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165ed49923d1331f92c208c6898c827424f891529de11fa92113037837471d8b | Text | 817 | 25 | # Code for "Modeling 2D Spatio-Tactile Population Receptive Fields of the Fingertip in Human Primary Somatosensory Cortex"
---
Susanne Stoll, Falk Luesebrink, D. Samuel Schwarzkopf, Hendrik Mattern, Peng Liu, Johanna Noelle, and Esther Kuehn
---
This repository contains
- custom code associated with our manuscrip... |
f1d0ea46dc466ae556794eccbb2ce4425ff250c9b95042efd4676d6665112230 | Text | 817 | 8 | In this study, we intended to determine if SOX2+ cells in PCCs and PGLs can behave as tumour-initiating stem cells. Using expression and transcriptomic studies, we demonstrate the presence of SOX2/SOX2-expressing cells across a broad range of PCCs, PGLs, irrespective of tumour aggressivity, location, and causative muta... |
d49dcc8a580d8af782648bf3432400fc119c6e276051aefde3a674db9561eb0e | Text | 818 | 25 | This git repository contains Supplementary Information to the publication
“Can deep learning algorithms enhance the prediction of solute descriptors for linear solvation energy relationship approaches?”:
- Prediction_solute_descriptors_singletask.py
- Prediction_solute_descriptors_multitask.py
- Dataset_an... |
c6e60eb79ddb147b69189d2b487a27887bb91a62ecda05c3e1fd9bb8c8a39636 | Text | 827 | 22 | Analysis code for Huang et al., "Brain-wide information flow dynamics during novel visual processing in humans".
All analysis code was written in MATLAB R2017b (MathWorks, Natick, MA, USA). All these functions and scripts are divided into various subfolders according to the corresponding figures.
For example, the... |
34b61964118d28441ec87dca11bd41cf0bc77444ea1cd1b20fadc3c61bc0716b | Text | 834 | 16 | # Welcome
Unofficial fork of SOTA lesion segmentation tool **nnUNet model**, developed by Division of Medical Image Computing, German Cancer Research Center (DKFZ). [https://github.com/MIC-DKFZ](https://github.com/MIC-DKFZ)
# Unlearning
This SOTA nnUNet framewok for medical image segmentation is upgraded with **Inte... |
0d3b0f77a44534d05cce0d32a541f412d515acd7e12513952a3fa7435e9ea4db | Text | 835 | 13 | ## NHP_Freesurfer
This repo contains a number of Jupyter Notebooks that will guide you through the segmentation and surface generation of monkey brains using Freesurfer, the NMT template, and other tools.
### Requirements
The requirements are listed in each notebook separately.
### Contact
c.klink@nin.knaw.nl
or open... |
bb4f49fd06a144b946582b5d4f88151c4a6059b377ba5d68604d2bae459dc99c | Text | 837 | 14 | # Machairaki_2025_EV_Organoid_Proteomics
This is the R code for extracellular vesicle (EV) and organoid proteomics data processing, as described in Dr. Vasiliki Machairaki’s 2026 study.
You can explore the data through this shiny interactive page: [https://jtbuuy‐daiyun‐dong.shinyapps.io/organoid_proteomics_batch_cor... |
fb7356acb29d200b1a4783532f45d769d10168d40a21ad879fa6277cc577701b | Text | 840 | 22 | ## Edge Tracking Model
Model associated with:
**A vector-based strategy for olfactory navigation in Drosophila**
**Andrew F. Siliciano, Sun Minni, Chad Morton, Charles K. Dowell, Noelle B. Eghbali, Juliana Y. Rhee, L.F. Abbott and Vanessa Ruta***
*author for correspondence: ruta@rockefeller.edu
### Installation
... |
12e75361851fea1f8637f5e931a6cf41270953223fa549f42f53b9f6054808d3 | Text | 842 | 24 | # RAPIDO Firmware — BLE Wireless Command Protocol
Firmware source code for the RAPIDO wireless optofluidic
neuromodulation system, as described in:
> [Eun Young Jeong†, Jong Woo Park†, Sungwoo Cho, Donggi Han, Choong Yeon Kim, Sung Woo Kim, Wonhee Lee, Wha Young Kim*, Jeong-Hoon Kim*, Jae-Woong Jeong*].
> IoT-enabl... |
1d495406327c45246f2938e6dbd3102cd436897201cf430426ddc04b95f32368 | Text | 845 | 17 | 1) subjectID: participant ID
2) trial_idx: number of trial in each block (1:60).
3) EEG: epoched EEG data respect to saccadic onset (time 0) before ICA.
4) block: block number.
5) sessionIdx: session number (participants’ would do 1-3 sessions across different days).
6) uniqueID: unique participant identification ... |
ead07fdd743486d5d258e76b76806477463df125a8feab4d221de026ce7fcb7e | Text | 851 | 36 | [](https://github.com/achiefa/DeepLearningTheory/actions/workflows/test_pip.yaml)
[](https://codecov.io/gh/achiefa/Deep... |
f372f5ca9638ce795c1c7dca35583325b655919e441702cc722c3dad4e0ced23 | Text | 852 | 38 | # ModelistsGCN: A Multimodal Graph Convolutional Network Framework for Single-Cell Spatial Transcriptomic Cell Typing
---
Noa Konforti, Tal Goldberg*, Michal Danino*, Shahar Alon
---
---
## Overview
ModelistsGCN is a semi-supervised graph neural network for clustering c... |
ffcb8ec931bf1136ecbc37e162df1701008f7098e0037b71f729771c8abff54d | Text | 858 | 21 | # SenseOrPass - Proteomic Cancer Classifier
This project implements a deep learning classifier trained on proteomic biomarker data filtered by a predefined protein list. It includes model evaluation using ROC/AUC and SHAP interpretability.
## 📂 Structure
- `Scripts/` – Jupyter notebook with complete pipeline
- `Dat... |
bd4d67a286711ac0e6e3556822aac89eda9138e208fe03bfa70cf25dd0e882ac | Text | 863 | 18 | # Liquid State Machine (LSM)
The Liquid State Machine (LSM) ([Maass et. al. 2002][1]) is a computational model
which uses the high-dimensional, complex dynamics of recurrent neural circuits to
conduct memory-dependent readout operations on continuous input streams.
[1]: http://dx.doi.org/10.1162/089976602760407955
T... |
0d063dd09b6fe5065cd5d4dc7ae25c362e9917f707f551a596c29a88aa99fec0 | Text | 866 | 9 | Here is the file to reproduce the results of our analysis of three Vanilla RNNs via Spectral-Submanifold (SSM) model reduction:
- The "Context Dependent Decision-Making RNN" of Mante et al. (2013): the SSM reduction and analysis is in "cddm demo.ipynb", the SSM-reduction of the noisy network is in "cddm_demo_noisy.ipyn... |
0affc5a2a89d4dc9a8305b22866829a00b73a3683b8a1a68129cd7800cfc3dc3 | Text | 867 | 14 | # VERA
***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 to make localization as accurate and seamless as possible. Unfortunately, a lot of these methods... |
48e68de1c8bc85e3480f7de54d9fe0599c2bf8087271bc89ea6eb64727f37304 | Text | 877 | 12 | # ALDH7A1
This is a repository for the following publication:
Travis E. Faust, Atsushi Saito, Shoichi Ishikawa, Kun Yang, Wendy Xin, Ho Namkung, Amit Agarwal, Adriana Ramos, Brian J. Lee, Lindsay Hayes, Rupali Srivastava, Sunday Adelakun, Sneha Saha, Trexy Palen, Tyler Cash-Padgett, Daniel J. Wood, Elisa Carloni, Ryos... |
8b7b81b5b57f9268d8fe3810b018c8d6dca2e6949b9e5cf8226722848ae7cad2 | Text | 889 | 8 | # Automated-EEG-Algorithm
This repository contains the automatic and manual versions of an automated EEG algorithm developed in Matlab for detection and quantification of interictal spikes and convulsive seizures.
Automatic Code - this Matlab file is used to rapidly process EDF files containing EEG data without genera... |
053e7d4dc9d89b191abf3ebb0e604ba22ba2eaf9ea4acf41771fbf0f8c1783fa | Text | 894 | 25 |
# CriticalWindow-24 (CW-24) Benchmark
A comprehensive benchmark for 24-hour ICU mortality prediction using eICU and MIMIC-IV datasets.
## 🎯 Overview
CW-24 provides standardized benchmarks for predicting hospital mortality within 24 hours of ICU admission, ensuring strict temporal constraints and preventing data le... |
55c4b4d9a15025d37803cc96648f2b383f4e078be70f443cd8e86df37cb83fb7 | Text | 897 | 18 | This directory contains MATLAB scripts for modeling gastric motility and gut-brain axis interactions. Below is a description of each file:
--------------------------------------------------
1. compartment_gut_brain_axis.m
- Models the vagal region of the gut-brain axis influence on gastric motility and gastric ... |
e850bea408a9d0c34fcfa13caf097f24ea869e848063d89ace9bd52f8d4b1491 | Text | 901 | 29 | 
# Pyecog2
Under construction.
PyEcog2 is a python software package aimed at exploring, visualizing and analysing (video) EEG telemetry data
## Installation instructions
For alpha testing:
- clone the repository to ... |
3fee009279384d1180084a24991736a9ccb658ef62e52963cecbe1d494c92af3 | Text | 904 | 13 | # Concept2Brain
The present repository presents the scripts for training the deep learning models underlying the Concept2Brain model and testing its performance with image and text inputs.
## Give it a go
Clone this repository onto your local development machine:
- `git clone https://github.com/codeforgermany/click_that_hood.git`
- `cd click_that_hood`
Install dependencies:
- `npm i`
Build the `data.js` file:
- `npm run build`
The resulting... |
b6a042915323492d84390d5a766ce82d9cca568eb059bcc357a284793064332f | Text | 922 | 29 | # Graphene-seq
Code and source data used for graphene-based optically clear in situ sequencing
and electrophysiology analyses.
## Repository Layout
- `notebooks/`: Figure and supplementary figure notebooks.
- `src/graphene_electro_seq_analysis/`: Analysis utilities used by notebooks.
- `SourceData/`: Preprocessed da... |
66751d89c2b6e7e4732b3e3bc3b534a86696a1529da18c8b9b5c0148ac6e68ff | Text | 923 | 24 | # REPeatedOPtogeneticStimulation
Analysis code and processed data for Murano et al bioRxiv 2015 "Repetitive Neuronal Activation Regulates Cellular Maturation State via Nuclear Reprogramming"
## Overview
This repository contains analysis code and processed data for:
Murano et al., bioRxiv (2015)
"Repetitive Neuronal... |
eb6a731ac8d0bc46004eab69b3aaaa05c7216398e6dde740d1f4feb785945bca | Text | 926 | 20 | [![CC BY 4.0][cc-by-shield]][cc-by]
[](https://zenodo.org/badge/latestdoi/306986751)
# Bold Response Delays Represent Local Cortical Processing
__Analysis Code to Reproduce Figures__, by Sébastien Proulx
Manuscript by Sébastien Proulx and Reza Farivar accepted for publ... |
446c8baf63de6dc4edfee4ea270cf9fa36441173d9bdfdd8d0a2c93f25076570 | Text | 930 | 17 | # DynamicACh
Code associated with the manuscript "Dynamic cholinergic signaling differentially desynchronizes cortical microcircuits dependent on modulation rate and network topology."
The repository contains Python 3 code to generate each of the figures in the paper. Aside from using basic Python libraries
such as ... |
9822d52cc824171d1ffb392f8ad086b9f73d235242c29b6eeac9e4a985f2d023 | Text | 938 | 20 | # paz-analysis
## Summary <br>
imageJ macros designed to analyze the abundance and distribution of proteins in the periactive zone of Drosophila neuromuscular junctions.
This may be generally useful to analyze the architecture and distribution of any biomolecules that form a reticular structure.
## Author <br>
Steve... |
20fdfd90fc691637d18eec28582cf14209a954086a134cf82e96a2a4529f7c3a | Text | 948 | 24 | # DCM Parcellation
This is a demo for parcellation of a dynamic causal model of the brain, based on the attention-to-visual-motion dataset.
Run DEMO codes in the Code folder. DCMs are included in the Data folder.
DEMO1 should take less than 10 minutes to run, DEMO2 less than 5 minutes. Plots will be saved in Results... |
f4f71f10e58cc446a3f3d3c5f5a8e3ec311f747fc16691f3f4e7bc8e2cabdf38 | Text | 960 | 13 | # Code supporting the release of a dataset of EEG/ECG recordings from 1000 infants, children and adolescents.
This repository includes code that supports the public release of the Helsinki 1000 EEG/ECG dataset. This dataset can be found on Zenodo -
* anonymize_dataset_for_github.m - outlines the procedure used to ano... |
03bc5871f19c914b25f068569a8b2e4fd3902d808482a1d773acc716214627a4 | Text | 967 | 20 | ## AlphaFold3 Modeling And Analysis Scripts
This directory contains all generated AlphaFold3 (AF3) models and relevant confidence metrics outputs.
Two independent AF3 modeling conditions were tested:
1. **NBCn2 monomer, two sodium ions, one carbonate ion, and three water molecules
2. **NBCn2 monomer, two... |
4f9dcaa4932b1f4d881f1716591736f64d6d2f6fc4a256f27d069ca9602d9cd3 | Text | 967 | 9 | # Combining Sampling Methods with Attractor Dynamics in Spiking Models of Head-Direction Systems
Code supporting paper "Combining Sampling Methods with Attractor Dynamics in Spiking Models of Head-Direction Systems" by Vojko Pjanovic, Jacob Zavatone-Veth, Paul Masset, Sander Keemink & Michele Nardin.
Code written by Vo... |
c5a1a449991a83c8df84c752745a7a8e17ce99224755e907a98768790a9e9f90 | Text | 967 | 16 | # A Novel Blood-Based Epigenetic Clock for Intrinsic Capacity Predicts Mortality and is Associated with Clinical, Immunological and Lifestyle Factors
**Link to the paper:** TBD
## Repository Structure
- **code/**
This folder contains the R scripts used to replicate the four figures presented in the study. Most o... |
e70554b297025e7b7fe786161c0ffe4a916cf30433ea06a11123087c1f73a127 | Text | 969 | 22 | # Aery Jones et al, 2025
Python code used to generate "Entorhinal cortex represents task-relevant remote locations independent of CA1"
Preprint: https://www.biorxiv.org/content/10.1101/2024.07.23.604815v1.full
### How to install (in Conda)
1. Clone this repo
2. `cd` to the top level directory
3.
```bash
$ conda crea... |
9c6f77c5ed25b9b247642c8e90f57babd87fd6b6c8f8a9e12701097ef73dcde9 | Text | 970 | 43 | # NSIBF
### Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering
Cheng Feng and Pengwei Tian. 2021. Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering. In Proceedings of the 27th ACM SIGKDD Conf... |
193d2d11a97e27c5138db563ca8036d9b51854af796ae7a68d715ad5d3af7952 | Text | 980 | 20 | # Scripts and resources supporting the paper "Exploring the Link Between Body Physiology and Cognition: The Role of the Brain and Aging"
## Article Reference
- **Title:** Exploring the Link Between Body Physiology and Cognition: The Role of the Brain and Aging
- **Authors:** Irina Buianova, Narun Pat
- **Year:** 2026
... |
98de651b02ddc602dafdfd98d383f4ae0fda6105d86e6b7213d1d78ceac45b34 | Text | 980 | 21 | These scripts were used to analyze data for the pinprick assay in Figures 2E, S4A and S4B of the manuscript titled "Targeting Gi/o-coupled GPCRs to inhibit nociceptors: insights from the serotonin receptor Htr1b and triptans."
Requirements
MATLAB (developed and tested in R2018b)
No additional toolboxes required
A... |
c5010fd2d33efa6d8d16bb9488e0347d6f2fcc6dc7645654eaa50573f2bb223b | Text | 980 | 12 | # HCP-dMRI-connectome
MRtrix scripts to generate dense weighted structural connectomes from the Human Connectome Project "minimally pre-processed" diffusion MRI data
If utilised in your publication, please cite:
Civier, O., Smith, R. E., Yeh, C. H., Connelly, A., & Calamante, F. (2019). Is removal of weak connections... |
d80ba7fbc19ae8a3e9f29a3041c1452d9814f3be985f2abda235126d65c36d85 | Text | 984 | 24 | # Newborn_TREC
**Title**: Thymic output in human newborns is shaped by environmental exposures and a common TCRD genetic variant
## Description
This repository contains scripts and data needed to reproduce the figures in the paper [*Thymic output in human newborns is shaped by environmental exposures and a common TCRD... |
a8b4096f6b7139db4b4c5eb84ef8f36c5da6e06e402e97b26e621f0ed3102a8d | Text | 985 | 22 | Identification of moderate effect size genes in autism spectrum disorder through a novel gene pairing approach
Author: Madison Caballero
Preprint: https://doi.org/10.1101/2024.04.03.24305278
Folder descriptions:
1_MES_screen: Code and files related to the initial screen of MES genes (Figure 2 Steps 1-4). Individual-le... |
eb249a23f7bde378fe85ed41ac1c3fff2c12ce5caa9922d4823ed76d9cdb3959 | Text | 986 | 22 | # README — Data and Figure Reproducibility
## Overview
This directory contains analysis scripts, serialized numerical results,
plotting code, and exported source data used to generate the figures
reported in the manuscript.
## Directory Structure
- `analysisCode/`: scripts documenting the analytical procedures used
-... |
9bcdb017754451af44d52b680158f8bdd5a12d0198daf1ac8a5ea3a7627006f0 | Text | 988 | 12 | Code for "Sensorimotor transformation of number in the primate parietal cortex"
This code pack requires the use of MATLAB version 2021a or newer.
Please make sure files are in MATLAB path.
"visualization_behavior" creates Figure 2 of the manuscript and is used to plot behavioral performance functions.
"visua... |
06a7b8b2e83b913a1e31fb20024c0206395b6897d88d81078c1da50abf0c80c7 | Text | 992 | 15 | # SAAV Decoding
This repository contains all the elements of decoding SAAV's post reversal turn signal.
[DecodingMain.ipynb](https://github.com/flavell-lab/SAAV_Decoding/blob/main/DecodingMain.ipynb): a Jupyter Notebook that can be run through to completion to recreate all results.
[kfold.py](https://github.com/flav... |
d4aefd5b38e6ca1b3ebd0e2a3e8ae075fe59dc907cc217d31e181e95fb747302 | Text | 995 | 5 | This repository holds the data and source code for the following manuscript:
[Corridon TL, O'Moore J, Seerley A, Sprague DA, Lian Y, Laversenne V, Noble B, Kamath NG, Serack FE, Shaikh AB, Erickson B, Braun C, DeSouza-Lenz K, Howard M, Chan N, Jackson WS, Reidenbach AG, Cabin DE, Vallabh SM, Grindeland Panter A, Oberb... |
666e8a0921edcb68a684e805d6564b53007ab3720bebb120b21224de37afde08 | Text | 1,000 | 12 | ## Emergence of multifrequency activity in a laminar neural mass model
Welcome!
The material you will find here provides the main tools to reproduce the results shown in in the paper: [Aristides et al. , *Emergence of multifrequency activity in a laminar neural mass model* (2025)](https://doi.org/10.1101/2025.06.16.6... |
4a21caf68cf6575b7e938649a296421a8ab687e3eecbbc5573b17126b9974457 | Text | 1,010 | 9 | # ADRD-Neuropathology-Scripts
Misc scripts associated with a genomics study of AD/RD neuropathology:
Cholerton B, Godrich D, Pasteris J, Rivero J, Martin ER, Kunkle BW, et al. (2026) Genome wide association study meta-analysis of neuropathologic lesions of Alzheimer’s disease and related dementias in a multi-site auto... |
b2553495a5b10ae1678e326ba4a95aca6258dd5daf0bd44f35d8340fb5d748b5 | Text | 1,021 | 37 | Manifold Topological Deep Learning (MTDL)
====
This manual is for the code implementation of paper "Manifold Topological Deep Learning for Biomedical Data"
****
# Prerequisites
- numpy 1.26.4
- h5py 3.11.0
- medmnist 3.0.2
- scipy 1.11.4
- python 3.11.7
- pytorch 2.4.1
- pytorch-cuda 11.8
# MTDL model arc... |
47f825e165bbc3a8c9dbfee99fd47d42dd04151a1934a9f0816156df6e82a63a | Text | 1,026 | 47 | # NetworkBrainAge
A deep learning toolkit for predicting **brain age** from T1-weighted MRI scans using a Simple Fully Convolutional Network (SFCN) and network-wise analysis.
---
## Requirements
- Python 3.6+
- TensorFlow 2.x (with Keras)
- NumPy
- Pandas
- scikit-learn
- nibabel
- SciPy
- Matplotlib ... |
43025da751d2618e9d42620e37eb93687a6213c28d3000bd6426ca63484c3aea | Text | 1,034 | 37 | # gucompaper: Naturalistic behavior and self-generated neural activity predictive of self-correction
Analysis code accompanying the Gu et al. change-of-mind paper.
The code was previously developed inside the [Spyglass](https://github.com/LorenFrankLab/spyglass)
framework under `spyglass.shijiegu` and has been extrac... |
6d06b01d89d1da44563e7f0f75e641a9152f2e59dc3c07bc78c0289fe6ae89a4 | Text | 1,034 | 27 |
<!-- README.md is generated from README.Rmd. Please edit that file -->
# SpNeigh
SpNeigh provides methods for neighborhood-aware analysis of spatial
transcriptomics data. It supports boundary detection, spatial weighting
(centroid- and boundary-based), spatially informed differential
expression using spline-based mo... |
eeb9bd8b6ebd58379f36368d463a2a2a6e06051353700373a3b75fb266dc7160 | Text | 1,046 | 22 | # GLM utilities
Tools for fitting Generalized Linear Models (GLMs) with time dependence (a.k.a. filters).
Features:
- Time delay embedding ([basics demo](demo/basics.ipynb)).
- Basis functions ([bases demo](demo/basis_functions.ipynb)).
- Follows [scikit-learn's](https://scikit-learn.org/) API conventions. Can be use... |
8de19c07ec65242bd579b6d772c87406cfb09b85a355b260a415195c2e5d1390 | Text | 1,054 | 11 | # automated_synapse_analysis
multi-channel cluster analysis
This Python code is used to identify and quantify the properties of clusters from multi-channel fluorescent images. Code is intended to be used in an automated fashion to remove user bias. In the laboratory we applied code to primary neurons that express low... |
c1a3166f7706d26eed4ec6a83ea114a81f43502ce3c2d06f2e020836cc2a8c2b | Text | 1,057 | 46 | # ModelistsGCN: A Multimodal Graph Convolutional Network Framework for Single-Cell Spatial Transcriptomic Cell Typing
---
Noa Konforti, Tal Goldberg*, Michal Danino*, Shahar Alon
---
---
## Overview
ModelistsGCN is a semi-supervised graph neural network for clustering c... |
5d5cc838f5f4ef25b953527d6a80bb0412e0d1ce673cb05da3227836c3fb201f | Text | 1,074 | 21 | # ldsc project
Singularity wrapper for https://github.com/bulik/ldsc .
To get started, see [docs/ldsc_real.md](docs/ldsc_real.md) example.
## Important! - Set up Git LFS
Have a look [here](https://github.com/comorment/containers/blob/main/README.md#getting-started) if you're new to git or Git LFS.
## Build status... |
ad20b7bbd4e266932478753239276ec43d38204c39b01b87513e13e29445cb74 | Text | 1,074 | 35 | # Getting Started with GWAS Normalisation
__version__: `0.4.3b1`
The gwas-norm package is a toolkit to normalise GWAS summary statistics flat files. It aims to handle some of the most common scenarios and produce a flat file with:
1. A standardised column order
2. Uniform genome assembly
3. Indel noramlisation, vari... |
bc62053563e1be1702e150f6cf65e9db2a7a4415e4d34e27eea80a1611850678 | Text | 1,074 | 12 | # Neural Quantum Embedding
This is a code for [Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning](https://arxiv.org/pdf/2311.11412).
1. *data.py*: Loads datasets. MNIST, Fashion-MNIST, and KMNIST data are used with various feature reduction methods.
2. *embedding.py*: Includes code for *ZZ f... |
3ec27b04f3bb0f8a36dacc46b93c9b874eb589af35dd0386b0ec6928a640ea42 | Text | 1,077 | 22 | # NeuroMArVL #
Developed by:
[Tim Dwyer](http://marvl.infotech.monash.edu/~dwyer), Alex Fornito
Thanh Nhan Pham, Mingzheng Shi, Nicholas Smith and James Manley
Monash University, 2015-2017
## Features: ##
### Sharing ###
Allow neuroscientist to quickly share their visualisations on their own dataset with other scie... |
89bb6ba730bd6c02c10ec6108c10c17ca0c314e927f66838f26f9c6df095ec67 | Text | 1,078 | 16 | # DiffTasks
Resources for the paper [**The language network responds robustly to sentences across tasks**](https://direct.mit.edu/imag/article/doi/10.1162/IMAG.a.1283/137022/The-language-network-responds-robustly-to) by *Ruimin Gao, Chandler Cheung, Matthew Siegelman, Alvincé L. A. Pongos, Hope H. Kean, Alyx Tanner, Ev... |
4b0f00bae7206504c6c1bf05b6ae6fd18426254e019cf187fc6f051b030c36a4 | Text | 1,081 | 54 | 
# MMFF94 in PyTorch
This repository provides a PyTorch implementation of the MMFF94 force field.
It allows molecular energy minimization both in isolation and conditioned on a protein pocket.
## Features
- PyTorch-based implementation of M... |
a77b553ca26e8ad0a3b2f3dd0ab0542f277eab6ea32674805b7dda86d383b515 | Text | 1,081 | 9 | # Acquired genetic and cell state changes in IDH-mutant glioma progression
## Overview
The Cellular Analysis of Resistance and Evolution (CARE) consortium used bulk and single-nucleus sequencing approaches to study IDH-mutant glioma evolution. This repository contains scripts for analyzing single-nucleus RNA and ATAC ... |
3b4065103d98fcae3ae134249313502c780ef8d10196ffcfaf459a788e5f8c27 | Text | 1,082 | 33 | # geno-bicluster
**Fast biclustering of PLINK SNP–SNP interaction matrices ( *.epi.qt* )**
`geno-bicluster` pinpoints rectangular “hot-spot” regions in a chromosome-by-chromosome
interaction matrix whose density of significant epistatic hits is unlikely under a
hypergeometric null. The implementation is Numba-accele... |
73a8e457f8b3d81cabd4240f376d79aeda2f60c2e69284a56fcdbba814c6e37c | Text | 1,084 | 18 | # MidgutLineageDiversity
Important codes and data for "Longitudinal lineage tracing reveals early clonal attrition during *Drosophila* midgut aging".
## code
The calculation process of obtaining effective population size and clonal diversity in midgut.
## data
Files with **annotation** in the filename are the annotat... |
8a4b190dd4b923bd556d1dd116d1d8c28005026a66ede23120a88329c59ec1c2 | Text | 1,086 | 28 | # Experiment and Analysis Code for:
# Hierarchical brain dynamics supporting visual perceptual transitions
## Levinson et al., 2026, Science Advances
## Paradigm
**Flicker localizer** run from UI_retinotopy.m
**Main task** run from UI_master.m
**Resting state** run from UI_rest.m
## For analysis, set local p... |
00c4c5c70acb736bda6d69d4ee0a6955b651b17d481a7018022d001fadf43a35 | Text | 1,096 | 41 | Processed ground truth patches (PNG)
The folder processed_patches_512 contains ground truth patches used for training.
Each sample patch has:
Size: 512 by 512 pixels
Channels: 4
Channel order: C0 DAPI, C1 F actin, C2 Vimentin, C3 Lamin A
Raw ND2 data
Location: raw_nd2
The raw data are Nikon ND2 file... |
b5d66a715acb1fa92b147a3c0ddafa9c062e35f448196499e92c199266eb3981 | Text | 1,098 | 22 | # GENI plots <img src="man/figures/logo.png" align="right" height="139"/>
The GENI plots R package is designed to create a series of plots for visualising results from genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS).
## Installation
```
install.packages("remotes")
remotes::insta... |
224601e7a37b927b1007646faeec5f99988a00b3ba20a26f3cacc402678fbb21 | Text | 1,107 | 27 | # Towards real-time additive-free dopamine detection at $10^{-8}$ mM with hardware accelerated platform integrated on camera
This repository contains the implementation, data processing pipelines, and optical accelerator models described in our work on ultra-sensitive dopamine (DA) detection.
By integrating engineer... |
74c875cd11eac3e238ba984fad1f54fe2c4cb34f790f650e447da23b9369dae9 | Text | 1,109 | 48 | # simpl5pn_temperature_modulation
* a 4 compartment (soma-AIS, basal, proximal apical, distal apical) simplified l5 pn biophysical model with temperature sensitivity in ion channels
### Python environment Requirement ###
* python 3.7
* numpy
* scipy
* matplotlib
### Files ###
* \func: functions
* Na_channel_test.py:... |
cb8828372c4dc49dfccbe359511bca814048e1811d0ecd4c99e8c9cef1398730 | Text | 1,109 | 27 | # JuiceMe
Hi-Culfite Processing Pipeline
JuiceMe is heavily based on the <a href="https://github.com/aidenlab/juicer">Juicer</a> pipeline.
Please review the <a href="https://github.com/aidenlab/juicer/wiki">Juicer documentation</a> first
to understand how the JuiceMe pipeline works.
# Dependencies
In addition to the ... |
8a9f5ffa4f6a6cb6a265d1debb41fee7924b242b2c9120a25ab1a0a0f9c1f1fe | Text | 1,133 | 10 | ## Project description
This project contains the preregistration, data and analyses scripts for the paper "The functional neurobiology of dispositions towards negative emotions". An earlier preprint version can be found on biorxiv: https://doi.org/10.1101/2025.05.15.653674
The Patterns predicting vulnerability to str... |
1970fbad01ee0a7eafe6956665fe448379143a29305e31f38aaa7515ef3eb1ce | Text | 1,134 | 11 | # SignalBuilder
The simulation of temporal signals is crucial in fields such as deep learning and signal processing, where access to real data is
often limited due to ethical, economic, or privacy concerns. This study presents a method for generating synthetic data by
creating frequency reference points within control... |
fc465d28be6c190930c80dcd67bd1b2faff502e9086a084d59a9191e12c4b51e | Text | 1,135 | 17 | # BRET-Analyzer
BRET-Analyzer is a toolset for Fiji allowing systematic analysis of bioluminescence resonance energy transfert images. Its description can be found in [(Chastagnier et al. 2018)](https://www.frontiersin.org/articles/10.3389/fncom.2017.00118/full).
It has been since improved as a plugin, with more func... |
3d6e5211e86e1d5f2be575122ae8b7b70a390431688be82dc2972ef2ec2e6a4f | Text | 1,152 | 35 | # Single-Cell MR Discovery, Replication, and Colocalization Pipeline
This repository contains an end-to-end R pipeline for integrating single-cell eQTL data with GWAS summary statistics to perform:
1. **Discovery Mendelian Randomization (MR)**
2. **Replication MR**
3. **Colocalization Analysis**
as applied to 14... |
875f8ef53767e8ca1f0acaef83a5af30b4b4236f9ececb915116f7d03401127c | Text | 1,159 | 10 | # IgLON5 Autoimmune Antibody Influence On Neurons
To study the effects of IgLON5 AABs on neurons and Tau, polyclonal pools of IgLON5 AABs from the plasma of four anti-IgLON5 disease patients were isolated. As controls IgG pools derived from healthy subject serum were additionally collected.
The IgLON5 AABs wrer delive... |
512dd2e96efc004886b7c98a5a63d9b2765f2f3e56b753038d31e69be0d8b115 | Text | 1,161 | 26 | Analysis for
["The effect of experimental placebo interventions on cerebral pain signature activity – a meta-analysis”](https://osf.io/n9mb3/)
by Authors: Matthias Zunhammer1*, Tor Wager2, Ulrike Bingel1
on behalf of the Placebo Imaging Consortium
Affiliations:
1 Department of Neurology, University Hospital Essen, Huf... |
104bd06f3c866b1f394c1e3d6c6ab5e9827f253ea85d7b9a9f1d4cd984bfd0d3 | Text | 1,162 | 42 | # Large-scale synthetic data enable digital twins of human excitable cells
Usage Instructions
Step 1: Generate Data
Use createData.py to generate synthetic dataset, (line 50: number of cells)
Run the data generation script: bash runall.sh for step 1 & step 2
OR run them separately using GCC (or clang) and python (s... |
07b2058b632045451833a689e430d079a8d343f63442b5938ebafa9be3eb62df | Text | 1,163 | 29 | Neighborhood Opportunity, Cognitive Outcomes, and White Matter Microstructure: Insights from a Large Pediatric Study
Overview
This repository includes scripts for the data processing and analysis performed in the study titled “Neighborhood Opportunity, Cognitive Outcomes, and White Matter Microstructure: Insights fr... |
82cd8fb1b3257f24c256c02894e8196e72d7358a5b3746da1a2b20e95aa0d335 | Text | 1,165 | 6 | # Mathesonetal2022
This repository contains the code used to analyze the data in A neural circuit for wind-guided olfactory navigation, by Andrew M.M. Matheson, Aaron J. Lanz, Ashley M. Medina, Al M. Licata, Timothy A. Currier, Mubarak H. Syed, and Katherine I. Nagel.
To run code to analyze the data found at this pa... |
b34d73c8afb33e86c51b0d85a24ec062e080bd4d783c913ad7f8ccf3db768229 | Text | 1,180 | 43 | # Introduction
The scripts for analysis of **"Genomic sequence evolution underlying human neocortical interareal diversification"**.
## 01. Clustering
Clustering analysis including preprocessing and subtype identification by Seurat.
## 02. DEG
Identification of area-specific DEGs at the subclass level.
## 03. Int... |
d6cd7a353e1b2c2559ff4fdb4244e21c179215c6f56181af8859b48945f78ac6 | Text | 1,195 | 11 | # brainblenda
python tools for visualising neurons in Blender. Liases with Snudda (https://github.com/wstho/Snudda) to visualise neural simulations in 3D.
[](https://github.com/psf/black)
## Contact details
W. S. Thompson, Karolinska Inst... |
d97ab43bcd40110d932e7150974619e25add4e9d4c7ea763f32364761f9256ab | Text | 1,201 | 34 | # TadPose: post-SLEAP analysis for tadpoles, frogs and other animals
---
A Python library for post-analysis of SLEAP* pose estimation. TadPose was developed with the Sweeney and Novarino lab at ISTA (Austria). To use TadPose, the original movie and SLEAP .h5 analysis file is required.
## Features
* Alignment of anim... |
724a6fc46b7d6b34d898e2609b3d1bd61fd384317c78b46ad956526519f08837 | Text | 1,203 | 13 | # abcd-ela
R Markdown files for creating measures of early life adversity in ABCD Data Release 5.1.
You will need to run ELAfromABCD_setup.Rmd prior to running any of the code to create scores. The setup code will create csv and rds files needed for the score calculations.
Three scores are available:
1) ELAfromABCD_... |
87eb4ce73a75e4e12d21da6729bef8163c509c0c09f8e0241c5bdfda9fa7717f | Text | 1,214 | 19 | # Semantic Mnemonic Similarity Task (sMST) - Analysis pipeline
The featquery extracted fMRI data and the preprocessed behavioural data merged and analyzed in this pipeline.
Preprocessed data is uploaded to OpenNeuro, at: https://openneuro.org/datasets/ds007275
Experimental scripts available at: https://github.com/Ilye... |
48f5332163a14afaf0b53847ed773a2ea5626ae5d93d2d5ed06ed00a43ce989b | Text | 1,215 | 27 | # Neurotransmitter Prediction from Electron Microscopy Images in BANC
[](https://zenodo.org/badge/latestdoi/1028540389)
[](https://www.gnu.org/licenses/gpl-3.0)
This repository is based off previous w... |
ee856703e6238ba34993f318cdfeb629609b0e6a19b6888ed70f23fda8fe4b19 | Text | 1,230 | 17 | CSDplotter
----------
This repository contains version 0.1.1 of the CSDplotter tool implementing the inverse current-source density methods described in
Klas H. Pettersen, Anna Devor, Istvan Ulbert, Anders M. Dale, Gaute T. Einevoll, Current-source density estimation based on inversion of electrostatic forward soluti... |
a987a95e7dacb7ca4076421b541d85b8f405e59438867e1c325ac00d0a8d90c4 | Text | 1,241 | 32 | # AttMAMLToxIL
Few-shot Prediction of Toxicity of Ionic Liquids Supported by Att-MAML: Attentive Model-Agnostic Meta-Learning
Corresponding author: Karol Baran (GdańskTech), karol.baran[at]pg.edu.pl
Manuscript status: submitted (2026)
## Files and folders:
- data - directory with information on data and scripts t... |
9b24c33d75b7830a8358d22a16acd185d56ed0f97c83092cf05b4fe60cf5eb34 | Text | 1,244 | 31 | # NeuralBreathing
MATLAB code for analyzing forebrain neural synchronization with breathing using intracranial EEG (Mowla et al., Nature Communications, 2026)
# NeuralBreathing
MATLAB code for analyzing forebrain neural synchronization and entrainment to breathing during wakefulness, sleep, and external mechanical ve... |
4893be3b477116af91fb8ca7d698151586174f99f55fcc903fac9fa29c7bee19 | Text | 1,254 | 28 | # Larval sleep quantification code
This repository contains custom code used to quantify larval sleep in Drosophila.
## Related manuscript
Neuropeptidergic circuit modulation of developmental sleep in Drosophila
## Contents
- `videoanalyzer_single_loop_ROI_F_binary-thresh_AppliedPC_8.py`
Calculates fram... |
28bc09d9e79e85baa615f88bc4c2d21c0e5047129864c96a1586c5eb842cb62d | Text | 1,259 | 38 | ## Introduction
This repository contains the implementation of the DeepDOX1 model for predicting protein-ligand binding affinities. The model leverages deep learning techniques to analyze molecular structures and predict their interactions.
## Requirements
- Python 3.8+
- cuda 12.4
- PyTorch 2.4.1+cu124
- RDKit
- NumP... |
1d4507902a5c40a6cc343a649343d60392ede28c037bf8980dc22ffd24db52ce | Text | 1,261 | 22 | # ChEMBL MTL
## Code
- Code to extract data using ACH and Target curation from ChEMBL as described in the manuscript: `001_Grab_Assays_ChEMBL34.ipynb`.
- Example code to run GNN regressors on these data splits: `002A_Run_GNNs_script.py`
- Example code to run RF regressors on these data splits: `002B_Run_RFs_script.py`... |
fbe7a833b59973f0703baed745d13f70dedba23c530ac3860dda2a1a26729d8e | Text | 1,268 | 29 | # Evaluating exon skipping in the central nervous system in Duchenne muscular dystrophy using spatial transcriptomics
This repository contains code and resources related to our manuscript:
**Evaluating exon skipping in the central nervous system in Duchenne muscular dystrophy using spatial transcriptomics**
Qirong ... |
72805c755eb0998c5085eceece3652eeed8811ff60b947982dc45e997cdbfb13 | Text | 1,288 | 32 | <Proposed method>
SuperDIRECTEUR
<Introduction>
SuperDIRECTEUR predicts combinations of small molecules by accounting for dynamic molecular mechanistic changes during direct programming induction. To account for these dynamic changes, the cell conversion process is divided into several stages (e.g., Primal stage, Imm... |
ba3dffd23279e8c4ec8795e0fc03f375c138d0d34345a255dc26dc61a0553096 | Text | 1,290 | 30 | # Dynamic Spatiotemporal Features in Action Recognition: A Multimodal Study
This repository contains the data and code for the analyses reported in the study: "Dynamic Spatiotemporal Features in Action Recognition: A Multimodal Study.
(Q.H. Jin, D. Cui, and K. Nelissen, submitted)
## Directory: video_feature_proce... |
1a77fdd4e49467867ad858ba0f4b3d038b0ca5d42c3cb1e3be7edd0450fedb4b | Text | 1,293 | 28 | # Code repo for the manuscript: "Multi-omic human neural organoid cell atlas of the posterior brain"
Repository conitaning code used for the analysis in the [Azbukina, He, Lin et al., 2025](https://www.biorxiv.org/content/10.1101/2025.03.20.644368v1).
The repository is organized into the following directories:
`ti... |
d07caf680c1db6dbe8d9ed7b9c6060a798896493b35ab5da265a124ff8c1cf3a | Text | 1,296 | 26 | HERE we are maintaining an newly improved stable version of SAIGE and SAIGE-GENE+.
Please find the https://saigegit.github.io/SAIGE-doc/ for documentation.
SAIGE is an R package developed with Rcpp for genome-wide association tests in large-scale data sets and biobanks. The method
- accounts for sample relatedness ... |
e0b87fa7a4e47baf230ad28c5c30d600d2d163f678c5c4e2b15ea799e07cd7c9 | Text | 1,296 | 29 | ## Associated Publication
### *Sex and tissue resolved co‑expression networks reveal a female placental–brain axis protective against prenatal PCB exposure* — Chau et al., accepted at Genome Biology (2026)
---
## License and Data Availability
This code is released under the MIT License. See the LICENSE file for deta... |
214ad1c8f2f1ea138556b0da05d27f537ecf8c67bb99d96fd8d0051995fc1c30 | Text | 1,301 | 31 | # New Mesmerize Packages
The Mesmerize desktop application within this repo is no longer supported. Please checkout the new mesmerize packages which have longterm support.
**These new packages are much easier to install! They are also much more efficient, versatile, and offer rich visualizations.**
The batch manageme... |
2905689beff9e0ce5c58d5b011ccad5aff894d1ab64a189f3d1f82e2167bfc61 | Text | 1,305 | 29 | # Diabetes Gender Disparity Analysis
This repository contains the full reproducible analysis code and synthetic dataset for the article:
**"Gender Disparities in Random Blood Glucose Levels Among Pakistani Adults with Type 2 Diabetes: A Cross-Sectional Analysis"**
## Contents
- `diabetes_study_raw.csv` – Synthetic ... |
6eb8b21437cbb05d43d0519361b628573d17e3c91c03a3f92d7093905839d108 | Text | 1,315 | 27 | # Metagenomic Intra-Species Diversity Analysis System (MIDAS)
MIDAS is an integrated pipeline that leverages >30,000 reference genomes to estimate bacterial species abundance and strain-level genomic variation, including gene content and SNPs, from shotgun metagnomes.
## Table of Contents
1. Getting started
*... |
b023b3fb7be64ff14f0d50802eb57541fdd2dd3c86b867ff5d8a416eb14601b1 | Text | 1,317 | 18 | # impro - IMaris file PROcessing pipelines
Imaris (https://imaris.oxinst.com/) allows for statistics being exported in the form of .xls files, e.g. from surface or filament reconstructions.
## Conversion of .xls to .xlsx
Please first convert your .xls files to .xlsx for the .R script to work. This repository includes ... |
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