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db346c521ccd2159882452f5be053ecc1d399e300993362003d952a7c68787dd | Text | 2,986 | 53 | # Overview :
LSL Kinect is a C# Program that broadcast motion capture data, on your local network, by using Kinect V2 and LabStreamingLayer technology. It also save these data under CSV files.
# System Requirements :
You must meet the following system requirements :
https://docs.microsoft.com/en-us/previous-versions/... |
60bdc4659dfec06fb773a1d9b1bad479a5bf44085682b9a8d90ffb38836f9a21 | Text | 2,995 | 74 | # "AgeingHRF" from https://github.com/RikHenson/AgeingHRF/
Derived data and matlab scripts for paper on effects of Age on HRF
The raw fMRI images are available on request from this website:
https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/
Specifically, select the "preproc_fMRI_DARTEL" images th... |
ace17a9ff42cd8eed96d36ab778b709bf88536de24d26efb5ab207997666095c | Text | 2,995 | 83 | # Fully-Gated Denoising Auto-Encoder for Artifact Reduction in ECG Signals
You can access our paper here: ([https://www.mdpi.com/1424-8220/25/3/801/htm](https://doi.org/10.3390/s25030801))
## Citation
Please use this BibTeX entry for citing our work:
```bibtex
@Article{s25030801,
AUTHOR = {Shaheen, Ahmed and Ye, Li... |
7aa926f755709eb097fb3f547362aa09f8eca193dc98ea637c6c42407d6c6eea | Text | 2,997 | 86 | # autoMEA
*autoMEA* (Automated analysis of MEA datasets) is a open-source Python package for the analysis of Micro-Electrode Array (MEA) datasets.
## How does autoMEA work?
Bursts are detected using the *Max Interval Method*. Users can manually set *Max Interval Parameters*, or can use a machine learning model that... |
86654bdf490bfa99067832cb19d2a2397e395289c060c9c0643f61ee9549b3d9 | Text | 3,004 | 39 | # Cho2024_MEEG_RSN
This repository contains the scripts and data for reproducing results in the "Comparison between EEG and MEG of static and dynamic resting-state networks" paper.
🔗 Comparison between EEG and MEG of static and dynamic resting-state networks (DOI: [10.1002/hbm.70018](https://doi.org/10.1002/hbm.7001... |
021a4d12065b41fbdec0b0cef52564dec94654c2cf63b5a3025f5eedefe393da | Text | 3,017 | 48 | # Chisco
**[Chisco: An EEG-based BCI dataset for decoding of imagined speech](https://www.nature.com/articles/s41597-024-04114-1)**
## **Abstract**
The rapid advancement of deep learning has enabled Brain-Computer Interfaces (BCIs) technology, particularly neural decoding techniques, to achieve higher accuracy and d... |
981210c54613528ae8dce9eaaeffd004029fa4f7b0688c4b49591f59f4befcdd | Text | 3,019 | 36 | # Human L2/3 Cortical Circuit Model for Therapeutic Dose Prediction of New Pharmacology in Depression --- Guet-McCreight-et-al.-2024
===================================================================================================================================================================
Author: Alexandre Guet-... |
1d59c8ef806d0ad8777c750ded2dab5adb6e02ba66d6d48205650ff1a0e13fcb | Text | 3,022 | 58 | # STR Catalogs
Short tandem repeats (STRs) are genomic sequences comprised of repetitions of a short motif (typically 2-6bp). Many STRs are implicated in a variety of genetic disorders, such as Huntington's disease, amyotrophic lateral sclerosis (ALS), and fragile X syndrome. Thanks to recent improvements in Next-Gene... |
9b87b370484a69139f55048daddcbce4bd70a5c05a947b0f476794643c800703 | Text | 3,022 | 68 | E3FP: Extended 3-Dimensional FingerPrint
========================================
|Docs Status| |CI Status| |Codecov Status| |PyPi Version| |Conda Version| |License|
E3FP [1]_ is a 3D molecular fingerprinting method inspired by Extended
Connectivity FingerPrints (ECFP) [2]_, integrating tightly with the RDKit_.
Docu... |
de49e2549c522692630f5d8abd562c2e7f2d6d77bbfb43ef8145140525c397cf | Text | 3,024 | 58 | # NEVACS
The project aims to perform NEVACS for video-activated sorting. The event stream from the event camera is received and preprocessed, and the preprocessed event image is then inferred by the spiking neural network (SNN) classification model, which is deployed on the neuromorphic chip. The classification resul... |
ae392dcd556bd5730154e2ab2931bab3ba9c11e6576dd1e86ada9174a0ac4671 | Text | 3,025 | 60 | Source code: [](https://doi.org/10.5281/zenodo.11268944)
Meshes: [](https://doi.org/10.5281/zenodo.10480303)
Results: [](https... |
335974f5c42128476bf6b73c1385004be17d881c8054c8dff9fe49c53a8a6ca8 | Text | 3,027 | 62 | # *megSAP* - Medical Genetics Sequence Analysis Pipelines
megSAP is a NGS data analysis pipeline for medical genetics, which is developed by the [Institute of Medical Genetics and Applied Genomics, University Hospital, Tübingen](http://www.uni-tuebingen.de/Klinische_Genetik/start.html) and several collaborators from... |
c4fe521ebfb08978cc8ae39d1f16cff5ddaca344b2cb470e16fe2b7d07fb07e6 | Text | 3,030 | 119 | # HPRO: Hamiltonian Projection and Reconstruction to atomic Orbitals
[](https://badge.fury.io/py/hpro)
[](https://pypi.org/project/hpro/)
[](htt... |
157ddce62d2073695af2946186861d8968f611bc0511f54085653104544c9483 | Text | 3,048 | 73 | [](https://zenodo.org/doi/10.5281/zenodo.12735192)
# scPair is a computational framework for boosting single cell multimodal analysis by leveraging implicit feature selection and single cell atlases
scPair, a deep learning framework for computational analysis of single c... |
6be9da4e6fa4f3d90a55a955995b67036503102a2a20f68d6df158bf92a340dc | Text | 3,051 | 47 | [](https://img.shields.io/github/stars/STOmics/stereopy)
[](https://pypi.org/project/stereopy/)
[
## Introduction
Squid (Simplifying Quantitive Imaging Development and Deployment) provides a full suite of hardware and software components for rapidly configuring high-performance microscopes tailored to users' applications with reduced ... |
ccf17d928e8ad990483cf6c989ce25cd6fd194584da552ee3b7c1dce083bc941 | Text | 3,057 | 57 | ===============================
HyDGL
===============================
.. image:: https://dl.circleci.com/status-badge/img/gh/uiocompcat/HyDGL/tree/main.svg?style=svg
:target: https://dl.circleci.com/status-badge/redirect/gh/uiocompcat/HyDGL/tree/main
.. image:: https://codecov.io/gh/hkneiding/HyDGL/branch/main/grap... |
2ddac950018205a6a8f93fc7a318a64c9d97e21bcb6cd898a63d4e609d74ff06 | Text | 3,058 | 22 | ## compare methods
- **GCN**：Kipf, T.N., and Welling, M. (2016). Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907.
- **GIN**: Xu, K., Hu, W., Leskovec, J., and Jegelka, S. (2019). How powerful are graph neural networks? International Conference on Learning Representatio... |
71ef725f21f47f8516bcf73261fdf78b817ec350ee1e8f2d09db3ebcf01e4658 | Text | 3,064 | 45 | # Heterogeneous and non-random cortical connectivity undergirds efficient, robust and reliable neural codes
Study of network structure and how it shapes the robustness - reliability - efficiency struggle in biological neural networks as described in this publication.
[. It uses [Syncopy](https://github.com/esi-neuroscience/syncopy) to analyze data from the [Visual Coding Project of the Allen Brain Institute](https://allensdk.readthedocs.io/en/latest/visual_coding_... |
a6be93370de14358fbf934c2f41b48b924850f5b66fb01172ec0660aa53ec8a7 | Text | 3,073 | 63 | # Code for: A Computational Framework for Understanding the Impact of Prior Experiences on Pain Perception and Neuropathic Pain
This code produces the simulation results and figures in the manuscript "A Computational Framework for Understanding the Impact of Prior Experiences on Pain Perception and Neuropathic Pain".
... |
002c6ac3b5ba04c0763e755fc99b6d4d304c3566b6ae1d4f076d2dbf84b07ed4 | Text | 3,095 | 99 | # Microsaccade Selectivity as Discriminative Feature
Microsaccade detection, feature extraction, and decoding code for Nouri et al. 2025, *Microsaccade selectivity as discriminative feature for object decoding*, iScience 28(1):111584.
## Layout
```
ms-selectivity-feature/
├── src/ see src/READM... |
bd4810ad8ac48a48a4d3f77388699c42311af0bd565cd1d21ef23aab644df3f1 | Text | 3,102 | 48 | # REPN400
Simulation code for the paper:
Nour Eddine, S.\*, Wang L.\*, Brothers T., Jensen O., Kuperberg G. (2024), _An implemented predictive coding model of lexico-semantic processing explains the dynamics of univariate and multivariate activity within the left ventromedial temporal lobe during reading comprehension... |
55da8ccf0df592548d17ad4934a53980d3c725e9983f8522498781bd28c9a6fc | Text | 3,105 | 77 | # Efficient Spatial Transcriptomic Cell Typing Using Deep Learning and Self-Attention Mechanisms
This repository is the official implementation of DSCT.
## 🚨 environment
To download and star... |
6d7baf7c96b924ac577f945335a31bd463fb2995949084fb4c1ce98bda032a12 | Text | 3,106 | 76 | # SINCS
Compressing arbitrary-dimensional biomedical images using Semantic redundancy-aware implicit neural compression proposed in our paper:(https://www.biorxiv.org/content/10.1101/2023.08.22.554284v2)
<img src="./Example/pipeline.png" width="80%"/>
## System Requirements
- Windows Server 2022 Datacenter
- Gr... |
ccd16f7b4720e74e3b1cdc8ee1b2b30737be1de175f57bd5f5e5e729caa769ef | Text | 3,118 | 37 | <div align="center">
# **How Deep is Your Art: An Experimental Study on the Limits of Artistic Understanding in a Single-Task, Single-Modality Neural Network**
[Mahan Agha Zahedi](https://www.linkedin.com/in/mahanaghazahedi/)<sup>1</sup>, [Niloofar Gholamrezaei](https://www.regiscollege.edu/about-regis/find-us/facul... |
36e5b9680c81d67b5543eedf6973c6292205cc386c2f59fee8181f9aea61995a | Text | 3,120 | 32 | # Meta_matching_models
This repo contains pre-trained Meta-matching models. If you want to train your own meta-matching model from scratch, please visit our [CBIG repo](https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/predict_phenotypes/).
## References
+ He, T., An, L., Chen, P., Chen, J., Feng, J., B... |
4209fa64f0593068ce3612c738d859b04d6173ec498f879fdbb43e80060bb551 | Text | 3,124 | 51 | # XomicsEnrich
Integration omics summary data and enrichment analysis
`Requirements`: MATLAB 2018b; SPM 12;
## Table of content
1. Use instructions and parameter selection.
2. Explanation of the output files.
3. Posthoc enrichment analysis with R code.
## 1. Use instructions and parameter selection:
Run the "Xomics... |
2dcb1453bb59968faf0657106a05149fd6602ace8bae535fa74db04d724689bf | Text | 3,127 | 51 | # mFusion
Integration omics summary data and enrichment analysis
`Requirements`: MATLAB 2018b; SPM 12;
## Table of content
1. Use instructions and parameter selection.
2. Explanation of the output files.
3. Posthoc enrichment analysis with R code.
## 1. Use instructions and parameter selection:
Run the "XomicsEnric... |
574d83b3181a8228d3432ad9d9f46bf2f99b57b025d41cb9ce42c1d832188a09 | Text | 3,137 | 31 | The following scripts were use for data analysis of bulk RNA seq datasets and single cell/nucleus RNA seq datasets analysis in the manuscript.
#For bulk RNA sequencing data analysis (both from laser capture microdissection and FACS-sorted macrophages).
Laser-capture micro-dissected muscle tissues or macrophages sorte... |
5852ada23a2f466d8e8b1bf6813c1c69870798472b4f3541e1dec3c7c8030894 | Text | 3,142 | 70 | # PilotCareTrans Net: An EEG Data-Driven Transformer for Pilot Health Monitoring
## Overview
**PilotCareTrans Net** is a Transformer-based model developed to monitor the cognitive health of aviation pilots using EEG data. This project aims to improve decision-making in health interventions by leveraging EEG data to p... |
c5a650fa532aee7b5a7fcc264a82bff768350e2c1d6e547a90a27a049b978d7c | Text | 3,147 | 31 | # PCAR
## Path-connected aggregate recognition of diffraction-limited single-molecule images
The PCAR tool is designed for simultaneous analysis of diffraction-limited single-molecule images containing single aggregates in one click.
#### **Good features of PCAR:**
1. recognises aggregates of various size and shape r... |
eeda48caa2e32f97620f594d08bc180674eb9fed4582dee5142701203054e365 | Text | 3,150 | 63 | # Data and Code for "Lateral Prefrontal Theta Oscillations Causally Drive a Computational Mechanism Underlying Conflict Expectation and Adaptation"
This repository contains data and code associated with the experiments reported in the paper *"Lateral Prefrontal Theta Oscillations Causally Drive a Computational Mechan... |
14c14bdf91e567ae540aab09068729810bf9ce3e2d4822ff03e09c90b6263298 | Text | 3,152 | 50 | <div align="center">
<img src=https://github.com/Quantum-Accelerators/quacc/blob/main/docs/images/quacc_logo_wide.png width="300"><br>
</div>
# `quacc` – The Quantum Accelerator 🦆
[](https://codecov... |
4e12d7df4037c80e07efe7898b80c24c10da0557427b7e9f0a814df743fec989 | Text | 3,153 | 45 | # Readily-interpretable deep learning translation of GWAS and multi-omics findings to understand pathobiology and drug repurposing in Alzheimer's disease
Human genome sequencing studies have identified numerous loci associated with complex diseases, including Alzheimer’s disease (AD). However, translating human geneti... |
a990949fa41cfaef5c65e153d8c02d2617cb77840a3b96e60b2e29c151666166 | Text | 3,157 | 111 | .. image:: https://raw.githubusercontent.com/giotto-ai/pyflagser/master/doc/images/Giotto_logo_RGB.svg
:width: 590
|wheels|_ |ci|_ |Twitter-follow|_ |Slack-join|_
.. |wheels| image:: https://github.com/giotto-ai/pyflagser/actions/workflows/wheels.yml/badge.svg
.. _wheels:
.. |ci| image:: https://github.com/giotto... |
627f2585ee7e498995a860fb81edee5364fb91627dc8df5f740b461b9d85ccf0 | Text | 3,161 | 84 | # meta: General Package for Meta-Analysis
Official Git repository of R package **meta**
[](https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html)
[](https://cran.r-project.org/package=meta)... |
490f302b18b4ac95bffc5ab3988d1585d567b380e7d3fe6646d984748bf33b8d | Text | 3,167 | 78 | # A novel way to gapfill metabolic models
## Installation instructions
To run the `dnngior` gapfiller, the [Gurobi](https://www.gurobi.com/) solver is mandatory.
```bash
pip install gurobipy
```
To use `gurobi`, you need a [license](https://www.gurobi.com/downloads/). If you are an acedemic, you may get a license f... |
a1ff11580b3fa52d1f0823b09e112474c943773599a9cbab9d397b05df1660ac | Text | 3,171 | 47 | <div align="center">
# Where, Why, and How is Bias Learned in Medical Image Analysis Models? A Study of Bias Encoding within Convolutional Networks using Synthetic Data
</div>
<p align="center">
<img src="figs/methods_fig.png?raw=true" width="600">
</p>
Code for layer-wise analysis of bias encoding in a CNN using... |
86c9177b8d0763609f0757826312d815532be42c81df6bfd10781d533b083ac1 | Text | 3,178 | 75 | # TargetCall
TargetCall is the first pre-basecalling filter that is applicable to a wide range of use cases. TargetCall’s key idea is to quickly filter out off-target reads (i.e., reads that are dissimilar to the target reference.) before the basecalling step to eliminate the wasted computation in basecalling. TargetC... |
f6d2ce9809540a56efb7827f8b0d4495b641bf83013ee1bee8bb1ebd80e89f99 | Text | 3,182 | 79 | # MRAi_2D: Magnetic Resonance processing with Artificial intelligence for 2D spectra
## About
MRAi is an AI-powered tool for processing Magnetic Resonance data, specifically designed for 2D NMR spectra. With it, you can perform the following tasks:
* Non-Uniform Sampling (NUS) Reconstruction (`NUS_Rec.ipynb` [Preview]... |
41b9fd82a0668eb867883e10649241a89632824b80eaf18fb73f5eb399f2a7c2 | Text | 3,184 | 70 | This is the GitHub repository for the manuscript
"**An Integrated Machine Learning Approach Delineates Entropic Modulation of alpha-Synuclein by Small Molecule**"
doi: https://doi.org/10.1101/2024.01.15.575555
This GitHub repository contains two directories : (1) variational autoencoder (VAE) and (2) denoising con... |
0ce2f694498ac4a995247a668617b4654500b472d48f4b99470bc9220980e29d | Text | 3,214 | 44 | # Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI - Software
This repository contains software to characterise the diffusion-weighted steady-state free precession (DW-SSFP) signal based on the proposed frameworks in "Tendler, Investigating time-independent and tim... |
851e202210da28c57f91be2a52bd864ae434f29bb56f3e4c5b051b891d88a250 | Text | 3,221 | 87 | # Network community detection via neural embedding
## Paper
- [Nature Communication](https://www.nature.com/articles/s41467-024-52355-w)
- [arXiv version](https://arxiv.org/abs/2306.13400)
```
Kojaku, Sadamori, Filippo Radicchi, Yong-Yeol Ahn, and Santo Fortunato. "Network community detection via neural embeddings." ... |
bd5dde9947ca3905d5e76e967f2c8d1217ddeee37438ffc69797f0d2bd5f2e82 | Text | 3,222 | 52 | # Run with python
Run app.py
----------------------
# Create .exe PupilMetrics
Create the .exe with python libraries by the command ‘pyinstaller --noconsole your/path/app.py’ (10-20 min)
Copy the content of files folder into ‘forexe/dist/app/’
The .exe PupilMetrics is at ‘forexe/dist/app/app.exe’ (you can creat... |
03d25f21e1b35fd938db4788d83a5ea99bc3e0356e256b1a0bae470cf0391b7f | Text | 3,225 | 76 | <a name="readme-top" id="readme-top"></a>
<!-- PROJECT LOGO -->
<div width="100" align="right">
<a href="https://github.com/yzhang511/inv-vae">
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://github.com/yzhang511/inv-vae/blob/main/assets/inv_vae_icon.png">
<source media="(prefer... |
309ef0fa2ec9330ddd8df8ea15bc6dd9beef38ddc18713b7786c2bca41ade8a4 | Text | 3,238 | 37 | # MeSH2Matrix
A set of Python codes for the classification of biomedical relations based on the MeSH keywords of PubMed scholarly publications
**Demo**: [](https://colab.research.google.com/github/SisonkeBiotik-Africa/MeSH2Matrix/blob/main/MeSH2M... |
fa28b21ccc9323c5df52a50d4ada4407febf6ad1b0b842ac077910551069b9c4 | Text | 3,241 | 14 | # PyTDL
PyTDL is a comprehensive Python framework designed for the modeling and simulation of biological cognitive decision-making processes. It incorporates the Temporal-Difference learning algorithm, offering a versatile tool for researchers in the field.
Licensed under the MIT License, PyTDL is compatible with Pyth... |
361b0d9df5b0051d1cbec71a961bb02a5e85cd1b2f885f2dd100305690805782 | Text | 3,243 | 56 | # FC-SC-data-pipeline
Pipeline for TVB processing for the journal articles:
- Gerard Martí-Juan, Jaume Sastre-Garriga, Eloy Martinez-Heras, Angela Vidal-Jordana, Sara Llufriu, Sergiu Groppa, Gabriel Gonzalez-Escamilla, Maria A Rocca, Massimo Filippi, Einar A Høgestøl, Hanne F Harbo, Michael A Foster, Ahmed T Toosy, M... |
18591fcd49dfefd4f2aa8dc40af2ced361d8b073ab255ec1ab62ab5c738f97c7 | Text | 3,254 | 71 | # ARC DreamCoder
> **Neural networks for abstraction and reasoning: Towards broad generalization in machines**
> *Mikel Bober-Irizar & Soumya Banerjee*
https://arxiv.org/abs/2402.03507
## Repo overview
Most of this repo follows the primary DreamCoder repo: https://github.com/ellisk42/ec.
Some helpful ARC-specifi... |
c8d4b624fabdeed4d56cd624d39565df340e9ab3877d78e9c2af6a79289746ae | Text | 3,261 | 78 | # MMDB
PCMMD: A Novel Dataset of Plasma Cells to Support the Diagnosis of Multiple Myeloma is a novel dataset of plasma cells.
This repository contains the database with annotations of plasma cells and non-plasma cells, as well as the diagnoses of 10 patients with multiple myeloma.
Original Manuscript:
> LB ANDRADE,... |
91dba72d4aeabecfdcec7bbfdfc9dcd9da8a40fd1987825f3a3fec21ea59cd1d | Text | 3,276 | 70 | Cirrocumulus
----------------
Cirrocumulus is an interactive visualization tool for large-scale single-cell genomics data, with the following features:
* Visualize datasets in h5ad_, `10x h5`_, Xenium_, loom_, Seurat_, TileDB_, or zarr_ formats
* View MERFISH_ or other spatial transcriptomics data overlaid on an imag... |
bd6d0bafa4199c1b67ae6193a814e2b16c56b855f3c494b3016ff384c603a899 | Text | 3,277 | 68 | # Ithildin C++ Framework
## Anisotropic reaction-diffusion solver
This is the Ithildin framework for parallellized simulations of excitable
media, using C++ and MPI.
## Citation
Please cite this paper when using the implementation:
Kabus D, Cloet M, Zemlin C, Bernus O, Dierckx H (2024)
The Ithildin library for eff... |
bde7e8c8a4e737a6fb75ec9a82611bb90ae240eda6f913dfce9af94345088f3a | Text | 3,280 | 58 | # scPerb
Traditional methods for obtaining cellular responses after perturbation are usually labor-intensive and costly, especially when working with multiple different experimental conditions. Therefore, accurate prediction of cellular responses to perturbations is of great importance in computational biology. To add... |
416abcdcfcea1e5000cde0b4f5165e78ff7538e37b35982c3f701d8527466322 | Text | 3,282 | 62 | # DrugDAGT
A dual-attention graph transformer framework with contrastive learning for 86 drug-drug interaction types prediction.<br/>
<br/>
Please see our manuscript for more details.<br/>
## Requirements
* python>=3.6<br/>
* cuda >= 8.0 + cuDNN<br/>
... |
e8ca7a1be0c64b8a61f8efb7ec55fb1a7f9295a0aeb3cf1507a8cd105ebe18d2 | Text | 3,284 | 88 | # Joint k-mer and variant phasing
[](https://zenodo.org/doi/10.5281/zenodo.10655504)
<!---
[](https://github.com/mrvollger/k-mer-variant-phasing/actions)
-->
This is a p... |
00264b87f83b80076eb966f5810c402e00120a48ce72649e70b2c3fd37fcd9c1 | Text | 3,285 | 75 | # Get_Properties
Workflow scripts for automated collection of molecular properties, as well as atom- and bond-level properties for a conserved moiety of interest from Gaussian jobs. Post-processing allows for the collection of condensed descriptors for conformational ensembles:
* minimum property value
* maximum p... |
33feb56a3f3b77d52df7cbed4699c22447b149e87c63585b2db540d1cf51883b | Text | 3,291 | 87 | # Phase Coupling Optimization
This implements Phase Coupling Optimization in Matlab
If you use the algorithm, please cite:
On optimal spatial filtering for the detection of phase coupling in
multivariate neural recordings. Waterstraat G, Curio G, Nikulin VV.
Neuroimage. 2017 Jun 13;157:331-340. doi: 10.1016/j.neuroi... |
fc9bda4e428beafb57198ba8bc152fa2b258e0eae4cb87eda0fedfe963a08c48 | Text | 3,309 | 57 | # Biomarker-Guided scRNA-Seq Cancer Attractor Analysis
## Overview
This repository provides code for a biomarker-guided uncovering of potential cancer attractors given a single-cell RNA sequencing (scRNA-seq) processed count matrix. The pipeline executes biomarker-oriented clustering and ellipsoidal statistics to iden... |
0d26592fc034c1ed0db7f26dab0545c93eb7725cfc8804a4d5201b90cc6ac18f | Text | 3,313 | 77 | # SCanSNP
## __Installation__
<pre>
conda create -n SCanSNP python==3.8
conda activate SCanSNP
conda install -c conda-forge r-base=3.5.1 r-ggplot2 r-mixtools r-dplyr r-robustbase r-cluster r-gridExtra
git clone git@github.com:GiuseppeTestaLab/SCanSNP.git
pip3 install ./SCanSNP
</pre>
## __Or docker image__
<pre>
d... |
08098479f4418e488a907732ce219ac3ed90b6d0fa7df2befdf456fefdfa8642 | Text | 3,315 | 70 | # Strategies for Pre-training Graph Neural Networks
This is a Pytorch implementation of the following paper:
Weihua Hu*, Bowen Liu*, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay Pande, Jure Leskovec. Strategies for Pre-training Graph Neural Networks. ICLR 2020.
[arXiv](https://arxiv.org/abs/1905.12265) [OpenRevi... |
cbf71d41da9cecfb9218e4c0707e59f2a8f444a96d3e5346c9ebab2382dcab70 | Text | 3,331 | 41 | # DeepNSD: Controlled DNN Modeling of Human Visual Brain Data
This repository contains code for the DeepNSD project, an attempt to characterize the representational structure of human visual cortex with the massive [NSD](http://naturalscenesdataset.org/) fMRI dataset and a bountiful cornucopia of deep neural network... |
03929a7e6056a64011a2179eadf0e61f3514cddb4a805f53e50d3a5ea8424cbb | Text | 3,345 | 33 | # CerviFusionNet: A Novel Multi-Modal, Hybrid CNN-Transformer-GRU Model for Enhanced Cervical Lesion Multi-classification
## Introduction
In this paper, we proposed a cervical lesions diagnosis method named CerviFusionNet, which is based on deep learning and multi-modal data. Our study represents a significant advanc... |
12a76e955ae1aef62d86973075d83773773580dee790fa1dd466d906a41b836f | Text | 3,348 | 61 | This data is generated in a reasearch regarding machine learning transition state search.
The repo contains json files corresponding to inititial transition state guess structures, optimized transition states, and corresponding reactants and products. The naming of the files contains six pieces of information.
1. R... |
e6bffc13833830689db302fdf4b783f0a892151245a0337e8cacf01209a536f7 | Text | 3,358 | 66 | # Instructions for Running Myrf_iCKO_OpticNerve snRNAseq Analysis
snRNAseq Analysis of Demyelinating Myrf iCKO Optic Nerves
This repository can be used to exactly reproduce the snRNAseq analysis done for the current publication.
Katie Emberley 10.19.2023
## System Requirements
The snRNAseq Analysis was preformed us... |
f3e1374180cc60af5313f1821f80341d04e15f72266a6e4ca85d92319a8d186c | Text | 3,358 | 69 | # PRISM-MS: Mass-Guided Single-Cell MALDI Imaging of Low-Mass Metabolites
DOI: [10.1002/advs.202410506](https://doi.org/10.1002/advs.202410506)
This repository hosts the PRISM-MS application and related resources for the study described in our publication:
**Mass‐Guided Single‐Cell MALDI Imaging of Low‐Mass Metabolit... |
ac88f34bab148cc4012436f3e5eb01ff6f045baae6be3762161c269a8fc51fa8 | Text | 3,369 | 37 | HMP
==========
> [!WARNING]
> We are transitionning to a stable version of HMP 1.0.0 by autumn 2026. There will be some bumps on the road sorry for that. The stable version 0.5.0 is usable but we recommend new users to start with the latest version as this will be closer to the future stable version (and is also the o... |
f220d077ee8d98146d953d1d7b80fd2f05265d5af20eb1bc43159fa9c011ace6 | Text | 3,369 | 161 | #Optimizer
Optimizer is a graphical tool for fitting the parameters of neuronal models
Installation
============
Get a read only copy of optimizer
----------------------------------
Install `git` and type:
git clone https://github.com/KaliLab/optimizer.git
More information on this here: http://rogerdudler.git... |
5bc9c9681942f3689e8008902f5fe227d39ad8895c9ee7a0e91d9a02260200c2 | Text | 3,375 | 99 |
treem - neuron morphology processing tool
=========================================
Module provides data structure and command-line tools for accessing and
manipulating the digital reconstructions of the neuron morphology in
Stockley-Wheal-Cannon format (SWC).
[](ht... |
ca2de25f3cf924fd75c6a6c483d40ba1fb7b1312453be9305024770fefe59804 | Text | 3,399 | 49 | # Supplemental code for "Rapid modulation of striatal cholinergic interneurons and dopamine release by satellite astrocytes"
------------------
## Contents
* [Project Overview](#project-overview)
* [Folder Structure](#folder-structure)
* [License and citation](#license-and-citation)
* [Acknowledgements](#acknowledgeme... |
71b5474e7e61e8e2c212997c0454d5ddc97d7925034a2135dcab9264b52961e1 | Text | 3,407 | 66 | # BAE-ViT: An Efficient Multimodal Vision Transformer for Bone Age Estimation
**This is an official implementation of BAE-ViT**
BAE-ViT is a novel vision transformer model optimized for bone age estimation (BAE) that efficiently integrates both image and gender information. Utilizing tokenization techniques, the model... |
16aea917afd2d22ae8773b9223d0cf923b0681bb4adaf345f760fbc076f40459 | Text | 3,430 | 86 | # stImpute
stImpute is a novel method that leverages single-cell data to predict authentic spatial transcriptomics data by integrating gene relationships. stImpute initiates the process using an autoencoder to create joint embeddings of spatial and single-cell transcriptomics data. These embeddings are then used to id... |
4aa4a04f2b31c4ef4904e09fc75c275330ccb96c8916b45ecfa0ac8dfa05ff13 | Text | 3,443 | 77 | # Get_Properties
> [!IMPORTANT]
> This repository is deprecated. Use the updated [GetProperties](https://github.com/SigmanGroup/GetProperties)
[](https://zenodo.org/doi/10.5281/zenodo.10651726)
Workflow scripts for automated collection of molecular properties, as well as... |
5e954bfd2f9075a3752996883f7acd414016ce9e51b4207ec5b284f8a19d4c9f | Text | 3,452 | 76 | Example Script Files:
accAssessmentExamples.R: calculation of accuracy assessment metrics at point locations and from raster predictions and raster labels
classificationExampleLCAI.R: complete workflow for classification of landcover.ai dataset
classificationExampleTopo.R: complete workflow for classification o... |
9935a09cba65dcbebb3efde2d2068b278715ae10f98f9faa2a960dec7a681a49 | Text | 3,470 | 85 | # HGGEP: Gene Expression Prediction from Histology Images via Hypergraph Neural Networks
For more details, please check out our [publication in BiB](https://academic.oup.com/bib/article/25/6/bbae500/7821151)
###
Spatial transcriptomics reveals the spatial distribution of genes in complex tissues, providing crucial... |
2ee27a8afceb9df573ab2c94b2cc4159a9febec3794f64b2a492e2d32c99bb04 | Text | 3,485 | 56 | # AD Progression Study
A single-nucleus transcriptomics study of 629,755 astrocytes from five brain regions of 32 donors representing the hierarchical spatiotemporal progression of Alzheimer’s disease (AD).
Link to manuscript:
Note:
Data required to run the scripts is located in the ./Example_data directory of this... |
f969dbb8d0ac5f83c73f9def3f231c302d768dd71c742ae40328f71b430728e3 | Text | 3,487 | 78 | # Quantification of calcium imaging signal
This macro aims at measuring the (F-F0)/F0 where F is the average fluorescence signal over time for predefine region of interest and F0 is the baseline.
- F0: the baseline is define as the a minimum filter of the median filtered signal
- SBR: signal to base ratio (F-F0)/F0
-... |
15f83ed9aaa3ea59aab12d203645f008244c14cffe1d388de5ffbcab6b1246c1 | Text | 3,490 | 54 | # Organ-Segmentation
## Deep Learning Multi-Modality Automated Organ Segmentation Tools
This repsotiry is about multiple organ segmentation on multi modality images.
This repository provides tools for automated segmentation of multiple organs across various imaging modalities using deep learning. All models have been ... |
41367440dee9ee1319a7244ff1c6f992571b424dfe1438aafa294679489af37c | Text | 3,492 | 55 | Code for paper Weber Zendrera, Sokolovska, Soula. Functional prediction of environmental variablesusing metabolic networks. Scientific Reports (2021)
## How to run the code
A Python2.7 environment is provided to generate the graphs, obtain the scope matrix and do the random forest analysis (**requirements2.7.txt**). ... |
8e33541a6a0cbb63d9a10be1fe83229e1bcecc3fb367c746e57aa4a8da9cae40 | Text | 3,528 | 73 | # CSearch: Chemical Space Search via Virtual Synthesis and Global Optimization
The two key components of computational molecular design are virtually generating molecules and predicting the properties of these generated molecules. This study focuses on an effective method for virtual molecular generation through virt... |
47469ccea232190616665c33bc82082bf13db8e8c402310318ddb73f0faf1cf1 | Text | 3,534 | 70 | [](https://colab.research.google.com/github/KULL-Centre/_2023_Tesei_IDRome/blob/main/IDRLab.ipynb)
[](https://youtu.be/r-eFzoBiQZ4)
[
An overview of voltage imaging data gener... |
241c72da7662056aae60ff300a2df57a199aa7c2f6cdc2ef08e018a920d9e8e3 | Text | 3,542 | 81 | # Spliceformer: Transformer-Based Splice Site Prediction [](https://zenodo.org/badge/DOI/10.5281/zenodo.14019451.svg)
Spliceformer is a machine learning tool that leverages transformers to detect splice sites in pre-mRNA sequences and estimate the impact ... |
0684fdd229b283bc172e6405a81c0ce1690d4ebf1ae707479c31bed569150b1e | Text | 3,544 | 92 | # hdpy
Repository for *HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Represenations* by Derek Jones, Xiaohua Zhang, Brian J. Bennion, Sumukh Pinge, Weihong Xu, Jaeyoung Kang, Behnam Khaleghi, Niema Moshiri, Jonathan E. Allen and Tajana S. Rosing
Link to manuscript [here](https... |
e59b219fb844f412fa0c5fd54fb7d0d85d1f12d82c4cfa89927a66629bd81f61 | Text | 3,545 | 48 | # RT-Sort
RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies
## Source code organization
This repository contains all of the code used in the development of RT-Sort and used to create the figures in the RT-Sort publication. The source code is d... |
f6f0550eae00858fb42d3bae803c54e4905d83ee4cbd1e9bb365ba53bf15d3c3 | Text | 3,545 | 113 | # TwoResNet
<picture>
<source media="(prefers-color-scheme: dark)" srcset="./figs/tworesnet_dark.svg">
<source media="(prefers-color-scheme: light)" srcset="./figs/tworesnet_light.svg">
<img alt="Shows an illustrated sun in light color mode and a moon with stars in dark color mode." src="https://user-images.gith... |
738dbbbd6ec374298c7046939837afb20736287d975707ac39c1e5828c7398ff | Text | 3,555 | 88 | # <p align="center"> Deep Learning Resilience Inference for Complex Networked Systems </p>
##### <p align="center"> Chang Liu<sup>1</sup>, [Fengli Xu<sup>1</sup>](https://fenglixu.github.io/), [Chen Gao<sup>1</sup>](https://fi.ee.tsinghua.edu.cn/~gaochen/), [Zhaocheng Wang<sup>1</sup>](http://oa.ee.tsinghua.edu.cn/~bc... |
b107c13d7e335f19b25521d7b4b62c228254a6ebf5112c230ecdae7f0218da32 | Text | 3,576 | 34 | # flywire-network-analysis
This repository contains analysis scripts for the network analyses of the Flywire connectome.
Network Paper Preprint: Lin, Yang et al. 2023, "Network Statistics of the Whole-Brain Connectome of Drosophila" (https://www.biorxiv.org/content/10.1101/2023.07.29.551086v2)
Data Paper Preprint: D... |
c66574ee93b03404564746c209b5903f1ef4120756907240ccf7973086968bdc | Text | 3,579 | 79 | # DeepH-E3
This code is the implementation of the DeepH-E3 method described in the paper *General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian* ([arXiv:2210.13955](https://arxiv.org/abs/2210.13955)).
You can find demo input files and instructions in these ... |
cfc8e6c905d76ceabec3d8aeb6c796dd379e265f878cfb149710b2bc43622456 | Text | 3,581 | 21 | Code and documentation behind the publication:
# Prediction of methylphenidate treatment response for ADHD using conventional and radiomics T1 and DTI features: secondary analysis of a randomized clinical trial
*Mingshi Chen; Zarah van der Pal; Maarten G. Poirot; Anouk Schrantee; Marco Bottelier; Sandra J. J. Kooij; ... |
dfa38dba7207a990f1e339532a19dc31dd03720dc3b39176d23bdc4312a19fda | Text | 3,582 | 55 | # EpiBERT repository
**EpiBERT** learns representations of accessible sequence that generalize across cell types via "masked accessibility modeling" which can be used for downstream fine-tuning tasks, such as RAMPAGE-seq prediction in new cell types
## dataset processing
Scripts and code for dataset processing can be... |
19954a7126437e8ecc81ad6d0c7b5bb2b6ef536c15c75f9d58c5bda696f53962 | Text | 3,604 | 114 | # OmniAnomaly
### Anomaly Detection for Multivariate Time Series through Modeling Temporal Dependence of Stochastic Variables
OmniAnomaly is a stochastic recurrent neural network model which glues Gated Recurrent Unit (GRU) and Variational auto-encoder (VAE), its core idea is to learn the normal patterns of multiva... |
134fdad7b2fd02891ead069d1dbf203808eb33e9e9655beac948f3e561095303 | Text | 3,621 | 64 | # Code and data for "A Generic Self-Learning Emotional Framework for Machines"
This repository contains the code and data to reproduce the results presented in the paper:
- **Title:** A Generic Self-Learning Emotional Framework for Machines
- **Authors:** Alberto Hernández-Marcos, Eduardo Ros
- **Publisher:** Spr... |
1b1c077d96bad22ded78eeb860baad0d5c69c66eae4fd6b25bf86d826805054a | Text | 3,624 | 109 | BEHRT federated learning Implementation of the `FederatedAveraging` algorithm.
Code of the paper: Federated Learning of Medical Concepts Embedding using BEHRT
https://arxiv.org/abs/2305.13052
**If you used our code, please cite us: **
```
@article{shoham2023federated,
title={Federated Learning of Medical Concepts E... |
f9799f658f9f6c4538c47ed2ea8f605a70acc263f2239d9129fc164056bd8099 | Text | 3,624 | 41 | # Generalized Phase
This repository contains code and demonstrations implementing the "generalized phase" (GP) representation introduced in:
> [Davis*, Muller*, Martinez-Trujillo, Sejnowski, Reynolds. Spontaneous travelling cortical waves gate perception in behaving primates. *Nature*, 2020 (*equal contribution)](htt... |
3a04c2338857881ca1946a7ec5aa254b00e39198a36bd9b97082394228735d0c | Text | 3,644 | 114 | # Dissociable contributions of the amygdala and ventral hippocampus to stress-induced changes in defensive behavior
### Pennington ZT, LaBanca AR, Sompolpong P, Christenson Wick Z, Feng Y, Francisco TR, Chen L, Fulton SL, Maze I, Dong Z, Cai DJ (2023)
*Nash Family Department of Neuroscience, Icahn School of Medicine at... |
ef9439f7d107ef96b4c82de511eca3c32d6a715277de0310f6c76e62a32fb97a | Text | 3,654 | 86 | > [!WARNING]
> The Blue Brain Project concluded in December 2024, so development has ceased under the BlueBrain GitHub organization.
> Future development will take place at: https://github.com/openbraininstitute/AstroVascPy
# AstroVascPy
AstroVascPy is... |
b0042c1eb79374ecb224759cc57c5dbbf7f6b4757450c1b9e034aa6374da8617 | Text | 3,659 | 57 | # Summary
This repository contains the code to reproduce the results of MRPA-LegNet, a variant of LegNet [doi:10.1093/bioinformatics/btad457] specifically modified and optimized for predicting gene expression from human massive parallel reporter assays in K562, HepG2, and WTC11 cell lines.
# Setting up environment
Pl... |
f45eadc5a10fcf637450f3bf387df855c0343c78a2d3f0a639a64ff8d0ab879b | Text | 3,664 | 92 | # Knowledge Graph-Driven Medicine Recommendation System using Graph Neural Networks on Longitudinal Medical Records
### Folder Specification
- src/
- dataloader.py: load the processed MIMIC-IV data for training
- KGDNet_Model.py: the full model of KGDNet
- KGDNet_Training.py: the full code for training KGDNet
... |
b0e8448fd1dbc9459db7b39c1f01f88e96db7b47960ee70fafba82d11ac9268e | Text | 3,668 | 42 | # ZeroCostDL4Mic: exploiting Google Colab to develop a free and open-source toolbox for Deep-Learning in microscopy
_**Tl;dr**_: this [**wiki page**][wikiPage] has everything you need to get started.
[](https://zenodo.org/badge/latestdoi/239971181)
## What is this?
Zero... |
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