63 | Repository associated with the study: **IGSF11–VISTA is a critical and targetable immune checkpoint axis in Diffuse Midline Glioma**
=============================================================
Overview
--------
This repository contains filtered, preprocessed single-cell / single-nucleus RNA-sequencing (scRNA-seq / ... |
651e42b55986ba7c268c83e180e542d1181ad241ba29e1b739b17f9973d2eb6d | Text | 2,250 | 54 | # LaDynS: Latent Dynamic Analysis via Sparse Banded Graphs
This repo consists of
1. Python package `ladyns` which implements LaDynS [[1](#BYSVK21)]
2. Experimental data analyzed in [[1](#BYSVK21)]
3. Reproducible IPython notebooks for simulation and experimental data analysis in [[1](#BYSVK21)]
## Install
### Prere... |
05eb1c7d203eed2a2c2796521db2aec14443c6691cd2517cb0653824a2bcc2e9 | Text | 2,253 | 65 | # MAKO
This is the repository for MAKO 🦈 (Mammary Analysis for Knowledge of Outcomes), a framework for inferring transcriptomic recurrence risk scores and intrinsic subtypes in breast cancer.
This repository is a work in progress. Please check back occasionally for updates.
# Install
Install dependencies first.
I... |
9cfb32ba909d4c2f1532b6ec9ad4b281d85320d2e2e17c26f75ddc2a31b46fd4 | Text | 2,266 | 53 | A neuroimaging-enhanced AI framework for personalized sports training optimization and injury prevention through multimodal data fusion and deep learning.
---
## Overview
Neuroimaging has become a cornerstone of sports science, offering deep insights into brain activity, cognitive-motor coordination, and injury mech... |
36f2ec55108d93ecf39b9bc6b366d7ac336e432a1c226ab8f9d052d357fd5c27 | Text | 2,267 | 43 | # Myelination-function-coupling
This repository provides core code and relevant toolboxes for data analysis in the article “Dual-axis myelination covariance drives the functional connectivity emergence during infancy”.
## This repository contains the following files:
### <0.Preprocessing>:
The dHCP anatomical data s... |
c7656fdf1eedb83cd3d82aaec559ea6e8c4353b5e84ab7739a3121e4ce43f1ab | Text | 2,271 | 68 | # Stick Insect Proprioception
This repository contains the code for the research papers:
- "Encoding of movement primitives and body posture through distributed proprioception in walking and climbing insects," submitted to PLOS Computational Biology.
- "A spiking neural network model for proprioception of limb kinemat... |
ea7a74456c3e8a6078fe2dd28fe34107b7637b7aae30ac7a558ae03d3fd94fea | Text | 2,271 | 66 | # Violin Plots for Matlab
A violin plot is an easy to read substitute for a box plot that
replaces the box shape with a kernel density estimate of the data, and
optionally overlays the data points itself. The original boxplot shape
is still included as a grey box/line in the center of the violin.
Violin plots are a s... |
f80a20e3da76a5d1ae33f5b638d9ff26324d196b86cc5be25f005ccb9aaeada9 | Text | 2,273 | 78 | # U-test-based-GRN
# 🔍 Differential Network Testing Toolbox
This repository provides Python implementations for statistical testing of group-level differences in binary gene interaction networks. It is designed to work with binary matrices (0/1) representing the presence or absence of gene interactions across sample... |
dad5f4ded67eb015020b66fc678ec832e285a468559982d299de05ec65581403 | Text | 2,286 | 66 | # ColocalizationDeconv.ijm
**FIJI/ImageJ macro for quantifying colocalisation between two fluorescence channels after deconvolution.**
This macro automates the analysis of colocalisation between two fluorescent markers in microscopy images. It performs iterative deconvolution, applies intensity thresholds, and measur... |
7c5eb8d78779dde0c5c02f5519870f76559107c25eaa40199caaeab6ae9de13e | Text | 2,287 | 36 | # Fluorescence-Assessment-in-FGS
This repository contains the algorithms to train and test anomaly detection VAEs on the publically available FGS dataset (https://doi.org/10.5281/zenodo.15260349)
It contains:
1. A training sequence for a contarstive learning Variational Autoencoder for the detection of fluorescence i... |
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