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7abf434b6147b1a5cd7c8be5b080fa09a1873631049401f9f01e29c275a56292 | Text | 971 | 16 | # A Protein Dynamics-Based Deep Learning Model
(1) Data: protein sequence and function, DCI, and pdb file.
(1.1) AA index: values for AAs. 19.npy
(1.2) “Processed_data” contains test.csv and train.csv. It also contains the K-fold sets of “train_fold#.csv” and “valid_fold#.csv”.
(1.3) DCI folder – contains a folde... |
8035acaff229a6cce47b5047a94af16083273e9be034c207a451b8217ece43fc | Text | 985 | 9 | # SODAlight: Simple Omics Data Analysis (light version)
SODAlight is a stripped down version of [iSODA](https://github.com/ndcn/soda-ndcn). It consists out of the lipidomics visualization module of [iSODA](https://github.com/ndcn/soda-ndcn). SODAlight is used by the [Neurolip... |
db4310a72185fb19a178bb4629c04f5b7c576b143340c7df27acf1a40ed20b78 | Text | 985 | 37 | # ADresilience_CastanhoNaderi
This repository contains the scripts required to reproduce the results presented in the manuscript I. Castanho and P. Naderi et al.
The data required to reproduce the analyses and the outputs generated by the codes in this repository have been deposited on Synapse under the Synapse ID syn... |
5f23f4d7683c1fb6207bf4e6587f95ee5c5cf059a5a94a2df973bc6e4e0cc50a | Text | 989 | 37 | GENERAL INFORMATION
------------------
1. Dataset title: A one-transistor organic electrochemical neuron
2. Authorship:
Name: Juan Bisquert
Institution: Instituto de Tecnología Química, ITQ (UPV-CSIC), Av. dels Tarongers, 46022, València, Spain.
Email: jbisquer@itq.upv.es
ORCID: 0000-0003-4987-4887
... |
9f9253b12173dc9c0624e45df89054980477805481bcaa9d19125ddd3b959880 | Text | 993 | 14 | # MFAT
| INPUT | OUTPUT MFAT-EIGN | OUTPUT MFAT-PROBABILITY |
| ------------- | ------------- | ------------- |
| <img src="https://user-images.githubusercontent.com/43176622/45551155-dcf24b00-b824-11e8-85d9-817e5f2c67f1.jpg" width="250"> | <img src="https://user-images.githubusercontent.com/43176622/45551064-a7e5f8... |
6fc23b56150c53061f87f6362534a73be0f35baeae3e66a021c50640dc5bf507 | Text | 1,004 | 17 | # Shafiq_PlosBiol_ATRX_microglia
[](https://doi.org/10.5281/zenodo.15679297)
# ATRX-null Microglia Multi-omics Analysis
This repository contains all scripts, pipelines, and documentation used in our study of ATRX deletion in microglia. Our analysis inte... |
1062f4a8e4ce215f9b154034c6776acafe7ed73e2ce0d67a2bc72625ae1ce52a | Text | 1,024 | 23 | # Visual detection of seizures in mice using supervised machine learning
This repository contains data and scripts for reproducing results associated with the manuscript. Please see the paper for full details on JABS features and models.
## Requirements
The scripts in the repository require the following R package... |
9cda33ebbc8b1f83b50f209fd3ac2e9d70fa32cb3a7ee8711b659f85de0691c9 | Text | 1,025 | 12 | # Data for "Rapid intracortical AAV delivery in neonatal mice enables stable adult imaging of genetically encoded sensors"
## Figure 8: A large PPC neuronal population in a neonatal-AAV-injected mouse stably expresses jGCAmP8f over 4 weeks and exhibits activity that reflects experimental variables.
The `Figure8` ... |
2d80f3effb3327a955e6d4ad8134a61d6a8e505aafcd5d7d886c21199b49fd26 | Text | 1,028 | 19 | # ClusterGvis Shiny Application
ClusterGvis is a user-friendly and customizable Shiny-based web application designed to streamline workflows for gene cluster-based enrichment analysis and the visualization of complex heatmaps. ClusterGvis provides an intuitive platform for biologists and bioinformaticians to perform f... |
073e0c12da1b1433b2a8312e52cd0bc5110f1fd50bb109ca02699014b5283990 | Text | 1,043 | 29 | Welcome!
This is a python repository to generate HCR v3.0 probes for in situ hybridization visualization of mRNA in Anopheles Gambiae.
The module allows for quick and easy design of probe pairs for the Hybridization Chain Reaction approach (Choi et al. Development 2018.)
You can install the HCR probe design tool by f... |
893f2546f3535b5a06414ab2932b00ba3235fb76b701ca3a11519f0af640c4c5 | Text | 1,051 | 11 | Supplementary dataset for: "A Simple and Scalable Kernel Density Approach for Reliable Uncertainty Quantification in Atomistic Machine Learning"
Python Scripts:
- 1_DESC.py – Generates descriptors from a training database and performs PCA to reduce data dimensionality.
- 2_CALIBRATION.py – Calculates the stand... |
9da307a37139b5af262219710ec834951feac7008ab014e64d7b7c0d7321cf38 | Text | 1,054 | 24 | 
[]([https://github.com/Young0222/MotiL/blob/main/LICENSE.txt](https://github.com/Young0222/MotiL/blob/main/LICENSE.txt))
# MotiL #
This repository is the official implementation o... |
084116182d8aed14899b4e23484454454b96f6c6ea84224449447601d625ebf6 | Text | 1,057 | 15 | # Zillich, Gasparotto, Rossetti, Fechtner et al. - Capturing disease severity in LIS1-lissencephaly
R scripts for all analyses - Unraveling LIS1-Lissencephaly: Capturing disease severity in LIS1-lissencephaly reveals proteostasis dysregulation in patient-derived forebrain organoids
1_organoid_quantifications contai... |
6a3195c618201993e4587baf33cfa63c14b0b76dfec032ccc561a3924bda71eb | Text | 1,061 | 23 | # ImPheNet
Image Phenotyping Network (ImPhenet) is a proof-of-concept framework which uses DL to classify the
organoids into healthy or DS. The main steps of this software are:
- **AI_ImPhenetModels**: Folder with the final trained DL and ML models for day 0 and day 7.
- **Data**: Folder with the csv files pointing ... |
def35cb81208b9a5d99e0195ca7c320deaa9698c2f2b7de60bc5d8c92aedc126 | Text | 1,072 | 28 | Select design problems
% 1. Three bar truss design
% 4. Speed Reducer
% 6. Pressure vessel design
% 7. I-beam vertical deflection
The other codes are in the form of functions and cannot be run directly.
The optimization algorithm code is placed in the optimization folder, and other algorithms can be placed... |
367271f77123903bfeaa1dfe2a5281fc6feec7b57efa7399a230930d750557d0 | Text | 1,076 | 34 | AcrossPatientDecodingModel
==========================
This package demonstrates the use of the across-patient and cohort movement decoding model, presented in the publication *"Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants"* [1]_.
We recommend installing the... |
acec4a4b7f466c7151e0036173851151f866d8429058ca192b2646e14351f8c5 | Text | 1,076 | 17 | # pydentate
pydentate is an open source Python-based toolkit for predicting metal-ligand coordination in transition metal complexes (TMCs). Using only SMILES string representations as inputs, pydentate leverages graph neural networks to predict ligand denticity and coordinating atoms, enabling downstream generation of ... |
f6460ce2fcf117d1615c867760932a9d1aac9c3573a1e61591e32dc81859450a | Text | 1,088 | 10 | # Chemogenetic tuning reveals optimal MAPK signaling for cell-fate programming
This repo contains all data analysis and code to create the figures in Lende-Dorn et al. "Chemogenetic tuning reveals optimal MAPK signaling for cell-fate programming".
# Python setup
1. Create a virtual environment in the repository direct... |
17f7d5c1caa84314602c0200cf911f39214b9dd01c3e44ee0267bac8dbe1f542 | Text | 1,089 | 15 | # COX_TDP-fingerprinting-datasets
This repository contains exemplar and pre-processed datasets used in the research manuscript titled *Fingerprinting disease-derived protein aggregates reveals unique signature of Motor Neuron Disease*.
### Datasets
The datasets are provided in the following categories:
- ``... |
bf603d152b1ced57a8eae3e6a82bf10fc0aa63e455aa9c8a58ff9ca662b453a1 | Text | 1,095 | 20 | # Affordable solution for investigating zebra finch iEEG signals
This repository contains open-source code and analysis for recording intracranial EEG (iEEG) signals from zebra finches. The project aims to study neural dynamics during different levels of anesthesia and in response to auditory stimuli, using affordabl... |
b35f87458d18eecbe84456566ea57333169aa3ff8f23da42c83ddc7b1c25c571 | Text | 1,096 | 16 | # S4NN
The implementation of S4NN presented in "S. R. Kheradpisheh and T. Masquelier, Temporal backpropagation for spiking neural networks with one spike per neuron, International Journal of Neural Systems (2020), doi: 10.1142/S0129065720500276", availbale at: https://www.worldscientific.com/doi/10.1142/S01290657205002... |
4fc2dd6f29ca5ad4e5061d1d1b305661a1053d4da2b0a7b3f013e9ed1d505e2c | Text | 1,099 | 29 | # miniplace
These scripts can be used for simulation of mini (mPSC) data. It was written for Greger & Watson 2024 [doi:10.1101/2024.10.26.620084](https://doi.org/10.1101/2024.10.26.620084)
Included files:
**minisimulation.m** - Main script for event simulation
**miniranscaler.m** - Function for recording simulation,... |
6034108b6820028dfb3ffaddbbcfd2a9e619aaa94cd91dcf03b6d7d93a8e2381 | Text | 1,111 | 12 | # Perriot and Jones, 2025
### Neuron-reactive KIR+ CD8+ T cells display an encephalitogenic transcriptional program in autoimmune encephalitis
Code for R analyses for Perriot and Jones et al, 2025. The TCR-seq data used in the study is available at NCBI GEO with accession [GSE263666](https://www.ncbi.nlm.nih.gov/geo/... |
f56fa657576fabd7d96ebbf1a7fd4bf9bcca08491eb24af15c7b3d4076d7499d | Text | 1,115 | 33 | # BloemBakstMcGuireLing_eLife_2025
Code associated with Bloem, Bakst, McGuire & Ling (2025) eLife publication
**Overview**
---------
This project repository contains code and data associated with the following publication:
**Paper**: [Dynamic estimation of the attentional field from visual cortical activity][1]
... |
b3a3dbbb64fef9fa87ee48387526d965ddfc7458d59d87e4b414ae14cdf44a52 | Text | 1,128 | 24 | # Multi-ancestry Brain pQTL Code Sharing
**Publication**: Wingo et al., _Multi-ancestry brain pQTL fine-mapping and
integration with genome-wide association studies of 21 neurologic and
psychiatric conditions_
This repository provides transparency for critical analysis details of the
manuscript.
For MESuSiE analysis... |
a7dffdab55efbe2f21e21414d8b59174d133a43e9acc20df83c5aa0aa1a8ae06 | Text | 1,163 | 25 | # Repo with code for the validation of deepRetinotopy toolbox
This repository contains the code to validate the [deepRetinotopy toolbox](https://github.com/felenitaribeiro/deepRetinotopy_TheToolbox), accompanying [our manuscript](https://www.biorxiv.org/content/10.1101/2025.11.27.690210v2).
## How to run the validati... |
be587fd29c6b2a2f85ca64484fe508aa2cf7a666b875d608966214c9c10781d5 | Text | 1,176 | 53 | # ImmunoRankAge
A machine learning model for predicting immune age by rank-enrichment algorithm.
This model, operating in both CPU and GPU modes, quickly predicts over 200 samples in less than 10 seconds.
## Requirements
- R == 4.1.... |
e2b1f85fc4641cd390b85536f5861968849ca7a186126e5d915ea0c2082f2409 | Text | 1,183 | 28 | # MK-801
[](https://github.com/ScreenNeuroPharm/MK-801/blob/master/LICENSE)
> The repository contains the data and the functions needed to reproduce the analysis reported in the article "In vitro clustered cortical networks reveal NMDA-dependent modulation... |
e88537caa272fdf3f5ccd4989bc300336d396999c3a496a11d5a7b704658f4e3 | Text | 1,187 | 22 | # Code for Building compositional tasks with shared neural subspaces, Tafazoli et al. 2025
This is the repository for code supporting all of the analysis and figures related to Tafazoli et al, Building compositional tasks with shared neural subspaces, bioRxiv 2025, **https://www.biorxiv.org/content/10.1101/2024.01.31.5... |
d804c9e17a7f32646fe002cbf4ebded5e5be33c4e32b465d8d98ae70fbb7b202 | Text | 1,189 | 47 | pyeeg
=====
Python + EEG/MEG = PyEEG
Welcome to PyEEG! This is a Python module with many functions for time series analysis, including brain physiological signals. Feel free to try it with any time series: biomedical, financial, etc.
Installation
------------
### Via Git
Clone the repo via HTTPS:
```sh
$ git clon... |
e3baf120738a02ee93e9e1f20528367003f4136a0c18a14e42e1b478d341b96d | Text | 1,191 | 36 | # DAPI_NEUN_ORF1P
* **Developed for:** Tom
* **Team:** Fuchs
* **Date:** July 2023
* **Software:** Fiji
### Images description
3D images taken on a spinning-disk with a x40 objective
3 channels:
1. *CSU_405:* nuclei
2. *CSU_642:* NeuN cells
3. *CSU_561:* ORF1p cells
### Plugin description
* Detect DAPI nucl... |
986937919eea2e3c893ef9289feb730f4b3573c0ff4376eda74e6d4cd780bfde | Text | 1,207 | 15 | # Mouse Mammary Gland Cell-Sorted RNA-seq
This repository contains the data-processing pipeline scripts and analysis code for mammary gland cell-sorted total RNA-seq in hybrid mice from reciprocal cross between CAST and B6 mouse strains.
The main data processing pipeline is built using _snakemake_, and was run the U... |
55c909cffb30f324b2c12008515e7263d03846c4c608316043b56908810a846b | Text | 1,213 | 49 | # loopcolcox
R-package to perform loop of univariate cox analyses on columns of a dataframe
### compute analyses
```r
library(devtools)
install_github("cdesterke/loopcolcox")
```
### compute analyses
```r
##load package
library(loopcolcox)
data(cancer)
library(dplyr)
cancer%>%select(3:7)->data
df<-coxbycol(cance... |
9d4c38ea47ccf1e968222c93d26f7081f3a7b8e398840d6f98eb48a75e124a81 | Text | 1,215 | 13 | # Arousal dynamics code base
Code supporting all analyses in the paper ["**Arousal as a universal embedding for spatiotemporal brain dynamics**"](https://www.nature.com/articles/s41586-025-09544-4). Jupyter notebooks for reproducing all paper analyses and figures are available in the notebooks directory.
Data for thes... |
032d61e4fa798efa5bf2666309573c58f69b219bf5c92ca7f5a967f78b1da8cf | Text | 1,219 | 52 | # CAIP 2025 and CBMS 2026 Supplementary Material
This archive contains sources, slurm scripts and pointers to the material for the papers:
**"Enhancing Synthetic CT from CBCT via Multimodal Fusion and End-To-End Registration"**
**Enhancing Synthetic CT from CBCT via Multimodal Fusion: A Study on the Impact of CBCT Q... |
5efb52bd2e3b46cc147aeffe48fc690502eb15bfab6e1e17b6d4a39d6caa3dd4 | Text | 1,225 | 28 | This repository contains the codes necessary to perform equivariant graph neural network models.
* [**equivGNN**](./equivGNN) Catalytic descriptors are crucial to accelerating catalyst design. Here, we develop an equivariant graph neural network to enable
robust structure representations and achieve accurate predictio... |
607b6084c306db91821ae016522073f5d6645ab6d9aa528c0075a0482a4e8c47 | Text | 1,245 | 18 | ## Recurrent issues with DNN models of visual recognition
This repository contains data and code associated with *Maniquet, T., Op de Beeck, H. & Costantino., A. (2025) Recurrent issues with deep neural network models of visual recognition* (see [paper](https://www.nature.com/articles/s41598-025-20245-w)).
### Data
... |
4e18484ea4e90199798f31826c7bc4611ce16d5156c03b9c650de41e0d47a62a | Text | 1,249 | 16 | This folder contains the data and analysis notebooks from the publication:
Title: Feature-dependent decorrelation of sound representations across the auditory pathway
Content:
- Dataset_XX: 4-D (3-D for CC) numpy array containing the data for each of the 4 regions included in the analyses (CC: cochlear model, CN: coc... |
1de9b7675fb4c8bb487478a1c9355614924f10f4ce87200674a905ff173fe265 | Text | 1,253 | 15 | # FlowMat
**FlowMat is a lightweight and user-friendly MATLAB/Simulink toolbox designed for the efficient modeling, simulation, and optimization of flow reactor setups. It uses a modular approach, allowing users to easily reconstruct any real-world setup within MATLAB/Simulink... |
0ac1bfc03d4d10b5f99100f0229a4657cff5b63e755e0b065359352609b74a6f | Text | 1,254 | 18 | # LKM_FED3-tasks
Arduino files for operant learning tasks used in Conn, Milton et al for FED3 devices
This repository contains the task files created to perform assessment of operant learning paradigms in Conn, Milton et al submitted for publication in December 2023.
These are original resources from Lex Kravitz and h... |
c5e4a11fc3c6bb612b3d54ae761a40f0564117500b8392938540c66805f7e770 | Text | 1,257 | 24 | # QuickNII-extras
Code snippets and tools for working with QuickNII output, mostly put around propagation (algorithm is described on [NITRC](https://www.nitrc.org/plugins/mwiki/index.php/quicknii:Propagation)).
* **Python** module for propagation (also CLI app), example .flat decoder (and conversion to .png)
* **JavaSc... |
c3513dec493061e47551b814150cce92f736904b5f949b7b325826604b6653bb | Text | 1,258 | 20 | # Plugins to Phy
These plugins add additional features to Phy
## Features
* Reclustering. Reclustering with KlustaKwik 2.0 - dependent on a local version of KlustaKwik, which is provided in the zip file for Windows 10) and python package: pandas. To install write “pip install pandas” in the terminal in your phy envir... |
09ef37edf86dddaef7d35e9ff16620cae85c1ae6e46356ff03de546a44b6acd3 | Text | 1,279 | 15 | # DeepPHSI
## A general and accurate deep learning-based method for easily identifying Pogostemon cablin categories in hyperspectral data.
The hyperspectral data of Pogostemon cablin contains rich information about Pogostemon cablin but is difficult to analyze. In this study, a method called DeepPHSI was proposed to ad... |
f04a4681e3a02d67e78c28b28cd81b6350a75c9769a77f63bef0976b6df13d4a | Text | 1,301 | 30 | # sc[ai]les
Model architecture and development for Willmes et al., in review: "Identifying escaped farmed salmon from fish scales using deep learning". This deep learning image classifier can distinguish farmed from wild Atlantic salmon using scale images. The model was trained on ~90,000 fish scales from hundreds of r... |
c0429e4f06e94e04afb01aa44cdf1de5c5599e96ba9924c34e2ccb78d40705f7 | Text | 1,320 | 23 | # AECCN
The ISCX-VPN-NonVPN-2016 dataset can be obtained from https://www.unb.ca/cic/datasets/vpn.html.
Both of these datasets are raw traffic datasets in PCAP format.
If you want to verify whether your runtime environment is properly configured, you can directly run the GCNII.py file, which already includes the req... |
8bcdbf70cffc6293e948709bb29934582ebafedc648058d7e46c3853e6fb1d63 | Text | 1,321 | 17 | Contents of this repository:
For each of GB1 and AvGFP...
* md_inputs - files for running MD simulations
- .in Amber input files for minimization, heating, and production simulations
- Initial (pre-minimization) model .inpcrd coordinate and .prmtop topology files
* md_analysis - files relating to extracting featu... |
c8b6b5d70993e08944fd43e69f46208fdbea81a61d60b28cf2ddd9a5e3bd5a86 | Text | 1,324 | 25 | | News | Date |
| ------------- |:-------------:|
| LittleBrain version 1.0.0 release| 08/25/2018 |
| LittleBrain pre-print posted on bioRxiv| 08/26/2018 |
| LittleBrain version 2.0.0 release<br>(added: non-binary maps, gradient values csv output)| 11/21/2018 |
| LittleBrain version 3.0.0 release<br>(a... |
60b66af767229c9004d3b893087c05b08ce55f5a0bb9cfdcc35e47f8a52e399f | Text | 1,325 | 15 | ## Pre-infection cerebral cortex structure predicts murine polymicrobial sepsis outcome
### We use high resolution structural brain MRIs and a murine polymicrobial sepsis LD50 model to demonstrate that pre-infection variability in brain structure can reliably predict infection outcome. Specifically, mice fated to surv... |
a592c8e57b751329f5269a4b604202ae0b82640d4b085638ffb7ff9014e8a54c | Text | 1,330 | 61 | # hcRL
Code and data for the paper:
**"Hippocampus supports multi-task reinforcement learning under partial observability"**
https://www.nature.com/articles/s41467-025-64591-9
---
## 1. System Requirements
- **Operating System**: Tested on Ubuntu 20.04
- **Python version**: Python 3.9
- **Hardware**: GPU (CU... |
0a76e911acd48fd77fdb0372266a3d670096ac984f7384c11856dc0d301b76fe | Text | 1,332 | 62 | # hcRL
Code and data for the paper:
**"Hippocampus facilitates reinforcement learning under partial observability"**
https://www.biorxiv.org/content/10.1101/2023.11.09.565503v4
---
## 1. System Requirements
- **Operating System**: Tested on Ubuntu 20.04
- **Python version**: Python 3.9
- **Hardware**: GPU (C... |
36b927b7714db0bd5c73f4443ebbd3c3f686cc737d3ece7e7f4aebf084067d9b | Text | 1,332 | 30 | # fNIRS-EEG-NFB
## Project overview
This project is an experimental platform designed for simulating and analyzing various machine learning models in different experimental conditions. The platform leverages Python scripts and OpenviBE scenarios for online EEG and fNIRS acquisition, preprocessing and visual NFB. It i... |
4cb6ade08a194ca07e6b0d4a2de4e050ee22f04aaef877d0dbad050b04b43f80 | Text | 1,337 | 50 | # Archetypes
[](https://github.com/aleixalcacer/archetypes/actions/workflows/python-pa... |
a38cb4f978b66a6d0d7600e56f2079b7ac9c50a2a3f75ef914e501cd947ce8bb | Text | 1,337 | 28 | # AllenHumanGeneMNI
[](https://zenodo.org/badge/latestdoi/131175230)
Careful multispectral registration of the Allen Human Brain Gene Samples in MNI ICBM NLIN SYM 09c space
This set of scripts and data is a re-registration of the Allen Human Brain MRIs
http://human.brain... |
7fce4c198f7fa6d1164afd3a5bac246012cd723e3b78bfcc653e18d375fc9d25 | Text | 1,352 | 45 | Title
MATLAB pipeline for auditory brainstem response (ABR) analysis across two rat models of autism
Description
This repository contains MATLAB (R2022b) scripts used to perform statistical analyses and generate figures for the study:
“Sex Differences in Auditory Brainstem Responses of Two Rat Models of Autism: E... |
5d407b4d65e6a16210e02fbccd8a5b5e8fae3895d104b86f25990d4f9a0e9506 | Text | 1,363 | 29 | # DeepMetab
DeepMetab is an end-to-end, integrated metabolic characterization prediction model based on multi-task strategy and multi-scale features. This model provides comprehensive predictions about metabolic enzymes, metabolic sites, and metabolites for specified molecules. The methodology is described in detail in... |
c00607200c68db8a1e14d4fed1f45c3aa2707e81c35f70020c8ec024e6bc66bb | Text | 1,363 | 8 | # outlier
extreme outlier RNA expression
This repository includes the R code and test data for the manuscript "Patterns of extreme outlier RNA expression suggest an edge of chaos effect in transcriptomic networks".
The R script "analyze_outlier.R" identifies outlier genes and correlated over outlier (OO) gene pairs. ... |
540a9b25ffcd69110742ddfb861197b125f02848037a48d49e69ade4cbcb4937 | Text | 1,368 | 52 | This repository contains the code implementations for the paper [Enhanced Prediction of Absorption and Emission Wavelengths of Organic Compounds through Hybrid Graph Neural Network Architectures](https://doi.org/10.26434/chemrxiv-2025-rcwxh)
## Installation
- Clone this repo: Open t... |
664deb888cd6450fc026b45f88aacf8643b0ebba5a87f18900e858694436b071 | Text | 1,371 | 42 | # Spike Sorting Pipeline
Jupyter notebook to analyze and sort spike based on their morphology recorded via microneurography and another notebook to evaluate and create visualization of the results.
## Setup Instructions
1. Clone the repository or download the ZIP file.
2. Navigate to the project directory.
3. Create ... |
ca47d64eeb6f98f215edb1f90ed441ec0e60c620ce091c0cec6bc42e85f29257 | Text | 1,374 | 25 | ## Inferring latent circuit from the neural trajectories of the RNN
This package allows fitting a latent circuit into the trajectories of the original continuous-time recurrent neural network (See [Langdon et. al](https://www.biorxiv.org/content/10.1101/2022.01.23.477431v1) for details). The latent circuit fitting can... |
394a710a116bd111820b450ee7878ae082a257041aaec0aa5b81be063f8dcde3 | Text | 1,376 | 29 | # LH Morais et al. (npj Parkinson's Disease 2025)
Reproducible analyses and figure code for
**“The gut microbiome promotes mitochondrial respiration in the brain of a Parkinson’s disease mouse model.”**
Accepted at *npj Parkinson’s Disease* (DOI: _TBD_)
> **Latest citable snapshot:** see [Release v1.1.0](./release... |
1fcb9f38b3186e7f026094a2e099b3108dc24bd2eefec37b5786403d24d5bc13 | Text | 1,396 | 9 | This repository contains the material related to an immersive VR experiment on cat calling experiences.
The included files describe the subjects' data, their verbal reports, the knowledge graph (catcalling_reports.owl and catcalling-wneur.ttl) extracted from the reports,
jointly with an ontology (the schema from catca... |
1171454e03e34d13f67ff7576390be6c11f2a1ffa660c41857f967fd7f273770 | Text | 1,400 | 39 | # Datasets
This repository contains the datasets used in this research paper:
- paper: [Electric-field driven nuclear dynamics of liquids and solids from a multi-valued machine-learned dipolar model
](https://www.nature.com/articles/s41524-025-01751-x)
- preprint: [arXiv:2502.02413](https://arxiv.org/abs/2502.02413).... |
0f2f4594bca6fcf99b0459add046f1505a1d2ec480a7f3d6b514ab93a47e91c5 | Text | 1,408 | 44 | # Drug3D-Net
A Spatial-temporal Gated Attention Module for Molecular Property Prediction Based on Molecular Geometry. This is the official code implementation of Drug3D-Net paper. But the algorithm has been optimized and improved, which is slightly different from the original version.
<b>Requirements</b> <br>
> Linux ... |
469d558cb5e6da1222ca19d5282ea0df688b08d1f752820e8190e1750c40a6c6 | Text | 1,408 | 26 | # HeartVoice VT / Non-VT Single‑Lead ECG Dataset
**Sampling rate:** 125 Hz **Format:** JSON
Each JSON file contains multiple **records of one specific patient**. A record minimally includes:
- `labels` : status of the segment (`VT` vs. `N_VT`)
- `sample_rate`: sampling rate (Hz), typically `125`
- `user_id`: a rand... |
9f5b4315725b505fb360bc79474c43270b46b562ca69f1bffd0d2715ebedffe7 | Text | 1,413 | 12 | # Deep Learning for Celiac Diagnosis: Recognizing IgA-Class EMA Patterns on Monkey Liver Substrate Through EfficientNet Architectures
This study comprehensively evaluates the performance of the EfficientNet and EfficientNetV2 architectures in binary, three-class and four-class classification
scenarios using immunofluo... |
b50c1801f7280e8cc589f040558d16b48cd4ba78cb2fe4d56ba18b9a3a7e5161 | Text | 1,415 | 30 | ## Running locally
In this directory, type `python3 -m http.server`
In a browser, navigate to `http://localhost:8000/?block=0&pid=1111&sound=1` you must include the arguments otherwise it will error. In this example, you're choosing `pid` = `1111`, `block` = `0`, `sound` = `1`.
`pid` can be any integer.
The option... |
67b0a6195737713d95668c69f9db8c64e8e8fd8ea425f73d33f93fed664d5bf1 | Text | 1,417 | 31 | # Re-analysis of Human Multiple Sclerosis Spatial Datasets
This repository contains the R code used for the analysis of published human multiple sclerosis spatial transcriptomicsd datasets.
Three datasets are included:
1) Lerma-Martin et al. 2024. Predominantly for white matter samples.
2) Alsema et al. 2024. Origin... |
106d3f11741756606adf5da4874208f166f12d3e2eb61e2ff19efe77810221c3 | Text | 1,422 | 73 | Step 0: Environment
set up suitable conda environment (assumes conda installed)
conda create -n torch python=3.10 -y
conda activate torch
conda install pytorch cpuonly -c pytorch -y
conda install numpy -y
conda install pandas -y
conda install scipy -y
pip install mat73
conda install numba -y
conda install scik... |
6bd05ab031a816eb6f81024f6aaf314ba01d3edde48b1b621568f06ac77103bb | Text | 1,443 | 8 | # outlier
extreme outlier gene expression
This repository includes the R code and test data for the manuscript "Patterns of extreme outlier gene expression suggest an edge of chaos effect in transcriptomic networks" (https://genomebiology.biomedcentral.com/articles/10.1186/s13059-025-03709-0).
The R script "analyze_o... |
9faae6b4bfd08e589582d0a6e69f0b91cb7b0529a41a6ee8669b861814b7716d | Text | 1,444 | 25 | # Plugins to Phy1
These plugins add additional features to Phy1
## Features
* Reclustering. Reclustering with KlustaKwik 2.0 - dependent on a local version of KlustaKwik, which is provided in the zip file for Windows 10) and python package: pandas. To install write “pip install pandas” in the terminal in your phy env... |
baf6fafda9457af8f87a2753a450d0c188f3f722b270965843c068963d46c683 | Text | 1,448 | 29 | Copyright (C) 2015 Kevin Allen
This file is part of ktan.
ktan is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
ktan is a C++ program to p... |
ef24cfda8fdc9a05ce095838493e714776939055ed86e06e2c14ac4ee89ce513 | Text | 1,465 | 34 | Python-Microscope
*****************
.. image:: https://github.com/python-microscope/python-microscope.org/raw/master/_static/microscope-logo-96-dpi.png
:align: center
:alt: Python-Microscope logo
Python's ``microscope`` package is a free and open source library for:
* control of local and remote microscope dev... |
b89ce0a930b8dc67d835ba95a7f53e0375283504d145a97dd45f769967cd4da8 | Text | 1,480 | 32 | # ToxMSRC
An innovative peptide toxicity prediction model based on multi-scale convolutional neural network and residual connection
# 1 Description
---
ToxMSRC is a deep learning model for peptide toxicity identification, where the pre-trained model ToxMSRC.h5 can be directly used in the test.py script to eva... |
816bb8bcca1ffb4f4c17d79b59b54d39d8459394cb11fa7e41e73a7e5063e445 | Text | 1,494 | 41 | <!-- markdownlint-disable MD041 MD033 MD013 -->
<picture>
<source media="(prefers-color-scheme: dark)" srcset="docs/assets/brkraw-logo-dark.svg">
<source media="(prefers-color-scheme: light)" srcset="docs/assets/brkraw-logo-light.svg">
<img src="docs/assets/brkraw-logo-light.svg" width="220" alt="BrkRaw logo">
</... |
690c0b84c5d8e4a66456925f20fcddaf2127c074b9ec72b04e37c262e188eb33 | Text | 1,495 | 25 | # gpSMART
A **g**eneral **p**urpose **S**tate **MA**chine **R**unner for **T**raining animal behaviors.
## Introduction
* [Bpod](https://github.com/sanworks/Bpod_StateMachine_Firmware) is an open-source software for real-time behaviour measurement. However, Bpod is running on an expensive hardware pod ($500+) and requ... |
fcd62bdcf82021bd307708f1cbeb5ff084fef616f072af540ebe526bfad3ebda | Text | 1,519 | 16 | # Melanoma_Brain_Metastasis
### Dissecting the treatment-naïve ecosystem of human melanoma brain metastasis
Jana Biermann*, Johannes C. Melms*, Amit Dipak Amin, Yiping Wang, Lindsay A. Caprio, Alcida Karz, Somnath Tagore, Irving Barrera, Miguel A. Ibarra-Arellano, Massimo Andreatta, Benjamin T. Fullerton, Kristjan H. ... |
821f0bf9f1000011d9de20f2b92fbe4e52c2ac0827ebf5813ef3a88b57ad4af4 | Text | 1,522 | 12 | # Scale-dependent brain age with cosmological higher-order statistics from structural magnetic resonance imaging
Data and ML regression codes from the paper A. Carnero Rosell, N. Janssen, A. Maselli, E. Peredad, M. Huertas-Company & F. Kitaura, NeuroImage, 2025, titled: "Scale-dependent brain age with cosmological hig... |
68ca9124ca6203c827796e5cd535d63ad557bd0c54ffbee67b5b7a5c0d36536b | Text | 1,525 | 19 | DeepHisto dataset contains tiles (patches) of hematoxylin and eosin stained Whole Slide Images (WSI) of 28 adult-type diffuse glioma cases collected at the National Center of Pathology (NCP), Luxembourg National Health Laboratory (Laboratoire national de santé - LNS) from 2017 to 2021.
WSIs were acquired with an Inte... |
73a3fc085536f008e1e917549bf35e72e8c8a888d30109aa5a8aaa8ea64d036d | Text | 1,552 | 21 | # Iterate
## Cyclic improvement of molecular inhibitors of alpha-synuclein
The repository contains the code (Python 3.9.7) used to carry out the iterative molecule improvement as applied to docking scores and then to the aggregation data using a Junction Tree Variational Autoencoder https://arxiv.org/abs/1802.04364 t... |
ce0cb60a1c7f12ad4f2042482d374ad294687f1000bf7ce9d91891e851beb27c | Text | 1,554 | 26 | Source code and Jupyter Notebook for testing pre-trained EP-GAN models (small and large HH-model, 64k sample size) with respect to 9 experimental C. elegans neurons considered in the paper.
# Dependencies
NumPy, SciPy, Pandas, PyTorch (CPU version), Matplotlib, ipython, jupyter
# Steps for running the notebook
Step ... |
e2e2b6d77d5443c3b8735b25f081ae6b1a6545c08e9638d6f96f77387dd397ae | Text | 1,554 | 31 | # hbMEP
hbMEP is a Python library for hierarchical Bayesian estimation of motor-evoked potential (MEP) size recruitment curves.
[](https://doi.org/10.1016/j.brs.2025.09.008)
[
We introduce a learning algorithm to discover neural network parameterized yield functions and hardening rules using displacement fields.
## Setup & Examples
Modify the input file `input.yaml` to change the analys... |
a91c87db7aeff0d4dc46b0c32a8d8eafd24e21e8948e8aa3a999240193c5ab94 | Text | 1,561 | 26 | # Memory-Net-Inverse
**_Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems_**
This repository includes the accompanying code for the paper "Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems," which contains a novel generalized deep architecture for solv... |
7e226ab8d574839fece59149dd850314acc5f76b135046226330e140879c9591 | Text | 1,571 | 14 | # Bridging human and animal personality: A new behavioural test to assess reward sensitivity
## Project description
Accounting for individual differences in depression or resilience is crucial to ensure individualised well-being. Differences in tendencies to approach rewards and avoid threats reflect personality, and ... |
0660148233743c102c1e378ba56daf69036f8e3af6b4b04f5e58c84eefdf7950 | Text | 1,575 | 30 | # <p align="center"> Multicenter comparison of sensory evoked fMRI in the rat. </p>
*<p align="center"> How Variable Are Our Rat Sensory-Evoked Functional MRI Datasets? </p>*
## Description
Extending the international collaborative project of Grandjean et al.... |
bbac0794d1ceac13a40c040f235e77db7b08a85d4d52397f9fed7c1b0bc44bea | Text | 1,580 | 30 | # BEHAV3D_TP_DataQC
**BEHAV3D_TP_DataQC** is a Python-based Streamlit application designed for quality control of behavioral tracking data. It allows users to visualize features grouped by experimental conditions and check for potential issues, such as missing values or unexpected patterns, before proceeding with furt... |
df25697173eab542a8d1869f70da73b84e5956bcffe1106be54b131b14620c09 | Text | 1,588 | 33 | # bbb_asl_identifiability
This git repository contains code that was used to generate results for the manuscript:
"On the structural and practical identifiability of BBB-ASL tracer kinetic models."
## Functions that solve the BBB ASL models:
- my_buxton_analytical.m
- my_solve_buxton_numerical.m ... |
320f8efa1f32ac84cbc8b4de4ebfb5dc5f916bb5d0b00d29db99c6d944ffafc5 | Text | 1,595 | 32 | QDPR
==============================
[//]: # (Badges)
<!-- [](https://github.com/Burgin-Lab/qdpr/actions?query=workflow%3ACI) -->
<!--[](https://codecov.io... |
867d69b209098fc180d32d74afcd9c6c3793240fdda231951b21c90f051aa810 | Text | 1,600 | 7 | **Integrative single-cell analysis of neural stem/progenitor cells reveals epigenetically dysregulated interferon response in progressive multiple sclerosis**
B Park*, AM Nicaise*, D Tsitsipatis*, L Pirvan, P Prasad, M Larraz Lopez De Novales, J Whitten, L Culig, J Llewellyn, RB Ionescu, CM Willis, G Krzak, J Fan, S D... |
82b2dd5997250466dd0f429541fad50887d8b9f8e40e429a430f62711cd60528 | Text | 1,605 | 25 | # quantitative_synapse_analysis
multi-channel cluster analysis
These imageJ/FIJI macros identify and quantify the properties of clusters from multi-channel fluorescent images. Macros are intended to be used in an automated fashion to remove user bias. In the laboratory we applied macros to primary neurons that expre... |
bab75b97ca4910984b12d42fc2f41b662878631c294fe2da1995b8cbbe9268b1 | Text | 1,606 | 8 | ## Cell-type-specific DNA methylation dynamics in the prenatal and postnatal human cortex
This repository contains scripts for the following paper.
Alice Franklin, Jonathan P. Davies, Nicholas E Clifton, Georgina E T Blake, Rosemary Bamford, Emma M Walker, Barry Chioza, Martyn Frith, APEX Consortium, Youth-GEMs Conso... |
69bd826da1e20c7f818d01989b3057dc3c986d9f2ee8dcc33b27d2991c5de297 | Text | 1,607 | 17 | # Split-seq toolbox
This is a toolbox for processing raw sequencing output from Split-seq experiments into a digital gene expression matrix that will contain integer counts of the number of transcripts per single cell. It provides a bash script that serves as a wrapper for multiple analysis steps, including demulti... |
6e988f4399069b2e879e6454c04e475a6d4baed434c16a25b6b94e2d7b285d17 | Text | 1,618 | 47 | # GNN-code
## Requirements
This project uses the Python packages listed in `requirements.txt`. Please install them before running experiments.
## Data Preparation (Skip if you already have the data)
1. **Generate MSN Dataset**
Create MSN data such that the variable name is `"connectivity"`, and save it as `cor... |
2d5e7626bf520801173b840a07009c5d292d19ce1473a3fe25cf7dc6c574b1bd | Text | 1,619 | 65 | # Microstate analysis for use with MNE-Python
A small module that works with MNE-Python to perform microstate analysis in EEG
and MEG data.
To learn more about microstate analysis, read the paper:
Pascual-Marqui, R. D., Michel, C. M., & Lehmann, D. (1995). Segmentation of
brain electrical activity into microstates:... |
9d526fe5b17c3c1e9d5c72b9fe9117c689810646a5307c4a6067e8efaf061fa2 | Text | 1,622 | 14 | This repository contains code for simulating the flow-driven adiabatic inversion process underlying pCASL MRI. The scripts in this repository originate from two submissions: Magnetic Resonance in Medicine (MRM) and MethodsX.
MRM submission includes three main functions:
1. "MRM_Main1a_AdiabaticInversion_SingleVelocity... |
35bd30d01f9971ed5969fa4e2a330139212245972aa106535a71bdde91cc740b | Text | 1,623 | 35 | ## Codes and resources for the study "Distinct Spatiotemporal Patterns of White Matter Hyperintensity Progression".
For SuStaIn modeling, we utilized source codes ("SuStaInMatlab-master"; https://github.com/ucl-mig/SuStaInMatlab) developed by Young et al. (https://doi.org/10.1038/s41467-018-05892-0).
For bullseye par... |
f70cd332e1f5aa765424677d54046ec2999e48e4e24e1bba21cce0b56eb319b2 | Text | 1,624 | 5 | The files called 153ProbabilisticROIs_t88_info.txt and 153ProbabilisticROIs_MNI_info.txt contain coordinates (in Talairach and MNI space, respectively) and network information for 153 high-probability ROIs. The first column labels the ROIs in numbered order. The second, third, and fourth columns contain each region's c... |
a59077b94e668f5b7af59af805b048ee6d1dddc5be0b0d5805e8d72103ef3ad5 | Text | 1,625 | 45 | # QuPath_ORF1P
* **Developed for:** Tom
* **Team:** Fuchs
* **Date:** March 2022
* **Software:** QuPath
### Images description
2D images of mouse brain sections taken with the Axioscan
3 channels:
1. *DAPI:* nuclei
2. *Cy3:* ORF1p cells
3. *Cy5:* NeuN cells
### Plugin description
Version 1:
* Detect nuclei... |
de434841d3a0d0291e78cde61fceb84796304ac19fa5cccab88ec26094533331 | Text | 1,626 | 41 | # World Hyper Fuzzy Deep Learning
## WHFDL
#### Article title:
WHFDL: an explainable method based on World Hyper-heuristic and Fuzzy Deep Learning approaches for gastric cancer detection using metabolomics data
-
#### Note:
Note that the values of the interpretability criteria change each time you run and output.
By... |
bb2f39c1c0b8e5d08505fae51d5ff46182754531d574689cffdf85bd2ed96aa5 | Text | 1,627 | 40 | # Hybrid Fuzzy-Weighted 3D FCNN with TSO PSO for Brain Tumor Classification
This repository contains reference code and documentation for the manuscript:
> "Efficient Hybrid Fuzzy Weighted 3D FCNN with TSO PSO Optimization for Accurate Multi Modal MRI Brain Tumor Classification"
## Overview
- **Model**: 3D Fully Con... |
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