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2a45640a2dc36ba06c944410c11d6a03535a3432700a8ed5410d6fd1c39b3860 | Text | 3,943 | 63 | Object detection and instance segmentation dataset for VHR remote sensing images further marked on the NWPU VHR-10 dataset and SSDD dataset according to the standard coco dataset.
# VHR-10_dataset_coco
NWPU VHR-10 data set is a challenging ten-class geospatial object detection data set. This dataset contains a total ... |
d58c948822dfb2503995fcc4d708c7b82291e3dd8a0741587714da05abaaeef2 | Text | 3,952 | 138 | # A Hybrid CNN GRU Model Framework for Epilepsy Detection
Based on our paper "**A Hybrid CNN GRU Model Framework for Epilepsy Detection from EEG Datasets**" will be published in **Brain Informatics, Springer**.
## Requirements
To install the required dependencies run the following in command prompt: `pip install -r req... |
8d2aa06019cba1ec7b4ebad7da852225257a6320850964a055d8c2d219dc5f5d | Text | 3,962 | 72 | # anestheticsAnalysis
repository for the code used in the analysis of the manuscript titled "Existence of multiple transitions of the critical state due to anesthetics"
This is documentation for the code provided along with the manuscript:Existence of multiple transitions of the critical state due to anesthetics
Link... |
2c80ec2198fe4e56338a58b29629b71e05f34f1388507e09e8e9565e60db618f | Text | 4,038 | 65 | # qmri-ald
[](https://github.com/umn-milab/qmri-ald/issues)
Image analysis pipelines of qunatitative MRI (qMRI), including diffusion MRI (dMRI), in patients with adrenoleukodystrophy (ALD)
## Content
- [Introduct... |
b41bd0cbdafbeca3d4c64fe599ab89427ceb10a7e1ded352555ebc4a06ecfe33 | Text | 4,054 | 47 | # Combining EEG and Eye-Tracking in Virtual Reality - Obtaining Fixation-Onset ERPs and ERSPs
The project implemented and tested an eye-movement classification algorithm for data recorded in a 3d, free-viewing, and free-movement virtual environment. It is a velocity-based classification based on the algorithms of the ... |
07c9cc07ff6497affa6353a4b82240a83617bd47ea4a04d1a939e13ea5baea3d | Text | 4,060 | 92 | # app-multiAtlasTT
master branch
[brainlife.io](https://brainlife.io/) version of multi atlas transfer tools (maTT). This app takes in a completed `recon-all` FreeSurfer directory, and outputs a volumetric parcellation in the indiviual's T1w space. These tools warp the parcellations to the subject space using the wa... |
a63b6a9c8164a946c1a06bde0c4fe262f702be0d272a61c9de1cde1cdd216a51 | Text | 4,110 | 41 | # Mouse Brain Atlases Generator Workflows
Scripts to build the mouse brain atlases collection used by [SAMRI](https://github.com/IBT-FMI/SAMRI) and more generally by the ETH and Univeristy of Zurich Animal Imaging Center.
**N.B.** Most of the volumetric data fetched and bundled in this archive are not originally reco... |
ca3cb0550cc58f77fa7139f2100ad8bc92f6b4c774df5c31ebc8e96dd48c7459 | Text | 4,113 | 103 | # Metallicity RRLs
Machine learning and deep learning models to estimate metallicity from light curves.
## Data
...
## Dependencies
All Python packages needed are listed in [requirements.txt](requirements.txt) file
and can be installed simply using the pip command.
## Models
The following models are implemented ... |
ad4a7ce276e2a049b7a8fa47d892efa3b10ad207669c0df7fa0469f63adb9120 | Text | 4,115 | 100 | [](https://www.python.org/downloads/release/python-390/)
[](https://github.com/rzzli/tiana/issues)
# TIANA
Transcription factors cooperativity Infe... |
4edff85a1ce5633dcc7bbe1a01255cc6f62ff20eb8435b3e58a1fb9721a9c77b | Text | 4,122 | 86 | This version of MonoAlg3D contains custom functions to reproduce the results in Riebel et al., Scientific Reports (2024), https://doi.org/10.1038/s41598-024-67951-5 and Riebel et al., Stem Cell Reports (2026), https://doi.org/10.1016/j.stemcr.2026.103007.
Accompanying Purkinje and biventricular infarction mesh files c... |
7a90ed369bc3f1db7fd19895d75ac7de559973af4e0fcb6c2b71eeadfdeec44f | Text | 4,123 | 80 | Endstate correction from MM to NNP
==============================
[//]: # (Badges)
[](https://github.com/wiederm/endstate_correction/actions?query=workflow%3ACI)
[![codecov](https://codecov.io/gh/wiederm/endstate_correc... |
54fdab6fec6c22ff9a1e80ad5e19d3b15a82eca58e6e6b1e5f27c03d5fbea7d4 | Text | 4,134 | 54 | # Deep transfer learning-based bird species classification using mel spectrogram images
This repository contains the code and resources for the research paper **"Deep transfer learning-based bird species classification using mel spectrogram images"**, published in *PLOS ONE*.
## Abstract
The classification of bird sp... |
a073294491cad163ba052f0d8f9c2059dbc1ded0f8687e81a992e20f3a62fa7f | Text | 4,146 | 88 | # Azure Kinect SDK (K4A)
Welcome to the Azure Kinect Sensor SDK! We hope you can use it to build many great applications and participate in the project. Don't be shy to ask questions, and provide feedback. See [Azure.com/Kinect](https://Azure.com/kinect) for device
info and available documentation.
[![Build Status
(d... |
09b8dc3acfb230e1704bdfb2e5b33314ecf5916b47827e7cae08a1a70f56b1a9 | Text | 4,164 | 49 | # MiniscopeAnalysis
Analysis package for miniscope data
Written by Guillaume Etter (Sylvain Williams Lab, McGill University)
This is an updated version of the Miniscope analysis package developed by Daniel Aharoni at UCLA in collaboration with the Golshani lab, Silva lab, and Khaki lab.
It combines core functions of th... |
8250d36840ac61ac94f84c26decd97bd9be1c833fe03e925f5375f56269d0a3b | Text | 4,170 | 73 | # kindey_disease_prediction
Implemented various classification algorithms like ExtraTrees,rf,decision tree and LightGBM, and also performed feauture selection and hyper paramter tuning
# Chronic Kidney Disease Prediction
This project aims to predict the presence or absence of chronic kidney disease based on medical a... |
9091c3f8890ec432948aa1acf18503b8c0cc7573a50aebf0462ded1809fb4f6b | Text | 4,184 | 87 | # NAS-Bench-Graph
This repository provides the official codes and all evaluated architectures for NAS-Bench-Graph, a tailored benchmark for graph neural architecture search.
Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu, [NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search](https://openreview.... |
c76ecaa7695eec474746f8aa13d2a20e334148901ebf2f5c0c8d4c77c7b7f7f0 | Text | 4,203 | 70 | # Jointly Efficient Encoding and Decoding in Neural Populations.
## Introduction
This repository contains the custom code associated with the manuscript titled "Jointly Efficient Encoding and Decoding in Neural Populations." (Blanco Malerba et al., 2023).
The manuscript investigates a novel approach for efficient enco... |
a7c1457ddd627308a47cf823a34196b24b4581f21d82c1122a90332ab079a283 | Text | 4,209 | 153 | # Comparison_AD_PD
Pipeline to process and annotate single-cell dataset. Comparison of two single-cell datasets on different biological levels such as gene, pathway, and cellular sub-network.
## DEGs_PD folder
Find the DEGs for all cell types in the PD dataset.
These files are the output of Single-cell_processin... |
1cda92e476ec0c50b83f37b1a5ac3534f55533c033e7b7946e31fd0d41bc2029 | Text | 4,219 | 89 | # Interpretable Classification of Alzheimer's Disease Pathologies with a Convolutional Neural Network Pipeline
## bioRxiv 454793
## DOI: https://doi.org/10.1101/454793
## Zenodo Data Available at: https://doi.org/10.5281/zenodo.1470797
This repository accompanies the publication above. Specifically, we include Jupyter ... |
6cd5fbe286f8c0c531e055499985be68c87101439d8f77d193cb1b78aae23218 | Text | 4,242 | 105 | # Nonlinear fusion
Code for the paper Ghosh et al., 2024 *Nonlinear fusion is optimal for a wide class of multisensory tasks*:
* [Paper](https://doi.org/10.1371/journal.pcbi.1012246)
* [Preprint](https://doi.org/10.1101/2023.07.24.550311)
If you have any questions regarding the code please contact either [Marcus Gho... |
96e3a2982fc3e03e702099f95baeb5e25b0ae913a4ce1b6f835f628faf91c890 | Text | 4,246 | 110 | # DNA-PAINT_analysis
Get performance metrics for your DNA-PAINT measurement.
Associated publication:
Please cite
Steen, P.R., Unterauer, E.M., Masullo, L.A. *et al.* The DNA-PAINT palette: a comprehensive performance analysis of fluorescent dyes. *Nat Methods* (2024). https://doi.org/10.1038/s41592-024-02374-8
... |
e6e615085ee24ae201fd3a72175cb68f134b8093c61f2d9a42dfdab7986cc50d | Text | 4,262 | 57 | # NativeThymusScripts
Collection of scripts used for analysis of data in "Intravital Two-Photon Microscopy of the Native Thymus"
# Scripts and Usage:
`Intravital two-photon microscopy of the native mouse thymus.xlsx` - Excel file containing raw data used to generate figures in paper.
`VasoMetric_SpencerVersion.ijm` -... |
42ba393c05ab87229ad0970a060a5f9042a7e1e192ae625b63b511caa7a78ee2 | Text | 4,272 | 59 |
[](https://github.com/google-research/weatherbench2/actions/workflows/ci-build.yml)
[](https://github.com/google/bayesnf/actions/workflows/pytest_and_autopublish.yml)
[](https://badge.fury.io/p... |
b0709604ae4f39db6ff8becf3f8492c668a21c6e644e0b7d9c669c1009cf13e5 | Text | 4,384 | 46 | # Asymmetric Weighted and Signed Connectome toolbox
This toolbox presents a set of functions that can be used to create and analyze asymmetric, weighted and signed anatomical networks as presented in the paper:
Tanner, J., Faskowitz, J., Teixeira, A. S., Seguin, C., Coletta, L., Gozzi, A., ... & Betzel, R. (2024). A m... |
f493d428cb017d5a79d1a2aa933824ce75c649804c03f78193dc35ee23a0c648 | Text | 4,389 | 68 | Along-tract statistics
========================
1. Overview
2. Install
3. Support
4. License
Overview
--------
This is a set of tools for conducting an along-tract analysis of white matter fiber tracts derived from diffusion MRI data. It allows you to analyze a scalar metric (e.g. fractional anisotropy; FA) parameteri... |
c28559701ecf27cdefaa7b0c111eb82e0034e82cdde753caea5404a53f09e2e2 | Text | 4,402 | 59 | # BPT-PLR: A Balanced Partitioning and Training Framework with Pseudo-Label Relaxed Contrastive Loss for Noisy Label Learning
<h5 align="center">
*Qian Zhang, Ge Jin, Yi Zhu, Hongjian Wei, Qiu Chen*
[Entropy](https://doi.org/10.3390/e26070589)
[License: MIT License](https://github.com/LanXiaoPang613/BPT-PLR/blob/mai... |
deb5484651056aa7ff31d270ca46181847b96ac8dc165b4bfd6266c10073fb74 | Text | 4,412 | 68 | # scCM
### A contrastive learning model for analyzing large-scale CNS scRNA-seq data
#### scCM is constructed based on a momentum contrastive learning framework (MoCo v3 [1]) to learn informative representations of CNS scRNA-seq data. It comprises three modules: an encoder, a momentum encoder, and a predictor head, all... |
18541a9d77a63250e43c39a343d2e0f8adecc79e43b971d277c20803a2f69d65 | Text | 4,430 | 64 | # Direct linear discriminant analysis (DLDA)
Here we provide a set of [MATLAB](https://mathworks.com/products/matlab) based scripts to perform direct linear discriminant analysis on fMRI data.
## Citing ##
Please use the following paper to cite the toolbox:
Kakaei,E. & Braun, J. (2023) - Gradual change of cortical ... |
6809b0a57527ffbf560c98f0a234f8f869363962186b458f126c6c31f93ef3cf | Text | 4,472 | 93 | Multi-dimensional Gated Recurrent Units
=======================================
This repository contains the code used to generate the result in the
paper `Automated Segmentation of Multiple Sclerosis Lesions using
Multi-Dimensional Gated Recurrent Units <https://link.springer.com/chapter/10.1007/978-3-319-75238-9_3>`... |
1514232f69a7fccd0d7867468f4d189bec3f9c48e22147553f2db9653f53560c | Text | 4,480 | 95 | Discovery of Nuclear Mitochondrial Insertions (dinumt)
======================================================
Description
-----------
This software is designed to identify and genotype nuclear insertions of mitochondrial origin from whole genome sequence data. It consists of two programs: dinumt (di-nu-mite), w... |
73630621c37d267daa833009cdccbecfe46ab8ae1471c4e754afeb4de592271e | Text | 4,501 | 88 | # Loss of Plasticity in Deep Continual Learning
## Contents
- [Overview](#overview)
- [Repository Contents](#repo-contents)
- [System Requirements](#system-requirements)
- [Installation Guide](#installation-guide)
- [License](./LICENSE)
- [Citation](./citation.bib)
## Overview
This repository contains the code to r... |
c08e763d24cf069e7d4c7f0231967be7a14652355978ca2a44b981ad9359fe56 | Text | 4,515 | 78 | <picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/neuromorphs/NIR/raw/main/docs/logo_dark.png">
<img alt="NIR Logo" src="https://github.com/neuromorphs/NIR/raw/main/docs/logo_light.png">
</picture>
# NIR - Neuromorphic Intermediate Representation
NIR is a set of computational primitive... |
3a9e5e3f297d99378edec0a6bfa4266eb7d38c3c8c6b41f8fea6a594f9e43882 | Text | 4,520 | 44 | # Read, write, switch — code and derived results
Code accompanying: Rahman T. *Read, write, switch: Recursive estimation of architecture, drive, context, and permissive terms in three Drosophila behaviors.* (under review at Behavioural Processes).
All numbers and figures in the manuscript are produced by the scripts ... |
4f963206fbf7a5e31c54cb15e7acb1804fdd4421076ad6e795098ff8baf53b4b | Text | 4,578 | 101 | Raw data of "Deep mouse brain two-photon near-infrared fluorescence imaging using a superconducting nanowire single-photon detector array"
========================
https://doi.org/10.48550/arXiv.2312.14042
Correspondence:
- M.C. (m.caldarola@singlequantum.com)
- R.P. (prevedel@embl.de).
Data were collected ... |
7759385e3971c394aa8b6f2f90e545c7b9295eeb62772437bb5bbd0e1a566530 | Text | 4,594 | 128 | # scCAD
## Introduction
Cluster decomposition-based Anomaly Detection method (scCAD) is used to effectively identify rare cell types in scRNA-seq data.
## Getting Started
## Hardware requirements
`scCAD` package requires only a standard compu... |
d82e6fd8a02287b29b5ec648b385c76a75aa11e6b651e92bd66744339f8c4e20 | Text | 4,608 | 131 | # Bipartite left-right sided endocrine system: processing of contralateral effects of brain injury
### Abstract
The crossed descending neural tracts set a basis for contralateral effects of brain injury. In addition, the left-right
side-specific effects of the unilateral brain lesions may be mediated by neurohormones... |
21d93739992b1d8f47b6598669724dad5acb14ce30097d1191707956400d3604 | Text | 4,630 | 128 | # scCAD
## Introduction
Cluster decomposition-based Anomaly Detection method (scCAD) is used to effectively identify rare cell types in scRNA-seq data.
## Getting Started
## Hardware requirements
`scCAD` package requires only a standard compu... |
72f731e3fb4305d99c5542708f0aa6005f0c64eda3e8202e81526357c380a94c | Text | 4,637 | 127 | spASE
================
- <a href="#installation" id="toc-installation">Installation</a>
- <a href="#quick-start" id="toc-quick-start">Quick start</a>
- <a href="#hypothesis-testing" id="toc-hypothesis-testing">Hypothesis
testing</a>
- <a href="#visualization" id="toc-visualization">Visualization</a>
- <a href=... |
a78c67116f6d0b73503642d48e8bb5f289635b40d04febfd18e3027dd3f0a653 | Text | 4,653 | 99 | # JHU/KKI_QSM_Toolbox
## Version 3.3
*************************************************************
Previous public version:
JHUKKI_QSMToolbox_v3.0 is available @ https://godzilla.kennedykrieger.org/QSM/
with some example 3T data and a basic manual
JHU/KKI_QSM_Toolbox is a MATLAB software with GUI for doin... |
1a96d4a25b53e8f2109e2b0a03e2a938ac65ccd10b690debe12592fae37290f0 | Text | 4,657 | 87 | # FRASE-bot-RDKit
FRASE-bot-RDKit is a collection of cheminformatics protocols designed for data processing on FRASE screening, developed in Python with RDKit, a powerful cheminformatics toolkit. This version eliminates the need for a Pipeline Pilot commercial license and provides flexibility for users to use the capa... |
1d084dd5ca7e60775a00ca3ce79b1be80b8fff72a824a0cf2542459635ba7450 | Text | 4,699 | 96 | # Successor Feature Neural Episodic Control
Source code and experimental evaluation for the paper: ["Successor Feature Neural Episodic Control"](https://arxiv.org/abs/2111.03110v1).
Authors: [David Emukpere](https://www.linkedin.com/in/david-emukpere/), [Xavier Alameda-Pineda](http://xavirema.eu/), [Chris Reinke](htt... |
174fff52e6b3a4629da290ecae77bbad6d9be79415bbbc3474fd93507b663916 | Text | 4,704 | 102 | # Predicting the affinity landscape of N-TIMP2/MMP9<sub>CAT</sub> by combining deep neural networks and deep mutational scans
# Introduction
We present a novel approach using deep neural networks (DNN) trained on High-Throughput Sequencing (HTS) data for protein mutagenesis library affinity screens.
In this study, w... |
3c67fde374fd6917e79fa7eb134f4db1096431e48b95cdc85226fae5b2297141 | Text | 4,741 | 80 | # Prognostic Risk Prediction Model for Hepatocellular Carcinoma Using CT scans
This is the Github Repository for "Deep Learning-Based Overall Survival Prediction in Immunotherapy-Treated Hepatocellular Carcinoma Patients Using CT scans".
## Getting started
### Dependencies
This proje... |
671cb863be018f5e0983deb117aac41d6421fa1ea5038ce5f4ac3067e5ff795d | Text | 4,743 | 84 | # Regional Deep Atrophy (RDA): A self-supervised learning method to automatically identify regions associated with Alzheimer's disease progression from longitudinal MRI
**RDA** is a model for longitudinal quantification of AD progression in the medial temporal lobe (MTL) region of the brain, the earliest detectable MR... |
d0585efe16a04aa62253b37d82644dfcfc061cc2bb3b7bca9788c74f8d8b8986 | Text | 4,781 | 107 | # GR-pKa: A message-passing neural network with retention mechanism for pKa prediction
## Introduction
This repository provides codes and materials associated with the manuscript [GR-pKa: A message-passing neural network with retention mechanism for pKa prediction].
- **GR-pKa** is a novel pKa prediction method whic... |
1a1b760c7d4f79c38fc1cd83826736bfbf4a94068f94e481ec1e6c8ff908bd0c | Text | 4,807 | 146 | [](https://github.com/nick-youngblut/gtdb_to_taxdump/actions/workflows/pythonpackage.yml)
[](https://zenodo.org/doi/10.5281/zenodo.10981088)
<img src="./figure.jpg" width="900">
We created a method scPriorGraph based on P... |
e453331dfda23b572cf465deb3d4beafc24588773c137e602557fae3bda8eb94 | Text | 4,847 | 56 | Decisively assess cross-contamination in spike-sorted electrophysiology data using DCISIv (Decoding Cross-contamination using Inter-Spike-Interval violations).
Pre-print link (Peer-reviewed publication link coming soon)
https://www.biorxiv.org/content/10.1101/2023.12.21.572882v1
# Quick-start guide
To get up and run... |
0a006ba64c1a11d26e05f55bb3aa6d148dcf230d79b4eed3ec859e7f2112394f | Text | 4,861 | 64 | # Graph Convolutional Model for Epigenetic Regulation of Gene Expression (GC-MERGE)
<img src="https://github.com/rsinghlab/GC-MERGE/blob/main/assets/model_summary_g2.png" s=400>
GC-MERGE is a Python tool that implements a graph convolutional neural network framework to integrate spatial genomic information together w... |
bc5dd2ab49a6402cfb2f739b5de1cfb44f34bfd932312fd34bfb840aefe08e67 | Text | 4,865 | 64 | # CardiacField: Computational Echocardiography for Automated Heart Function Estimation Using 2DE Probes
This repository holds the Pytorch implementation of [CardiacField: Computational Echocardiography for Automated Heart Function Estimation Using 2DE Probes](https://njuvision.github.io/CardiacField/). If you find our... |
802d0b8e9a9c4bafa8d7879d102ca97322d883e3cd86a6be0a2e068e9cd45cff | Text | 4,879 | 121 | # CrystalGenerativeModels
This is the code repository for the paper [Self-Supervised Generative Models for Crystal Structures](https://arxiv.org/abs/2312.14485).
<p align="center">
<img src="plots/results.jpg" alt="photo not available" width="98%" height="98%">
</p>
## Getting Started
1. Environment Setup: see [req... |
e6a7308d2a01620ac6ddaf97d9c03285683145b496816c2e12bcf58e050363e2 | Text | 4,890 | 52 | # Quantification & Colocalization
This repository contains the files used to quantify and analyze the colocalization of three different fluorescent markers per image of a cell culture. This works with whole folder structure, where each folder within a working directory contains the images of one cell line or treatment... |
b8c2eb5adcde6b710f388b2cd11337106c887c3d62280a6bc729681b5cccb30e | Text | 4,912 | 145 | # 💾Biomedical data compRession with Implicit nEural Function (BRIEF)
### [\<Paper Link\>](https://www.biorxiv.org/content/10.1101/2022.12.03.518948v1) [\<CUDA Implementation\>](https://github.com/RichealYoung/BRIEF_CUDA)
Welcome to BRIEF! This repository is aimed at helping researchers or developers interested in BRI... |
d5da9a2aa9b2cc19517afd3effe9a844cc98aa19a2411fd76d889d31ce9b64a3 | Text | 4,930 | 104 | KONECT-Analysis
===============
This is the network analysis component of the KONECT project (Koblenz
Network Collection) by Jérôme Kunegis.
http://konect.cc/
This is used to run analyses of KONECT networks in parallel, based on
using the Stu tool (see 'INSTALL' for installation instructions). The
code here is exec... |
9a3fba2b4d364304fc0605165ffde8f9a43fa3e2b8fada29cee0dc303f11c865 | Text | 4,934 | 96 | # Evaluating the generalizability of graph neural networks for predicting collision cross section
This repository contains code and data described in detail in our paper (Engler *et al.*, 2024).
## Table of Contents
* [Citation](#citation)
* [Reproducibility](#reproducibility)
* [Data](#data)
### Citation
If you ha... |
c47e1e8c9e38bc8358469e449f0b8553f0b07224e2b3d0ae5c35356eef906e42 | Text | 4,955 | 80 | # Steady-State and Dynamic Mass Constrained Neural Networks (MCNN)
MATLAB Codes and Python Notebooks for developing steady-state and dynamic Mass Constrained Neural Network (MCNN) models using noisy transient data
Author: Angan Mukherjee (am0339@mix.wvu.edu)
Last Page Update: Oct 10, 2024
# Announcement
We are very... |
187267ba75df36d23ff08b68a98bebaf34248a3741f79be6ba32ec681c76f70c | Text | 4,960 | 145 | # JTD-Boggle-107 atlas
## Overview
JTD-Boggle-107 atlas is a brain atlas (anatomical labels combining the individual brains, used for labeling) which is manually labeled human brain images.
This brain atlas is based on mindboggle atlas (https://mindboggle.info/) and adds/excludes some regions to define the 107... |
a5a52b3b606c46ae9039e737d4f0a271b25be4eeac4526bd6f07fed1ba08e3f6 | Text | 4,964 | 62 | <!-- badges: start -->
[](https://github.com/camaradesuk/ASySD/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->
# Automated Systematic Search Deduplicator (ASySD) <img src="man/figures/updated_logo.png" width... |
abb98bf849af49ed87e437b1bd37c52a0257dc0d2b8db993111fede73955510c | Text | 5,005 | 154 | # Prostate T2 Relaxometry using Convolutional Neural Networks
Code to develop and evaluate neural networks for parameter estimation in prostate T2 relaxometry.
This repository contains all code and models from:
**"Improved Quantitative Parameter Estimation for Prostate T2 Relaxometry using Convolutional Neural Networ... |
83e50354a83d94945e67371fdcf681e3836f2a9e333a202031fc47c4c8062027 | Text | 5,018 | 94 | <img src="dummyExperiment/img/standardized-team4.jpg" width=1400 />
# ExperimentTestingFramework
This repository contain all code used in the paper: "A standardized framework to test event-based experiments."
## Setup
The only dependency of this repository is mne python. Make sure to follow the installation guideline... |
50d091c9a906f81f87e9291bb0de3b2324bcf6e1c19e1308fd4e3172c1280633 | Text | 5,026 | 91 | <h1>
<p style="text-align:left;">
<img src="docs/docs/images/flyvis_logo_light@150ppi.webp" width="50%" alt="Flyvis Logo">
</p>
</h1>
[](https://badge.fury.io/py/flyvis)
[](https://pypi.org/project/flyvi... |
777360f96d9b8557f957a5e338eb5e0a0275c9509c6c0d3de18e9e823b64e935 | Text | 5,045 | 104 | <p align="center">
<img src="https://github.com/siapy/siapy-lib/blob/main/docs/images/logo-text.svg?raw=true" alt="Sublime's custom image" width="500"/>
</p>
<p align="center">
<em>Spectral imaging analysis for Python (SiaPy) is a tool for efficient processing of spectral images</em>
</p>
<p align="center">
<a h... |
640acf1c3f3f14c447c2a76fea280323a460e3374cf4367eb3e40ea589e29876 | Text | 5,054 | 148 | # UniFMIR
Official Implementation for "Pretraining a foundation model for generalizable fluorescence microscopy-based image restoration"
## Online Demo
We provide a live demo for UniFMIR at [http://unifmir.fdudml.cn/](http://unifmir.fdudml.cn/). You can also use the colab <a target="_blank" href="https://colab.r... |
f695553ab0be8b810d3ddb7ee48a6d34c7e6ddf83634d533abf0657613ae79de | Text | 5,054 | 87 | # DeepChrome
### Reference Paper: [DeepChrome: Deep-learning for predicting gene expression from histone modifications](http://bioinformatics.oxfordjournals.org/content/32/17/i639.abstract)
BibTex Citation:
```
@article{singh2016deepchrome,
title={DeepChrome: deep-learning for predicting gene expression from histo... |
8897f7fb553c15aa46a5bd78a977c2bdea888013bcf44a812880cdbc5603db78 | Text | 5,149 | 131 | # Dr. Probe command-line tools (drprobe_clt)
## Authors and Copyright
Juri Barthel,
Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
Copyright (c) 2008 - 2026 - Forschungszentrum Jülich GmbH
Published under the GNU General Public License, version 3,
see <http://www.gnu.org/licenses/> and LIC... |
f7cd127f6bc9dc8b56c640953aa249b441e17a18d0f6f93e13a14e74243af550 | Text | 5,153 | 146 | # SEMTor
<!--
[](https://SteffenPL.github.io/sEMTor.jl/stable/)
[](https://SteffenPL.github.io/sEMTor.jl/dev/)
[](https://github.com/brain-life/abcd-spec)
[](https://doi.org/10.25663/bl.app.43)
# app-tractanalysisprofiles
This service computes profiles of tensor (i.e. AD, ... |
94771fb12e2cea5975378c11c149afeb50f0a654d57e25bf4c8f42162e72d32f | Text | 5,159 | 127 | # MuLaNA -- Muzzio Lab Neuroscience Analysis
This is a set of neuroscience analysis codes written mostly in MATLAB. Different projects use a common set of codes and this repository is that set.
***This version of MuLaNA is used for our Cheng's Task 2C CA1 paper and will be kept frozen to not break compatibility***
T... |
127adb28b900168a58485216a3fae955f5aadcdbc335ccad4edc513e042765fd | Text | 5,216 | 92 |
2024–2025, we achieved two key milestones in intelligent crystal phase identification. We open-sourced a high-fidelity PXRD simulation package, [**PySimXRD**](https://github.com/Bin-Cao/SimXRD), and released an intelligent identification platform, [**XQueryer**](https://github.com/Bin-Cao/XQueryer). Welcome to follow... |
9e7ae30b45a046cb6718a824c9023ff3ab0754e075a586b73605263cb1247daa | Text | 5,235 | 137 | # HierarchicalConsensus
This code implements the hierarchical consensus clustering method introduced in
**Multiresolution Consensus Clustering in Networks**
Lucas G. S. Jeub, Olaf Sporns, and Santo Fortunato
[Scientific Reports 8, Article number: 3259 (2018)](https://doi.org/10.1038/s41598-018-21352-7)
[arXiv:... |
f70466e6630fd326246ad4896a46667b50b37532b8c7ff2a3e9aaecf8f5093b6 | Text | 5,241 | 105 | # cluster_diffex
Representative marker selection, cluster, visualization, and binomial differential expression pipeline reported in [Yuan *et al.* 2018](https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-018-0567-9), [Mizrak *et al.* 2019](https://www.sciencedirect.com/science/article/pii/S22111247183197... |
f8e3b2407dc9459e62ca344730a249197e8642031c4d87e0fca604ced9f14685 | Text | 5,246 | 163 | # 2023-toxoplasma_epitopes
Code for finding toxoplasma epitopes common to human brain proteins
### Description
This code can search for potentially immunogenic peptides on T. gondii (or any other organisim if the proper files are provided by the user) and then it matches them with human membrane or extracellular prot... |
e2c511c9bd8b27c2c85f1ba4c15e85d9a72e32f3425ec73ea7370764f9775aea | Text | 5,307 | 69 |
[](https://github.com/brain-life/abcd-spec)
[](https://doi.org/10.25663/brainlife.app.195)
# app-removeTractOutliers
This app uses [mbaComputeFibersOutliers](ht... |
cf135a7038af22d323aa715080cf979f08fae15eefb73b150a920062a2dcbf31 | Text | 5,350 | 79 | # Isotropic Reconstruction of Electron Tomograms with Deep Learning
# IsoNet version 0.2
[](https://zenodo.org/badge/latestdoi/222662248)
##
Update on July8 2022
We maintain an IsoNet Google group for discussions or news.
To subscribe or visit the group via the web interf... |
d25e6a175d4aad9c79c4fd9e3dee66abbd617b2b1a2502132ad6982de608e95e | Text | 5,359 | 75 | # PulseInputDDM.jl — a Julia package for inferring the parameters of drift diffusion models
A Julia package for inferring the parameters of generalized drift diffusion to bound models (DDMs) from neural activity, behavioral data, or both. The codebase was designed with the expectation that data was collected fro... |
89e264e3cb0dc3dd03f94824e654f5435247f88bea64929c97fc5a9d717be551 | Text | 5,402 | 70 | # G-PLIP: Knowledge graph neural network for structure-free protein-ligand affinity prediction
[](https://www.python.org)
[](htt... |
69f93eebc29c3b75c11a84db032a2138d475b8ef872739b0150925713042578d | Text | 5,437 | 120 | # Mothra
Molecular generation with an RNN, multi-objective tree search, QED/SA scoring,
AutoDock Vina docking and eToxPred toxicity filtering.
## Install
Use **Python 3.12.15** and a new environment. Do not install into an existing
research environment.
```sh
python3.12 -m venv .venv
.venv/bin/python -m pip install... |
d00b1c55d1482269ff0152171c6aba323a16dd49e94fe30ab3fa2cd25b6a15ab | Text | 5,454 | 95 | # Structural connectivity analysis in migraine patients
This repository provides the code used to analyze the data of migraine patients in the paper: [Involvement of the cerebellum in structural connectivity enhancement in episodic migraine](https://doi.org/10.1186/s10194-024-01854-8)
The overall pipeline can be seen... |
66cea9329f3ec01f355be932b728807fa828117dd4881455c1cd8237fca45658 | Text | 5,485 | 80 | # Steady-State and Dynamic Energy Constrained Neural Networks (ECNN)
MATLAB Codes and Python Notebooks for developing steady-state and dynamic Energy Constrained Neural Network (ECNN) models using noisy transient data
Author: Angan Mukherjee (am0339@mix.wvu.edu)
Last Page Update: Apr 11, 2026
# Announcement
We are ... |
a8cf411a572b657dfd641218e92719a3b4a0022a336929f6ce227f6b5483ac62 | Text | 5,497 | 64 | # MRI
Scripts for the paper:
A. White, M. Saranti, A. d’Avila Garcez, T.M.H. Hope, C.J. Price, H. Bowman,
Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI,
NeuroImage: Clinical (2024)
There are three folders.
* CNN training stores the scripts for traini... |
3073f7c0c639755f5eb6a5681e32d228d1e45b5518931dd6934913c345da54a7 | Text | 5,516 | 62 | # Targeted co-expression networks precisely delineate the pathways associated with the APP protein within Alzheimer's brains
## Motivation
Gene co-expression networks (GCNs) on transcriptomes are too coarse grain models to specifically investigate associations of gene expression with phenotypes of interest. Targeted G... |
0768e63eedda50dc8df92b664b4c94466525e741288ce59479278d5d62721ddd | Text | 5,529 | 161 | # 💾Biomedical data compRession with Implicit nEural Function (BRIEF)
### [\<Paper Link\>](https://www.biorxiv.org/content/10.1101/2022.12.03.518948v1) [\<PyTorch Implementation\>](https://github.com/RichealYoung/BRIEF_PyTorch.git)
Welcome to BRIEF! This repository is aimed at helping researchers or developers interes... |
809c4299fc103f77d77118d9add3211f6621d0d08c23061af11dec41649909e9 | Text | 5,544 | 148 | 
This paper explores the task of detecting images generated by text-to-image diffusion models. To evaluate this, we consider images generated from captions in the MSCOCO and Wikimedia datasets using two sta... |
aae0c0dfa7209d96b7044013c42cc69f0166f7aa8a62e7ac7c5824a3e28f07b8 | Text | 5,638 | 58 | KUOPIO GAIT DATASET
This dataset contains motion capture (3D marker trajectories, ground reaction forces and moments), inertial measurement unit (wearable Movella Xsens MTw Awinda sensors on the pelvis, both thighs, both shanks, and both feet), and sagittal-plane video (anatomical keypoints identified with the OpenP... |
edda3ecd28d6cb32559e638c56c7d28d59d6e2f9ada2dd084292c8706764bea6 | Text | 5,716 | 156 | ## Masked Autoencoders: A PyTorch Implementation
<p align="center">
<img src="https://user-images.githubusercontent.com/11435359/146857310-f258c86c-fde6-48e8-9cee-badd2b21bd2c.png" width="480">
</p>
This is a PyTorch/GPU re-implementation of the paper [Masked Autoencoders Are Scalable Vision Learners](https://arxi... |
94c3abff15a77c0df03615fdca1bf92bfd6e9d95a43d67e06f5158c5cc61913a | Text | 5,726 | 187 | **scAnnot User Documentation**
================
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
> scAnnot is a tool for performing hierarchical multi-level annotation
> of single-cell datasets using pre-trained SCANVI models.
>
> This document will guide you through the installation process, explain
> the... |
4736718328420f6160d0993386095246d1a6c71151568c4933a63b5f65ccd2d3 | Text | 5,729 | 127 | ## Find potential de novo variants in a given VCF.
de_novo_finder_3.py is a major update to the original caller. The main purpose is to
identify events that appear to be de novo in a specified VCF file that contains
sequence information from trios. Due to the nature of this variation, parents are required
to be homozy... |
50ef16352b238af81ec769b84c93259bb60a3bc5192ab6441e39497e44f2b7a7 | Text | 5,770 | 101 | # lime
[](https://travis-ci.org/marcotcr/lime)
[](https://mybinder.org/v2/gh/marcotcr/lime/master)
This project is about explaining what machine learning classifiers (or models) are doing.
At the moment... |
aa1d6b942a1c405ec4f9d2d880b25e8d610e5b2f78610ad7a10e609d46652dee | Text | 5,770 | 151 | # SNN-PCN
This is the code for the paper *Paired Competing Neurons Improving STDP Supervised Local Learning In Spiking Neural Networks*, published in Frontiers in Neuroscience ([paper link](https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2024.1401690/full)).
The proposed SNN consists of a f... |
549968838685f295850cc75acdbcbd3818bfd1008c28352626b8850cb8a0aa39 | Text | 5,781 | 100 | # Deep3P-Denoising
Deep3P Denoising: Code of the 3PM-Noise2Void and PerStruc-Denoiser Method
## Table of Contents
- [Deep3P-Denoising](#deep3p-denoising)
- [Table of Contents](#table-of-contents)
- [Dataset](#dataset)
- [Installation](#installation)
- [How-To-Run](#how-to-run)
- [Further information](#furt... |
0b84b4f5627bb993700ef490a2a3196fcfd0224e1a8651a634e2fe8146ddd777 | Text | 5,783 | 101 | # XAI-Tris
This repository contains all the experiments presented in the paper: *"XAI-TRIS: Non-linear benchmarks to quantify ML explanation performance"*.
We use `Pipfiles` to create Python environments. Our main experiments use [Captum](https://github.com/pytorch/captum), however inclusion of some methods (PatternN... |
910d5f8ac19d4ddfd0fcc77d24c9ba959675572baaed4adfe481fe2ace524479 | Text | 5,850 | 174 | # py-spinnaker2
Python interface for running experiments on SpiNNaker2 using the experiment runner
This project contains the Python code for running experiments on SpiNNaker2 or
the SpiNNaker2-FPGA prototype with the experiment runner interface.
It is required that you have access to the respective code for the FPGA... |
54ced8f5de36bee278bacf893fafcd62e4584fbfb121190393e0b1b5f9fc9e6f | Text | 5,851 | 70 | RPE_blob_analysis_pipeline.
Please cite this paper if this code is used in your study:
NOTES:
• The code was tested in MatLab 2017b utilizes MatConvNet-1.0-Beta23 developed by the MatConvNet Team (see http://www.vlfeat.org/matconvnet/).
• The code utilizes createCircleMask.m developed by Brett Shoelson (see https://... |
b6faf1f43a9de15c7ab23b9cde0986f802c68c3750300da9506c97dfe8a47726 | Text | 5,862 | 84 | # 🚀⏱️ Neural Space-time Model for dynamic multi-shot imaging
<p align="center">
<img src="assets/spacetime_cover_by_DALLE.png" alt="drawing" width="300"/>
</p>
<p align="center">
<a style="text-decoration:none !important;" href="https://doi.org/10.5281/zenodo.12786083" alt="DOI"><img src="https://zenodo.org/badge... |
eeb70317818650e5240dd7a87d407bf8911206ca42d24fd2c44e16b22fa782f9 | Text | 5,950 | 85 | # Dental Loop Signals
This software allows users to upload EMG signal images containing either unipolar or bipolar EMG signals, generate normal signals and quotients for duration/intensity. Customizable for muscle selection and activities, it provides CSVs for comparisons, especially useful when processing multiple im... |
97744121d749b5d8984fb78f98cff9ca2f34d3667bf97f0187ece157109ec1d2 | Text | 5,964 | 86 | <picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/neuromorphs/NIR/raw/main/docs/logo_dark.png">
<img alt="NIR Logo" style="width: 80%;" class="logo_front" src="https://github.com/neuromorphs/NIR/raw/main/docs/logo_light.png">
</picture>
# NIR - Neuromorphic Intermediate Representation
... |
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