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5739dee1b63c9550446dcd9368a003dc7861b0a2217a4bacb86921e504fba930 | Text | 3,515 | 87 | [![PyPi][badge-pypi]][link-pypi]
[![PyPIDownloads][badge-pypidownloads]][link-pypidownloads]
[![CI][badge-ci]][link-ci]
[badge-pypi]: https://img.shields.io/pypi/v/scvelo.svg
[link-pypi]: https://pypi.org/project/scvelo
[badge-pypidownloads]: https://pepy.tech/badge/scvelo
[link-pypidownloads]: https://pepy.tech/proje... |
de9d2180b6471dc3abb3853b49208677ee8ccc613163003d7c83d29692a78be4 | Text | 3,536 | 58 | This code was used for the analysis used for "Growth rates for coral reefs peaked at 25 °C through the Holocene"
by Tonya Macedo and Robert van Woesik.
Overview:
Main dataset: Holocene_Reef_Growth_Final.csv is the dataset that was used for modeling, containing 1,890 samples.
Main goals:
1. Use a GLM... |
9a29adef30b8df535bc42a90f03938e9ff05e38dd674785b29bb1d5a83b2b48a | Text | 3,542 | 68 | # A tool for identifying gene modules and regulatory lncRNAs and TFs
The eGRAMv2R1 program identifies gene modules comprising co-expressed genes, their regulatory lncRNAs and their regulatory TFs based on lncRNA/DNA bindings, TF/DNA bindings and gene expression correlations.
There are two kinds of input files - (... |
183068f60cce319240135f926874cda043a07f60357a06c0cc41abc000e8934d | Text | 3,548 | 101 | Early-Smoke-Fire-Detection
An intelligent vision-based fire and smoke detection framework that integrates a Vision Transformer (ViT) with the YOLOv8 detection architecture.
========================================
------------------------------------------------------------
Project Overview
-------------------... |
71ae6fa3a142ecbc4e7ab3c5e909541bd9b65527c2faa386f48a4bfb50422fcf | Text | 3,554 | 58 | # Corpus Callosum Dysgenesis impairs metacognition: evidence from multi-modality and multi-cohort replications
**Authors:** Joseph M. Barnby*¹², Ryan Dean*³, H. Burgess³, Peter Dayan ⌇ ⁴⁵, Linda J. Richards ⌇ ³
\* Joint first author
⌇ Joint senior author
¹ Institute of Psychiatry, Psychology and Neuroscience, King... |
d10b10a7e237341713b7dd7c48927f52c30191605a3225b95d2f3be8e3b560fc | Text | 3,560 | 50 | # Distinct representational properties of cues and contexts shape fear and reversal learning
This repository contains the analysis pipeline for a multi-day fMRI study investigating how the brain represents cues and contexts during fear acquisition, reversal, and extinction.
## Study Overview
Using a narrative-driven ... |
0a58d4a907578e43ffbbcf993d8ff6b574c8e44363d17d56bf56a0d963c5baa4 | Text | 3,574 | 82 | # Brain Network Transformer
Brain Network Transformer is the open-source implementation of the NeurIPS 2022 paper [Brain Network Transformer](https://arxiv.org/abs/2210.06681).
[](https://github.com/Wa... |
d2de6b4732cd5ceb9a90a43a3c807858653c3138594f25830f0ff705e27ed9b0 | Text | 3,596 | 92 | # High frequency train readily releasable pool analysis (hfrp)
`hfrp` is a Python library designed for automatically analyzing high-frequency train stimulation for releasable pool analysis. It reads electrophysiology data from Axon Binary Format (ABF) files. The library was created with the goal of providing an automa... |
d11d0c328a528ee79e8b8b520282b9d13bbe2cce57b3e07e02b85fa78f5a91e0 | Text | 3,616 | 62 | # GP-age
GP-age is an epigenetic clock for age prediction using blood methylomes, based on a cohort-based non-parametric Gaussian Process regression model.
Here we provide a commandline standalone python version of it. We provide three models which use 10, 30 and 80 CpGs, and additional three models (termed a, b, c)... |
668411c49b4ef75697e0b73681cc24f15f22f3a341b8f4af5f43612dec00e58f | Text | 3,661 | 55 | # Multidimensional_STEPN
Code repository for single-cell multidimensional profiling of supratentorial ependymomas, preprint: https://www.biorxiv.org/content/10.1101/2024.08.07.607066v1
Raw data for scRNAseq and 10X Xenium are deposited on gene expression omnibus (GEO) under accession number GSE260452, and processed d... |
e59d679f6fd92c573a8b07532ea2ac87ff830228bf5c0ace520899ee9758db59 | Text | 3,668 | 128 | # MedGAN-SSM: Medical Image Synthesis with State Space Modeling
A deep learning framework for synthesizing missing MRI modalities using a novel State Space Modeling approach.
## Overview
This project implements a GAN-based framework for synthesizing missing MRI modalities from available ones. The model uses a ... |
86fe9d1b1b79fee65cb5e30922d5b23c352cd76caf0dcb0140e1574177a0a6ea | Text | 3,670 | 104 |
# Learning, sleep replay, and consolidation of contextual fear memories: A neural network model
**Authors**: Lars Werne et al. (2024-2025)
**Citation**: *(Manuscript currently under review)*
## Overview
This repository contains the Python implementation of the neural network model presented in our manuscript, expl... |
c50f21a3ba03df2d903072bf876a7a939cb904d2afc2e7fa34c12c6c9f2458ef | Text | 3,682 | 125 | |Python35|_
.. |Python35| image:: https://img.shields.io/badge/python-3.5-blue.svg
.. _Python35: https://badge.fury.io/py/pypreclin
Description
===========
pypreclin is a Python project that provides a collection of Python scripts for
preprocessing MRI preclinical datasets.
This work is made available by a communi... |
3f87726c58077318eb84a2636b6de7ddbb59443e3ae9dddaab8078b2b93dbb31 | Text | 3,709 | 118 | # ADNI-12M-Cognitive-Decline-ML
Reproducible machine learning pipeline for predicting 12-month cognitive
decline (≥3-point MMSE decline) in Alzheimer's disease using ADNI
clinical and MRI data.
------------------------------------------------------------------------
## Overview
This repository provides a fully repr... |
76816aa60e9de1ec52e8cf7d7c3d30f9aa9f006328e7da45475d2c90934782e3 | Text | 3,729 | 55 | # Process-PFs
MATLAB 2017b scripts for the analysis of curled protofilaments (PFs), traced in IMOD software [refs: McIntosh et al., JCB 2018; Gudimchuk et al., Nature Commun., 2020].
Open Application_PF_processing.mlapp:
- Specify the name of your dataset.
- Specify the folder where your files with PF tracings are l... |
a83defbf95abd2d5bed652bc4014cab0c3d9dfd76ed52c2a2c5ae9388b56499b | Text | 3,774 | 92 | # Backpropagation as Adjoint Data Assimilation
Teaching a Neural Network to Play Snake Reveals the Common Mechanism of Intelligence Growth in Reinforcement Learning and Atmospheric Models
## Overview
This repository contains all code, animations, and supplementary materials for the manuscript published in *Scientifi... |
362cb8e8eb3aaff694bc712e373e3eceefc5ab5aa0998d2acb63c0a6b86c02c8 | Text | 3,779 | 127 | # NSCLC-DMSP.sig
## Overview
This repository provides the R code used in the study:
"Coordinated multicellular immune programs and drug targets revealed by
single-cell analysis in driver-mutated NSCLC"
The project aims to systematically characterize tumor immune
microenvironment (TIME) heterogeneity in dr... |
b9981221e7f7a36a6da696bb6bac622d05ec61370ecbdc8f44714d1b1b93bc09 | Text | 3,796 | 43 | # Guide for dataset 2
## Introduction
This is [Dataset 2](https://doi.org/10.5281/zenodo.7553640) for the paper "General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian". The other two datasets can be found in [Dataset 1](https://doi.org/10.5281/zenodo.7553640... |
878fc8109fdb3d7d810e7c27939a0843049e25ffaf28f050ab12d50b5f3b46dd | Text | 3,800 | 69 | # MoDAmix
A Unified Framework for Correcting Batch Effects and Integrating Multi-Omics Data
## Requirements
* Python (>= 3.6)
* Pytorch (>= v1.6.0)
* Other python packages : numpy (>=1.19.1), pandas (>=1.1.1), os, sys
## Usage
Clone the repository or download source code files.
## Installation
To install MoDAmix, ru... |
6c6e396c26c095b9c9882df4d0168117601d90e0791229335d1b4ec8cfe3331b | Text | 3,898 | 147 |
<!-- README.md is generated from README.Rmd. Please edit that file -->
<div style="padding-top:1em; padding-bottom: 0.5em;">
<img src="inst/figures/logo.png" width = 135 align="right" />
</div>
# ggmirt
<!-- badges: start -->
[**.
The model architecture, synaptic mechanisms, and ... |
35cf24e953687872cc03dceb1794500bd24ceb2dd81f35aec094743f1d50d6cb | Text | 3,969 | 88 | # **BolT**
## *Fused Window Transformers for fMRI Time Series Analysis*
Official PyTorch implementation of BolT described in the [paper](https://www.sciencedirect.com/science/article/pii/S1361841523001019).
## Overall View
### Architecture
<img src="./Assets/bolT.jpg" width="800"/>
### FW-MSA : Fused window mult... |
afccdbb86f72fd553a5d6247e513c59c2fe77b8a1356a28c57c449415809d2ed | Text | 3,971 | 64 | # Multidimensional_STEPN
Code repository for single-cell multidimensional profiling of supratentorial ependymomas, preprint: https://www.biorxiv.org/content/10.1101/2024.08.07.607066v1
Processed data for sc/nRNAseq and 10X Xenium are deposited on gene expression omnibus (GEO).
scRNA-seq: GSE300150
Spatial: GSE300146... |
c9f73342171a8dafb5372c150f6eb55a6ed0201609deaedaff5ac28a2b0c089d | Text | 3,993 | 100 | # Resolving Mesoscale Brainstem–Prefrontal–Striatal Pathways Underlying Decisions Upon Salient Events Using Submillimeter-resolution fMRI
This repository contains code used in the article:
**“Resolving mesoscale brainstem–prefrontal–striatal pathways underlying decisions upon salient events using submillimeter-resol... |
7ee907e5391e40c95e468ba98a5a7a9e2c8fa5a1ce48d8b12057154a2b45e1ea | Text | 4,015 | 102 | # CaFire
CaFire is a Python-based software designed for calcium imaging data analysis. It provides an intuitive graphical user interface that enables automatic peak detection and analysis for both evoked and miniature events, making data interpretation more efficient and accurate.
](https://doi.org/10.5281/zenodo.10401165)
This repository contains the Python package and scripts for analysis and visualization
of the Opioids dataset, from the... |
a2dd511707643ee4c7dbf227aece85b105306fe13dc37a04d49708f3df6b314d | Text | 4,063 | 120 | # tb-pnca-gnn
A Graph Convolutional Network (GCN) for predicting Pyrazinamide (PZA) resistance in *Mycobacterium tuberculosis* from mutations in the *pncA* gene.
## Overview
Pyrazinamide is a critical first-line antibiotic for tuberculosis treatment, but resistance prediction remains challenging due to the diverse r... |
ffaf3b34e8d8a6cd1f3aa6295423d0e2be3ec5d93984b9a61eb55c6e0e6a7d63 | Text | 4,075 | 44 | # Guide for dataset 3
## Introduction
This is [Dataset 3](https://doi.org/10.5281/zenodo.7553843) for the paper "General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian". The other two datasets can be found in [Dataset 1](https://doi.org/10.5281/zenodo.7553640... |
150a4cddcc96d8104893421630129fe7f7d18ae164c19f5ec55489d1f86fdc22 | Text | 4,081 | 122 | # pairwiseAdonis
# version 0.4 includes 2 functions
pairwise.adonis
pairwise.adonis2
# pairwise.adonis
This is a wrapper function for multilevel pairwise comparison using adonis2 (~Permanova) from package 'vegan'. The function returns adjusted p-values using p.adjust(). It does not accept interaction between factors ... |
51743c6393fbf322e07dea2cf1ad514b736f7c2d68a0846e7f34a3623d642061 | Text | 4,091 | 62 | # Code for: Interpretable Predictive Model for Listed Companies ESG Greenwashing Based on XGBoost and SHAP
This repository contains the complete source code to reproduce all results from the manuscript titled "Interpretable Predictive Model for Listed Companies ESG Greenwashing Based on XGBoost and SHAP" (Submitted ... |
fb1649c4706ec845ec8673a9f06232887b43f21ac0dd1aa54bd78db7c56d702b | Text | 4,117 | 77 | # pMAT (Photometry Modular Analysis Tool)
[](https://www.gnu.org/licenses/lgpl-3.0)
**Version 1.3 BETA is now available!!!**
- Spike detection protocol!
- Bug f... |
b581c58f2b6371118839b66ad4453c07d9f92ce28c1a8d959d0f702c400247a2 | Text | 4,124 | 63 | # Code for: Interpretable Predictive Model for Listed Companies ESG Greenwashing Based on XGBoost and SHAP
This repository contains the complete source code to reproduce all results from the manuscript titled "Interpretable Predictive Model for Listed Companies ESG Greenwashing Based on XGBoost and SHAP" (Submitted ... |
ee12ca3894555b0f57a7d36f7e0d169414b46d5de05165288182f28e5d3656dd | Text | 4,166 | 81 | # Aircraft Cabin Localization(ACL) Dataset
[](https://doi.org/10.5281/zenodo.XXXXXXX)
---
### Overview... |
da694bb14afe803724438acb495fd8a15dd6d27d44153e5141b5a1f04456c44f | Text | 4,196 | 126 | # Cere-MEG-Bellum (CMB)
CMB is a Python package for fitting a high-resolution cerebellar atlas to standard MRI (ARCUS) and MEG/EEG source space computation including the cerebellum.
Currently under active development: **API may change without notice**. Please report any issues or feature requests on the [GitHub issue... |
9c8fa7b1089ef19ce9e84b4822cefd6d52cb63d285e7343a612aa7e78aec9374 | Text | 4,238 | 107 | # AF2BIND: Prediction of ligand-binding sites using AlphaFold2
Predicting ligand-binding sites, particularly in the absence of previously resolved homologous structures, presents a significant challenge in structural biology. Here, we leverage the internal pairwise representation of AlphaFold2 (AF2) to train a model, A... |
ebbcd6a1d6e5ad9f54e13c79822631b18a03e70e0c6f0002aa58ca0fe3dda79e | Text | 4,245 | 95 | <img src="iSTTC_logo.png" align="left" width="320" alt="iSTTC logo" />
<h3> iSTTC: a robust method for accurate estimation of intrinsic neural timescales from single-unit recordings </h3>
Preprint on biorxiv ([here][isttc_biorxiv]).
Published in PLoS Computational Biology ([here][isttc_compbio]).
[isttc_biorxiv]:htt... |
686507111d8e6450fcc74c25fc0b4601cc62e95e2096ed8d2d538d5cf2278372 | Text | 4,275 | 135 | # RibonanzaNet
Training code for RibonanzaNet, preprint: https://www.biorxiv.org/content/10.1101/2024.02.24.581671v1.
# Example notebooks
You may not want to retrain RibonanzaNet from scratch and rather just use pretrained checkpoints, so we have created example notebooks: \
secondary structure finetune: https://ww... |
80bbc175ed6e084d7cc1d1a6c8dc7f9cb92c7309bb98cb57bd6aa041f6a89625 | Text | 4,352 | 105 | # AE-Trans
`AE-Trans` (AE-Transformer) is a dual-modality fusion interpretable deep neural network model based on the Transformer architecture, capable of integrating RNA and DNA methylation data for diagnosing Alzheimer's disease and identifying related biomarkers.The model incorporates an autoencoder, a Transformer m... |
d14d59c9c8604f3d12422bc8f013c4017b6c2a5dbc016d09ceea4c5766ee678f | Text | 4,391 | 43 | # NATVIEW_EEGFMRI
Welcome! Here you will find code for preprocessing simultaneous EEG-fMRI data that is part of the Naturalistic Viewing EEG-FMRI (NATVIEW_EEGFMRI) data release from the [Nathan S. Kline Institute for Psychiatric Research](https://www.nki.rfmh.org/).
Data from this study can be downloaded from here:
[T... |
eff8d6f8fd5dd92643715002268153cf11222d17530fdd49d03683535049fff2 | Text | 4,399 | 84 | # Speech-DPOAE Stimulus Generation and Experiment Evaluation
This repository contains the code used in our study on **distortion product otoacoustic emissions (DPOAEs)** evoked by human running speech (speech-DPOAEs).
If you use this code, **please cite**: [https://doi.org/10.1101/2025.08.15.670505](https://doi.org/1... |
373a000e7c70192697d6090da5297ab5f3bcdfd9652d4e1123a81de068472b3d | Text | 4,400 | 84 | gutSMASH - A new approach to functionally profile the human microbiome for specialized primary metabolic gene clusters
======================================================================================================================
Anaerobic bacteria in the gut are responsible for the synthesis and transformatio... |
31fafdbb5202f2675699d2195f8f93a18de54f91c4e3438e54e6fac16fff2a9c | Text | 4,408 | 73 | # FLightcase :airplane::briefcase:
A federated Learning toolbox for neuro-image research, based on secure copy protocol (SCP) via secure shell (SSH).\
It was first introduced in a [preprint in medrXiv](https://www.medrxiv.org/content/10.1101/2023.04.22.23288741v1)[1],
and now contains a Command-Line Interface (CLI): ... |
9c88faca8455dd1428de29b6b1523b7a5a9e3613ec2b13c88095088f635477a3 | Text | 4,416 | 63 | # Omniglot data set for one-shot learning
The Omniglot data set is designed for developing more human-like learning algorithms. It contains 1623 different handwritten characters from 50 different alphabets. Each of the 1623 characters was drawn online via Amazon's Mechanical Turk by 20 different people. Each image is ... |
a91524def612599f78c1952c708e8ff1228ba7f3f6cc3b6defe003f20f68978c | Text | 4,453 | 70 | # AIMS - An Automated Immune Molecule Separator
# Quick Start
As of AIMS v0.9, everything should be nicely wrapped up as an installable pypi package. You can simply install the AIMS GUI, CLI, and notebook using pip:
```
pip install aims-immune
```
You can then launch the GUI, the CLI, or the notebook from the termin... |
df8036cee0b5631f71250158c6e11b5fb29a6b79ba7e4b73fe5d4003a19c037f | Text | 4,464 | 55 | # scribbles creator
Welcome to scribbles creator. This is a little tool to **automatically create scribble annotations**, similar to if you would draw them by hand, based on the ground truth of an image. It can be very useful for testing tools that perform semantic segmentation based on sparse annotations. In this rep... |
e21d23d5c7d1de457a268ce85cc7c94701a300c8d2092f65992be5203f0bfb5e | Text | 4,550 | 82 | # Stimfit
Documentation is available [here](https://neurodroid.github.io/stimfit).
## Introduction
Stimfit is a free, fast and simple program for viewing and analyzing electrophysiological data. It's currently available for GNU/Linux, Mac OS X and Windows. The standard version of Stimfit features an embedded Python ... |
c59f3b7058cbb24fa11a8e0c588ac3e948ae0c9508db11f47aaf0fae609fd5e1 | Text | 4,583 | 73 | # Spike Localization Algorithms
This repository contains the full pipeline used for our manuscript "Benchmarking spike source localization algorithms in high density probes". We include figure-generation notebooks for both the simulated ground truth dataset (MEArec) and experimental ground truth dataset (SPE1), along ... |
2eaa2af0ce53a03c8dea960bc042a5f0953f68896fcdaac90005f4660ec85301 | Text | 4,587 | 83 | # scDeepCluster_pytorch
The pytorch version of scDeepCluster, a model-based deep embedding clustering for Single Cell RNA-seq data. <br/>
Comparing to the original Keras version, I introduced two new features:<br/>
1. The Louvain clustering is implemented after pretraining to allow estimating number of clusters.<br/... |
e50a331f30c7b13a784762a9fe9bf637af99d2bda1fb6e52fd7b245aea3b4ec1 | Text | 4,590 | 52 | # ASCENT: Automated Simulations to Characterize Electrical Nerve Thresholds
[](https://github.com/wmglab-duke/ascent/releases) [](https://wmgl... |
dc65c9ffb3857d0891f50fdd08f4f01abaa7fe42fdcc7376b2161ff06c12dd5c | Text | 4,644 | 87 | # TYK2 mediates neuroinflammation in dementia with Alzheimer’s disease
This repository contains code to reproduce the findings of [TYK2 mediates neuroinflammation in dementia with Alzheimer’s disease](https://www.biorxiv.org/content/10.1101/2024.06.04.595773v1). It uses an updated version of the [Drug Repurposing In A... |
9cac999d0fb9a941150a7fe7abe53dc73cf8a61e6ecd6d0fa03a38a56edfe2be | Text | 4,770 | 90 | # arcos4py
[](https://pypi.org/project/arcos4py/)
[](https://anaconda.org/conda-forge/arcos4py)
[](https://pypi.org/project/arcos4py/)
[](https://doi.org/10.5281/zenodo.18040040)
This repository contains models and analysis code for Brown et al. 2025, bioRxiv (https://doi.org/10.1101/2023.09.01.555612) to reproduce each figure. Full datasets for anterior cingulate... |
d2b76217a0280e71c2b0477ac32a72361613d1a6bc2d985a72c6e53a269434b9 | Text | 4,806 | 131 |
# Learnable Diffusion Framework for Mouse V1 Neural Decoding
This repository includes the codes for Sensorium-Viz, a neural decoding tool utilize the Diffusion Transformer (DiT) to reconstruct the visual stimuli with the neuron responses retrieved from the calcium image data of mouse right primary visual cortex layer... |
27e035a1f82b28240c20e9527312d0c75f805b4fa92c8605dcabeb4acbb12c35 | Text | 4,875 | 89 | <p align="left">
<img src="miloR_sticker.png" width="150">
</p>
# miloR
_Milo_ is a method for differential abundance analysis on KNN graph from single-cell datasets. For more details, read [our manuscript](https://doi.org/10.1038/s41587-021-01033-z). If you use Milo in your study, please cite _Dann, E., Henderson, ... |
45ed844ebe3bdf048b4c01a40728477e32ff89f4716c6789c7ce4fd897257427 | Text | 4,879 | 145 | # PART-hippocampal-morphometry-KAJ-lab
Analysis scripts for hippocampal subfield thickness and curvature in Primary Age-Related Tauopathy (PART) with and without TDP-43 co-pathology.
## Citation
If you use these scripts, please cite:
> Youssef H, Gatto RG, Petersen RC, Reichard RR, Jack CR Jr, Whitwell JL, ... |
f651e0a0ad007fe5b8f89fe01f0862235627921cafe619c19e37d6a3ac533732 | Text | 4,885 | 98 | <img src="boussardlab.png" width="50%" style="margin-right: 20px; margin-top: 10px;" />
----------------------------
# NLP to Detect Adverse Outcomes of ACU Patients Following Chemotherapy Through Clinical Notes
-----------------------------
We introduce a novel Natural Language Processing (NLP) model, Graph-Augmen... |
464ea9552d746c9e873443ebeb5fb63be45fed768ebbd8b76aa529b5a45b8c78 | Text | 4,928 | 57 | <!-- TODO
- Add dependencies and versions of code / libraries / software / etc.
- Add note about config README
-->
[](https://doi.org/10.5281/zenodo.18475037)
# 3D modeling of peripheral nerve stimulation
The publication associated with this code: Marshall, D. P., Upad... |
b54496ee1d61d2a291df76d7081dd25877415fac88e7b797dc1566ff77872424 | Text | 4,941 | 116 | # Quantum Machine Unlearning Research Code
This repository contains code for machine unlearning experiments, including:
1. Data poisoning and visualization
2. Hessian-based analysis of model landscapes
3. Various unlearning methods comparison (Retrain, Finetune, Scrub, Grad-Asc)
4. Evaluation of unlearning effectiven... |
5d32621ccdc9a61b93c1cc102fed794b4f71ab44fe8a3f6abf3e67e8dfec44f1 | Text | 5,000 | 146 | # SupContrast: Supervised Contrastive Learning
<p align="center">
<img src="figures/teaser.png" width="700">
</p>
This repo covers an reference implementation for the following papers in PyTorch, using CIFAR as an illustrative example:
(1) Supervised Contrastive Learning. [Paper](https://arxiv.org/abs/2004.11362) ... |
b18dc85cc66a580156f2e3b8f1eb31d79bffd9476c05286a9a9d60da59875c66 | Text | 5,021 | 93 | # Public Protocols for the IBC Project
This public repository hosts the software protocols used to launch the behavioral tasks in the [_Individual Brain Charting_ (IBC)](https://project.inria.fr/IBC/) project. To know more about the specific experimental design employed for each task in IBC, consult our data-descriptor... |
3e7f81d106c779a2c69bebad6d7b121bea8ab32bf418f7754416104d5ff5c572 | Text | 5,068 | 77 | _ _ _ _ _ _ _
/\ \ /\ \ /\ \ /\ \ /\ \ /\ \ /\ \
/ \ \ / \ \ \ \ \ / \ \ / \ \ / \ \____ / \ \
/ /\ \ \ / /\ \ \ /... |
46403fa34ba2d6488f7c7431f63af38b282812a725174e724079343133a7ef92 | Text | 5,076 | 61 | This new version of BEN calculation code can directly read .nii or .nii.gz file. To use it you can follow the matlab code batch_calc_uBEN.m or through the following python code
# ofile defines the prefix of the output entropy map
# -d specifies the window length
# -r cutoff. r can be set to be from 0.1 - 0.6. For... |
2a73b0c6232dba452b0deb9c63da99969a53fd841caa261c5842d5d744f1dc64 | Text | 5,138 | 68 | # Abrasion-Resistant Wearable Skins Based on Bilayered Solid/Liquid Stretchable Conductors
Motivation
==========
Soft bioelectronic skins face challenges in matching the abrasion-resistant sensing functions of human skin. We present abrasion-resistant wearable skins based on a bilayer stretchable conductor architectur... |
166ecb8fb482276efd848e878698b21467bc23d79b17da7fd9b9ce0d3ef70f92 | Text | 5,152 | 143 | # Cytocraft
<p align="center">
<img src=https://github.com/YifeiSheng/Cytocraft/raw/main/figure/Figure1.Overview.png>
</p>
## Overview
The Cytocraft package generates a 3D reconstruction of transcription centers based on subcellular resolution spatial transcriptomics.
Cytocraft employs a **multi-start optimizatio... |
e555911e66f4fc6b32333749704ac690e2d4b4871c91375e5620f68e4fca3ff5 | Text | 5,220 | 128 | # Fractal Dimension Estimation Toolbox
This Python module provides a comprehensive suite of tools for estimating the fractal dimensions of 2D datasets. It incorporates both established and innovative methods such as original box counting, correlation sum, exact box counting, oversampling, temporal sampling, and their ... |
95d82fee67ad765ff60a82dd7503d2f7fc6814720ceacd320cd8c609e708e02c | Text | 5,227 | 96 | -------------------------------------------------------------------------------------------------
(c) 2025 Rebecca C. Felsheim, David J. Sly, Stephen J. O'Leary, Mathias Dietz
This file is part of the repository providing the code for optimizing the parameters the aLIFP model
such that the behavior of an individual ne... |
8c01873b4fe92d03639a4deec4c53a8650a5abf082c26794fa78677e9f3a473e | Text | 5,291 | 112 |
<img src='./logo.svg?sanitize=true' width=30%/>
# Rlign: R peak alignment and ECG transformation framework
This scikit-learn compatible framework `rlign` is designed to synchronize the temporal variations across ECG recordings. This alignment enables the direct application of simpler machine learning models, like s... |
5cb32519f11cbdd0a1ce863d00e4a4516f08fd6bda26785fe0158adb6bdc2869 | Text | 5,316 | 67 | # Simulation and empirical evaluation of biologically-informed neural network performance
This codebase contains all the code associated with the paper (in submission). Posted on bioRxiv at https://www.biorxiv.org/content/10.1101/2025.11.13.687845v1.
This documentation is a work-in-progress and will continue to be upda... |
5d3ba68e80ebdedf37dd75a3eeb24aebedeed08fd386c047cb545de4ff1df452 | Text | 5,333 | 83 | The EpiCode repository has been moved to the Paris Brain Institute (ICM), where we can better maintain and further develop it.
Please update your links to: https://gitlab.com/icm-institute/iconics/EpiCode
Thank you, and see you there!
_ _ _ _ ... |
14741ee7a6ca6c73c1aeb9e12450374fbf8f229872fe20556dd6ad9eff97b9be | Text | 5,349 | 112 | # DCBC evaluation
Diedrichsen Lab, Western University
This repository is the toolbox of the paper "Evaluating brain parcellations using the distance controlled boundary coefficient". It contains all the functions needed to evaluation given cortical parcellations. See the [paper](https://www.biorxiv.org/content/10.110... |
2a6fcf43615a155b1b510320566dbaf836cce57fccc2343e34c391db460b3042 | Text | 5,349 | 107 | # NeuroVelo: interpretable learning of cellular dynamics
NeuroVelo: physics-based interpretable learning of cellular dynamics. It is implemented on Python3 and PyTorch, the model estimate velocity field and genes that drives the splicing dynamics.
**-based pipeline for supervised spike sorting of **microneurography** recordings from human C-nociceptors. The pipeline is designed to address challenges such as single-electro... |
5887c70e4b2c4ceb85edb776a9a6b73800e96b57dc5ad9e962e795e307b07ebf | Text | 5,482 | 139 | # Integrated machine learning and molecular dynamics framework for predicting and elucidating ABCB1 allocrite interactions
## MolMM-PMF
MolMM-PMF is an integrated computational framework for predicting substrates and inhibitors (allocrites) of the ABCB1 (P-glycoprotein) transporter. The framework combines meta-learni... |
2a98da12bb5d1058f4a99e29984b0bfdbdd44ffabac8f1bfb18392eb15e371c3 | Text | 5,490 | 184 | # R3J-AGNN
**Geometry-Aware Prediction of RNA Three-Way Junction Inter-Branch Angles from Secondary Structure**
## Introduction
R3J-AGNN is a geometry-aware deep learning framework for **predicting inter-branch angular configurations of RNA three-way junctions (3WJ)** directly from RNA secondary structure information... |
1a9e193f11010f0a6145b715c0abf13e0dcd8b0c1e41a1caae4c0dd921ff0ce8 | Text | 5,589 | 103 | ## JOINT for scRNA-seq
JOINT performs probability-based cell-type identification and DEG analysis for single-cell RNA sequencing (scRNA-seq) simultaneously without the need for imputation. It applies an EM algorithm on a generalized zero-inflated negative binomial mixture model. It supports arbitrary numbers of negati... |
76a615f0125087fdf8d5ae1adf8863ef75da2dc7f9a103a992aeb06da718ddc0 | Text | 5,698 | 89 | # MACE-H
This code is released as the MACE-H model in the paper *Equivariant Electronic Hamiltonian Prediction with Many-Body Message Passing* ([arXiv:2508.15108](https://arxiv.org/abs/2508.15108)).
This package is developed based upon [DeepH-E3](https://github.com/Xiaoxun-Gong/DeepH-E3), and share the similar ... |
c5d26207f00dee3c05ae67f3f03e74c7383c499148cd0485738cb0ca8b7625d2 | Text | 5,846 | 81 | # SPICE: A Dataset for Training Machine Learning Potentials
This repository contains scripts and data files used in the creation of the SPICE dataset. It does not contain the
dataset itself. That is available from Zenodo:
[](https://doi.org/10.5281/zen... |
87665781738ad9feb2839eda50f1f2916d344caadb8f440f9defcbd3e1e825ef | Text | 5,932 | 74 | ## Gray-matter Based Spatial Statistics (NODDI-GBSS)
[](LICENSE.md)
#### Introduction
Gray matter-based spatial statistics (NODDI-GBSS) is a pipeline to perform voxel-wise statistical analysis on gray matter microstructure. Our method is... |
808a877c4a6f7cde9a697ecacb975f90b183ab31222a58ad2a55a350308fd2be | Text | 6,027 | 169 | # idat-tools
[](https://www.python.org/)
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://causarray.readthedocs.io/en/latest/?badge=latest)
[](https://pypi.org/project/causarray)
[](https://pe... |
b7d41e502030a79c5cffe361a5f09693a2c93788c9e034603c95c2f4e3a0583f | Text | 6,070 | 114 | # spatialN3ICD
Source code for [Jagged-mediated lateral induction patterns Notch3
signaling within adult neural stem cell populations](https://www.biorxiv.org/content/early/2025/08/01/2025.07.29.667421) [[1]](#1).
This Python code implements spatial analysis from point process theory to study Notch3 signalling betwee... |
fc9b624afb70e0f00b29503e605b9463a397b5a0ce95e5e5261b089c629dfb3a | Text | 6,141 | 95 | <p align="center">
<img src="https://raw.githubusercontent.com/holehouse-lab/PIMMS/master/branding/logo.png" alt="PIMMS logo" width="480"/>
</p>
<h1 align="center">PIMMS: Polymer Interactions in Multi-component MixtureS</h1>
<!-- Badges -->
<p align="center">
<a href="https://idptools-pimms.readthedocs.io/en/late... |
2e3e33fd42e9d7643876ce30ba24bd1cd18eefc18bad7b157a969b753c017ae2 | Text | 6,177 | 116 | # MINFLUX_Localization_and_Tracking_Analysis
## Description
MINFLUX_Cluster_Analysis_Mulhall_2025.m is used to identify trimeric (triple‑labeled) PIEZO molecules from Abberior Instruments MINFLUX 3D localization data and to compute inter‑blade geometry. It does this by two-step DBSCAN clustering followed by an expect... |
6a8d62c8bea8eee8d902cd2b0460a557e5678d3370d835ee7b4fa73b938926e8 | Text | 6,261 | 73 | # BENtbx
A new version of the entropy calculation code of the BENtbx
ben included here is compiled using gcc 5.4. The Windows version was compiled with VS2012. To use the code, read the file readme.txt and follow the example provided there and in batch_calc_uBEN.m. You can still go to https://cfn.upenn.edu/zewang/BENt... |
775872736147efde834156a60a928ef9f071b85b06399994f9158a885c419f97 | Text | 6,371 | 157 | # campy
- Python package for acquiring synchronized video from multiple cameras with real-time compression
## Hardware/Software Recommendations
- Basler and/or FLIR machine vision camera(s)
- Windows, IOS, or Linux system
- (Recommended) Server/workstation class CPUs with >=4 memory channels (e.g., AMD Threadripper 39... |
be67418a0e0fff41c7ffad7f988c49772f236b3cd5c8bdf51eadbb8f22ac54cd | Text | 6,371 | 203 | Inverse Adding-Doubling
=======================
.. image:: https://img.shields.io/github/v/tag/scottprahl/iad?label=latest
:alt: GitHub tag (latest by date)
.. image:: https://img.shields.io/badge/MIT-license-yellow.svg
:alt: MIT License
:target: https://github.com/scottprahl/iad/blob/main/License
.. image:... |
e0764de202766c79377d1de473a7835f54973da8e8647ce3884d805932b87890 | Text | 6,430 | 135 | # designer-v2
## Introduction
Designer is a python tool for diffusion MRI preprocessing. It includes:
* denoising using MPPCA (or optionally using patch2self through dipy)
* RPG Gibbs artifact correction
* Rician bias correction
* EPI distortion correction
* Eddy current and motion correction
* b0 normalization for m... |
98b3f2114d164614c191434eb31b66e656b84f4b0d224f93d6acf144db4c0bc9 | Text | 6,456 | 157 | # Dynamic Neuron–GAN Alignment
Code and data for:
> **Neuronal tuning aligns dynamically with object and texture manifolds across the visual hierarchy**
> Binxu Wang & Carlos R. Ponce
> *Nature Neuroscience*, 2026
> DOI: [to be added upon publication]
---
## Overview
We evolved images to maximally activate i... |
42b8c78899a954e7ef9fc1ade7d12fc8c09da0e1ade5e5c55a1b5ccc017f573c | Text | 6,496 | 96 | # scMAVERICS
## single-cell Multiome Analysis using Variational-inference and Enhancer-driven Regulatory-networks to Inform Cell-atlas Structure
The workflow was built to minimize the time required to work on processing data and get the single-cell scientist analyzing high-quality processed data. This pipeline is b... |
c5276d439eff244933a6d1fc5f4510a3577ee35de81fd0b79917bda42fc24f10 | Text | 6,615 | 224 | # igsa-mlpnn-garson-hsq-happiness
Code and documentation for modeling the relationship between residents' happiness and human settlement quality using the IGSA-MLPNN-GARSON approach.
## Overview
This repository contains the source code, analysis scripts, and documentation associated with the manuscript:
**Modeling t... |
47ec805c94a3e800fb1fcf32b6b9e2ce8140b36296bceb3ed949e63c0af981c8 | Text | 6,656 | 224 | # igsa-mlpnn-garson-hsq-happiness
Code and documentation for modeling the relationship between residents' happiness and human settlement quality using the IGSA-MLPNN-GARSON approach.
## Overview
This repository contains the source code, analysis scripts, and documentation associated with the manuscript:
**Modeling t... |
fd0e0336387534ccb369d61b1c8c2efd80dd4d9d849311452222271c9699c130 | Text | 6,664 | 97 | # 
**Rabbit in a Blender (RiaB)** is an [ETL](https://en.wikipedia.org/wiki/Extract,_transform,_load) pipeline [CLI](https://nl.wikipedia.org/wiki/Command-line-interface) to transform your [EMR](https://en.wikipedia.org/wiki/Electronic_health_record) data ... |
bd8a4e76d3aea278c8b42d41472bdfff9ac3a212111f37a1c465fb42c8932314 | Text | 6,700 | 230 | # Synapse Gigamapper (SyGi)
Synapse Gigamapper is a specialized protein language model built based on Evolutionary Scale Modeling Cambrian (ESM-C) embeddings and the multi-task learning framework of the [ProtGPS] model (https://github.com/pgmikhael/protgps), designed to explore and predict protein localisations at exc... |
3d3bbb4e8f1462cfe3049c98a839f14cf619ef3947775bfc2009c6821bb75885 | Text | 6,708 | 95 | # SeuratData
SeuratData is a mechanism for distributing datasets in the form of [Seurat](https://satijalab.org/seurat) objects using R's internal package and data management systems. It represents an easy way for users to get access to datasets that are used in the Seurat vignettes.
### Installation
Installation of ... |
bb24c04466b7d31608b0156da4231d206f031140e18e1706ba6419a69c43effe | Text | 6,775 | 160 | README
# My Scientific Publication
This repository contains the code and data used for the manuscript titled
"Behavioral evidence for the hierarchical execution of sequential movements".
## Getting Started
All analyses and simulations were performed on a Linux machine. While we cannot
guarantee it, there should be n... |
267f19b2155d7416cc080997447923ee708250f7c746a47f2df3e779ff4a775a | Text | 6,811 | 129 | # Welcome to CBSI!
**Contrast-free BBB Status Identification model (CBSI)** is a generative diffusion AI that can identify BBB status with high accuracy using non-contrast MR images, including T1 and T2-FLAIR MR scans.
<img src="https://github.com/Kindyz/CBSI-debug/blob/main/sample_png/Framework.png" width="800px">... |
f853b964e188f25206670efa88240d7aa3ec810c6bb867a2b4a40fe4b5b1c597 | Text | 6,908 | 102 | # Pacman Behavioral Analyses
## Overview
Analysis scripts (mostly in R) for the behavior and statistical analysis of the PacMan project. While [Staveland_et_al_Pacman_Neural_Analyses](https://github.com/bstavel/Staveland_et_al_Pacman_Neural_Analyses) has the python scripts for analyses that are (nearly) only brain da... |
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