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f059af92d6b95558da06c9b23364e5856e92f0907899a5d95aabbbd8938cff14 | Text | 3,950 | 118 | # MEA Analysis for Multi-Organoid Loop Cerebral Connectoids
MATLAB code for the Multi-Electrode Array (MEA) data analysis accompanying the paper:
> **Multi-Organoid Loop Cerebral Connectoids Exhibit Enhanced Neuronal Network Dynamics and Sequence-Specific Entrainment**
>
> Tomoya Duenki<sup>1,2,3,4</sup>, Yoshiho Ike... |
959adba1e65b2b78658cb1e4b8b530edbe9897b5c1341b96287ef98878055617 | Text | 3,952 | 123 | # Human RNA-seq processing pipeline (paired-end)
This repository contains a **reviewer-friendly, reusable, runnable** RNA-seq analysis codebase that follows the method flow described in the provided “Human RNA-seq processing” section:
- Read filtering / trimming (**SOAPnuke** as a method-matching option; **fastp** pr... |
2ffa214be4020978ee5e0215aa0ba0fa73d2ab4c4931153d086d42fd632ef2bc | Text | 3,963 | 74 | # SnakeNgs (v0.4.0)
[](https://github.com/NaotoKubota/SnakeNgs/blob/main/LICENSE)
[](https://zenodo.org/doi/10.5281/zenodo.13337082)
[ It allows for the full reproduction of the paper's results and provides a framewor... |
aece4b22bb316e2663436635f932901d24989aae00624a3e5133f19d6e5ff1c1 | Text | 3,979 | 89 | # Quality assessment of RNA 3D structure models using deep learning and intermediate 2D maps.
Overview
----
[](https://www.python.org/downloads/) [](... |
bb877a5d2bca0fdf52a7961392435e0be7596b8c8d6e08ba821e4a8faa98201f | Text | 3,979 | 77 | # HeMoVal Analysis Code
This repository contains the full analysis code for the **HeMoVal study**, a preregistered multicentre prospective observational cohort study of patients with aneurysmal subarachnoid haemorrhage.
The primary analysis was conducted strictly according to the prespecified Statistical Analysis Pla... |
d35cfa30b7250238031f5e10e2ae34af1771d73da8184643bce0a18d96886659 | Text | 3,981 | 89 | # Quality assessment of RNA 3D structure models using deep learning and intermediate 2D maps.
Overview
----
[](https://www.python.org/downloads/) [](... |
aa893db7feddea3d7a19a421ca433bfd8090a43ada31c8c4c6140cb2b8fdf765 | Text | 4,037 | 129 | # Image Analysis Pipeline Using Cellpose and FIJI
This protocol describes a semi-automated image analysis workflow for extracting quantitative data from microscopy images using segmentation masks generated by [Cellpose](https://www.cellpose.org/) and custom macros in FIJI/ImageJ. The pipeline enables robust cell-level... |
700b05d7ab3ccd2b17aae5a7993af3eb8bd9d78d5122d9212f92c66d100ed113 | Text | 4,066 | 103 | # Interpreting-ANNs-for-GWAS
## Description
This is the repository with code explained in the manuscript "[Interpreting artificial neural networks to detect genome-wide association signals for complex traits](https://arxiv.org/abs/2407.18811)". This repo is still work in progress and will be updated with more details ... |
b562ae0f5f617d983de8e86eccb0e770ac1ad2474bcf1127aa47ba9758c73610 | Text | 4,066 | 50 | # Code used for the decoding analysis and data loading/analysis/plotting in the Ribeiro et al., Critical Scaling of Novelty in the Cortex, Nature Communications, 2025.
Below is a brief summary of the Python and MATLAB scripts posted in this repository.
### pstimutils.py
This is the main utility library for loading, h... |
da1e902eceeca11e485ccc7e7dda2075fd8208a61251d4042562e3a1cfab0c2e | Text | 4,072 | 153 | # SuperlinearAssociativeMemory
Codebase for hardware-adaptive learning in memristor-based associative memory with a multilayer structure.
This repository accompanies the paper:
**A Hardware-Adaptive Learning Algorithm for Superlinear-Capacity Associative Memory on Memristor Crossbars**
---
## What’s inside
- **Ha... |
efa96836c3975f7ce59dd5d7b61ffc4ec155e030e13ab6c38cd9a3aab909e355 | Text | 4,085 | 84 | # OPERA
OPERA is a free and open-source/open-data suite of QSAR models providing predictions on physicochemical properties, environmental fate and toxcicity endpoints as well as additional information including applicability domain and accuracy assessment. All models were built on curated data and standardized QSAR-rea... |
bfa2c2709882534df76cd0f1bba88e0197ad0449dcd270e328a28e6efb714fb9 | Text | 4,102 | 92 | # GEASO
#### Source code and detailed tutorials for "Network model for alignment, stitching and slice-to-volume 3D reconstruction of large-scale spatially resolved slices"
#### Yu Wang, Zaiyi Liu, Xiaoke Ma
Here, we introduce GEASO (Graph-based Elastic Alignment for Spatial-Omics data), a network-based framework fo... |
7377834179b2f8c480fc50e2e956b66e046836c0089a3d769307ab05260b7cb0 | Text | 4,108 | 130 | # SurfaceVolumeMeshingToolKit
Surface Volume Meshing Toolkit (SVMTK) is a Python frontend for specific 2D and 3D mesh generation methods in the Computational Geometry Algorithms Library [(CGAL)](https://www.cgal.org/).
SVMTK was designed to create volume meshes of soft organic tissue surfaces, like the human brain, w... |
d5ff90f9b382e23191b4c37e8560f886cf2916a585b0ae6cfaffcbb749514688 | Text | 4,113 | 66 | **This repository contains the instructions and material to reproduce the analysis reported in the article :**
# Ectopic expression of BEX genes in T-cell Acute Lymphoblastic leukemia
Authors : Quessada Julie<sup>1,2*</sup>, Nozais Mathis<sup>1*</sup>, Grosjean Clémence<sup>1</sup>, Pankaew Saran<sup>1,3</sup>, Sara ... |
c2138659888615da94b4a9f5b1148e2dbe556115bba932bc2c79f418000ac6bc | Text | 4,124 | 92 | # GEASO
#### Source code and detailed tutorials for "Network model for alignment, stitching and slice-to-volume 3D reconstruction of large-scale spatially resolved slices"
#### Yu Wang, Zaiyi Liu, Xiaoke Ma
Here, we introduce GEASO (Graph-based Elastic Alignment for Spatial-Omics data), a network-based framework fo... |
4034f8652e63930d2fa6af51e0281ae0be34c11600f3eca4efa27f95d22b85cf | Text | 4,133 | 43 | # ScoreREM: A user friendly Matlab-GUI for rapid eye movement (REM) sleep microstructure (Phasic/Tonic) annotation and quantification
**Licence:**
ScoreREM Copyright (C) 2024 Kiran K G Ravindran. Refer to the License.txt for more details.
## Overview
ScoreREM is a user-friendly Matlab GUI that allows rapid ... |
05258d5a45e02c07ee76efea844c1a45336ed07be8e4c5735673fed8dfa69901 | Text | 4,149 | 40 | # MEmilio - a high performance Modular EpideMIcs simuLatIOn software #
[](https://github.com/SciCompMod/memilio/actions/workflows/main.yml)
[](https://opensource.org/licenses/MIT) [. See also https://github.com/sitiny/BRIC_TUS_Simulation_Tools.
## Platform
Tested on Linux (Ubuntu 20.04.4 LTS) and on macOS Catalina (10.15.7; Intel i5... |
935ca37dab4d45c5f4a7b9a47f3581687b323bb73089fce662edea388bc45102 | Text | 4,168 | 19 | # Predicting Cellular Drug Responses Over Time with Signaling-Guided Recurrent Neural Networks
## Short Background
Protein phosphorylation is a reversible post-translational modification (PTM) that plays a role in propagating signals through the molecular networks of the cell. In mammalian cells, this process typicall... |
562f3acc25940730186b3c0003be0d2dcaf30084ed2a8a5c1c0cc4c580694917 | Text | 4,173 | 90 | # *A molecular map of the living human brain from quantitative MRI*
Can we infer molecular information from quantitative MRI imaging using spatially resolved transcriptomics? This is the question we set out to answer in our pre-print (https://doi.org/10.1101/2025.09.24.678316). This repository contains all the code re... |
b41f96d2f066e59dd46a08fe699d2b6b6b8ccedb4d4ba2fd536cba8f63e0bf14 | Text | 4,185 | 54 | ### TwiBot-20 Dataset
#### Introduction to TwiBot-20
TwiBot-20 is a comprehensive sample of the Twittersphere and it is representative of the current generation of Twitter bots and genuine users. It is naturally divided into four domains: politics, business, entertainment and sports and each user has semantics, proper... |
c3d35cfb0342c472dc3277e026a48710290847f49fb33b20bf245573a6faddfb | Text | 4,207 | 139 | % PARACLU Paraclu User Manual
% Martin Frith
NAME
====
paraclu - finds clusters in data attached to sequences
paraclu-cut - subset the output of paraclu
SYNOPSIS
========
paraclu [*minValue*] [*my_input*] > [*my_output*]
paraclu-cut.sh [*my_output*] > [*my_cut*]
DESCRIPTION
===========
Paraclu finds clusters in... |
f6bee27dfa63c627aca8af322fd6c52eb9c2b56738ab9fa0cb1a985b25356e6c | Text | 4,211 | 44 | ## DyeDactic: learning colours
--- -
[](https://www.gnu.org/licenses/agpl-3.0)
A colour prediction workflow for biosynthetically produced dyes and pigments.
A code repository to reproduce the results published by [Karlov et al.]()
## Command ... |
330412b5e9f0fea6ab85c325dcb4a3a0cf87f8fcce1ce5cbb242dbd5076d98bc | Text | 4,212 | 40 | # MEmilio - a high performance Modular EpideMIcs simuLatIOn software #
[](https://github.com/SciCompMod/memilio/actions/workflows/main.yml)
... |
5281da7b1638c894255d79d5c5cbe5e949afe2f8e6c846a096a0ab688ae9e66c | Text | 4,213 | 53 | # Hierarchy and MIND in schizophrenia spectrum disorders (SSD)
This repository contains code and data created in support of the project García-San-Martín, N.; Bethlehem, R. AI; Sebenius, I. et al. *"Long-term morphometric similarity gradients relate to cortical hierarchy and psychiatric symptoms in schizophrenia"* med... |
6accc9eefdb1e4ceda94aca915257971aeabbed627fef6c1b89f98ef5918d612 | Text | 4,214 | 82 | # Miller 2025 TMS Coupling
### Authors
- Aaron Miller, miller@cbs.mpg.de
- Konstantin Weise, kweise@cbs.mpg.de (main contact)
- Torge Worbs, torwo@dtu.dk
## Cloning Repo
```
cd existing_repo
git remote add origin https://gitlab.gwdg.de/aaron.miller/miller-2025-tms-coupling.git
git branch -M main
git push -uf origin m... |
d80acc07f100f76b4bc20c01168d04d5351cf945b31bde1c920d6b620e777f5e | Text | 4,216 | 98 | graphpancake
==============================
[](https://github.com/sneha-sil/graphpancake/actions?query=workflow%3ACI)
[](https://codecov.io... |
a376eff67ce0713c3462e5bb8bafbbfdb3f31ec99c191e3ad97d04a7016f0f9d | Text | 4,221 | 97 | # CAMEX
## Overview
Single-cell RNA-seq (scRNA-seq) data from multiple species present remarkable opportunities
to explore cellular origins and evolution. However, integrating and annotating scRNA-seq data
across different species remains challenging due to the variations in sequencing techniques,
ambiguity of homo... |
f1a95bd2eae968f27203578261b95a26e1f98eb1cfcd4a6184e3f0fcc167ac40 | Text | 4,222 | 72 | # CarcGC
=====
### Carcinogenicity prediction model based on interpretable graph convolutional neural network
<br>
CarcGC is a graph convolutional network for chemical carcinogenicity prediction. It takes chemical structure as inputs and predicts the chemical carcinogenicity (binary classification)... |
05672755767295f591e9b1c2b53a0a2af43c11b8c864dcd18e2c54747eb28612 | Text | 4,227 | 221 | ## Machine Learning Models for Predicting Mechanical Properties of Gypsum-Based Composites
## This repository presents a comprehensive machine learning framework for predicting:
Compressive Strength (MPa)
Flexural Strength (MPa)
of gypsum-based composite materials reinforced with wheat straw and chemical additives.... |
f07de3324bbf1419b2242dc7aed899c37c013ae94c3532a4d37ac2b089b479c7 | Text | 4,255 | 73 | # NeST
[](https://zenodo.org/badge/latestdoi/631040801)
## Analysis of nested hierarchical structure in spatial transcriptomic data
Please see our manuscript at [https://www.nature.com/articles/s41467-023-42343-x](https://www.nature.com/articles/s41467-023-42343-x).
##... |
a7850b2ebb332eed5103f1a3b6730dc27c27ede737a0b0d5c546a113eae9aa03 | Text | 4,271 | 102 | # napari-debcr
<!--
[](https://github.com/DeBCR/napari-debcr/raw/main/LICENSE)
[](https://pypi.org/project/napari-debcr)
[ to get updates.
## News
- 2025.04.07: Release [MedSAM2](https://github.com/bowang-lab/MedSAM2) for 3D and video segmentation.
- 2025.02: Welcome to join CV... |
904b00df4bc32f53c02a3b757d8e3b08a158f4079f33cd678b4b5fabb026fa8d | Text | 4,295 | 38 | # Pipelines + statistical and visualization scripts
This repository presents analyses for the manuscript
*Loss of SETDB1-mediated H3K9me3 in human neural progenitor cells leads to transcriptional activation of L1 retrotransposons*
## Organization
- `Bulk` - Containing all scripts for bulk RNA sequencing and CUT&RUN ... |
17d2dc8da4ea801d3b5dab4f063d8cb3371254558667a63ac5155f6ab842204f | Text | 4,298 | 162 | # ChAT Detection Training
Training code for a TensorFlow/Keras attention U-Net model for ChAT band segmentation. The script trains on paired `.tif` image patches and mask patches, with two output mask channels corresponding to ON and OFF bands.
## Supported Platforms
Supported:
- Linux
- Windows using WSL, preferab... |
0f48d8474707b6172e1271b28a8803fbfcb3080a03b7d879cb9ccb2155fa634d | Text | 4,310 | 43 | # DBS fMRI Reproducibility Repository
This repository contains de-identified example data and resources for assessing the reproducibility of resting-state fMRI (rs-fMRI) scans in Parkinson's patients who are receiving deep brain stimulation (DBS) therapy. It includes code and patient-derived, de-identified data for an... |
cc9943e36c5c1ba691d97a229247bf15c2fe81ae98a0aeeace21d1998db56ca1 | Text | 4,313 | 85 | # Nuc_fluor_Fiji_R_025
Simple nuclear fluorescence intensity image analysis pipeline in Fiji and R
Fiji/R nuclear fluorescence intensity analysis pipeline (v02.5, 5/5/23)
Pipeline usage overview (steps):
1) Basic image read, processing and ROI measurements
2a) (optional): Extract images for presentation
2) Read ROI ... |
8f0dbc221c2d381353077448e662dacdc9978580e192992392cb9bea91e3d6f6 | Text | 4,315 | 72 | # Highly Efficient Imaging Genetics (HEIG)
HEIG is a comprehensive toolbox for efficiently conducting joint analysis for large-scale imaging and genetic data, which includes Representation learning-based Voxel-level Genetic Analysis (RVGA) and Representation learning-based Voxel-level Rare Variant Analysis (RVRVA). Com... |
8979997c4b8b483e184095f8b853dfea3bf4094c5b95a67a6cc5611fe9a2ada7 | Text | 4,347 | 76 | # Single-cell analysis of heart organoids
[](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE309829)
[](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1356374)
🫀 Pipeline for... |
532caf3ea2d0479681afbb91371237701038a3184d5d1876dac60fce2cd8d598 | Text | 4,354 | 88 | ## Lesion Mapper
T2 FLAIR lesion volume is an important biomarker in aging and pathophysiology. The purpose of this software is to provide an easily usable and openly accessible method for quantifying lesions from MR images that does not require manual adjustments or multiple contrasts. The tool is provided as a BIDS-... |
f4d1f7d5cae6c33bb2412b383863990b5a4ce0aa187e8ea25b73edf84b9f9f24 | Text | 4,359 | 143 | # TWOM - Threshold-Weighted Overlap Mapping
Vectorised, command-line Python implementation of TWOM for characterising individual variation in neuroimaging. Quantifies spatial overlap across multiple statistical maps.
## Quick Setup
```bash
git clone https://github.com/oiwi/twom.git
cd twom
chmod +x create_env.sh
./... |
b6a24f0fa6763d78aaf60c943d059cb4300e795d1c24d263f5ad13107d2ba650 | Text | 4,363 | 81 |
## BAMboozle.py: de-identification of sequencing reads
**BAMboozle.py** is a tool that can remove genetic variation from sequencing reads stored in BAM file format to protect the privacy and genetic information of donor individuals.
## Installation
BAMboozle.py is available through PyPI. To install, type the follo... |
23e6de2629dc3248e2f85ffb727c035198e2204f5d7714a84d94fcb22fc6f7f8 | Text | 4,364 | 107 | # B97 and D4 Linear Parameter Optimizer
This project implements a multistart optimization framework for computational chemistry applications. The program optimizes linear parameters for the B97 functional against GMTKN55 and integrates external dispersion energy calculations via the DFTD4 program. It reads test set da... |
19d15b13fe1cd9ef8ef06ab363b2a01ee2415e8e156da04492ba11320b065766 | Text | 4,370 | 130 | # iTReX: interactive Therapy Response eXploration
## Overview
_iTReX_ is an R/Shiny web application for interactive analysis, visualization and exploration of mono- and combination therapy dose response profiling data and drug target interaction network mapping.
iTReX features an extended version of the drug sensitiv... |
b4554ef24bc09dfa1a9595fbcf452ac88a841ee4b1ac64b93f367909dec77db3 | Text | 4,390 | 50 | # The EEG-IP-L Pipeline
**This Project is no longer supported in MATLAB**: Instead, please use the [Python version of this pipeline](https://github.com/lina-usc/pylossless)
# Documentation
A reference manual for the pipeline can be found on the [Wiki](... |
908e5efe756c4282ae5207ec3515c2d5bc2575ca141c667c22066f2652596ec3 | Text | 4,393 | 98 | # Analog-aware NAS Works
## Description
Recent updates:
* **AnalogNAS-Bench**:** We have integrated AnalogNAS-Bench, a dedicated NAS benchmark tailored specifically for Analog In-Memory Computing (AIMC). This benchmark enables fair and systematic comparisons of NAS methodologies under realistic AIMC conditions, p... |
cf2d89b74cb4d68d604b3087c5f7c780ad812769c30c5867d634a331064df33c | Text | 4,401 | 66 | # Readme.md
## Overview
This repository contains the source code and data for our research on a highly energy-efficient multi-core neuromorphic architecture designed for training deep spiking neural networks. The project is divided into two main directories: `code` and `data`.
## Code Structure
The `code` directory... |
c9cd89cdaaa94c87a5c050e09dd228ce5134f723c6476bfb4315a04a69476e89 | Text | 4,408 | 129 | .. -*- rest -*-
.. vim:syntax=rest
==========
gradunwarp
==========
gradunwarp is a Python/Numpy package used to unwarp the distorted volumes (due to the gradient field іnhomogenities). Currently, it can unwarp Siemens data (and GE support very soon).
Installation
============
Prerequisites
-------------
gradunwar... |
3ff3c8c545e9b18ae2d67b33600114476ca883e35d45e7e8493956625b5979d5 | Text | 4,411 | 99 | 
A **Dynam**ic Programming Approach to Segment **ONT** Signals.
Dynamont is a segmentation/resquiggling tool for ONT signals.
Dynamont was tested on
* RNA002
* RNA004
* DNA R10.4.1 5kHz (I applied the trained transition parameters from the RNA004 model to the DNA R10 models. These should ... |
8b28c2ed65f99016c925d9613d86021505d415b8b6e18ab7dc9402e6b92eda63 | Text | 4,426 | 66 | # Precomputed Numerical Green Function Method:<br/>Near real-time full-wave electromagnetic inverse design
This repository contains code to precompute the numerical Green's function (NGF) matrix and perform optimization utilizing the PNGF method and direct binary search as described in the paper "Near real-time full-w... |
f34892d5902a9c3cd9d3e18a7ce2103371f0bdab8862e2aa048ed8c3a3277168 | Text | 4,430 | 109 | # RG-NFT — analysis pipeline
Code accompanying *How Far Ahead Is Driver Drowsiness Predictable? A Two-Corpus
Participant-Independent Evaluation of Multimodal Fusion and Reliability Gating*.
Every table and figure in the paper is reproducible from this repository plus the
two public datasets named below. `results/tabl... |
aafb7aeb4aff897bcea560451dc06fd1979b0967c9f05317bd7855ff9f796ac9 | Text | 4,476 | 100 | This library will efficiently generate visual stimulus videos using Perlin noise, including zebra noise. The core algorithm is in optimized C.
[Example zebra noise](http://www.youtube.com/watch?v=-SyjgbNCP4Q)
[](http://www.youtube.com/watch?v=-SyjgbN... |
e57ff9ff5a7d89ab1c4761d0b5f44fc3bc1f1e7268bd69ed8003ed2dd83d5a7d | Text | 4,481 | 135 | # Image Analysis Pipeline Using Cellpose and FIJI
This protocol describes a semi-automated image analysis workflow for extracting quantitative data from microscopy images using segmentation masks generated by [Cellpose](https://www.cellpose.org/) and custom macros in FIJI/ImageJ. The pipeline enables robust cell-level... |
a0a254f2abb65d418ce249c38643b8cdc482ea59ad2a20ed2f0eabb96f59e8f8 | Text | 4,503 | 72 | ------------------------------------------------------------------------------------------------------------------------
# Glioblastoma stem cells show transcriptionally correlated spatial organization
----------------------------------------------------------------------------------------------------------------------... |
15f514be673a26022ba82c0816a5eee4331db796b37a8f1997d17af7fdda697f | Text | 4,518 | 113 | .. -*- mode: rst -*-
|
.. image:: https://badge.fury.io/py/yasa.svg
:target: https://badge.fury.io/py/yasa
.. image:: https://img.shields.io/github/license/raphaelvallat/yasa.svg
:target: https://github.com/raphaelvallat/yasa/blob/master/LICENSE
.. image:: https://codecov.io/gh/raphaelvallat/yasa/branch/mas... |
bbe4ac2658731103e1b7bfa73a446e281ca9e9004313c81db6217da33e0563a7 | Text | 4,531 | 108 | # ContentContextNeurons
This repository contains code and data accompanying the following paper:
### Distinct neuronal populations in the human brain combine content and context
Marcel Bausch<sup>1</sup>, Johannes Niediek<sup>1</sup>, Thomas P. Reber<sup>1,2*</sup>, Sina Mackay<sup>1</sup>, Jan Boström<sup>3</sup>,... |
6c7983726cdd9a584e800cf3622c3fe73bc113ea8d2bed9c12956bab7bb9e52e | Text | 4,547 | 41 | # Contextual RL
Algorithm implementation, data and analysis code for Passlack J & MacAskill A (2025) Contextual inference through flexible integration of environmental features and behavioural outcomes. *bioRxiv* doi: https://doi.org/10.1101/2025.05.28.656607
## How to use
Details of anaconda environment used in requ... |
603bb1e06d495b70dfdd8df22337e919f567ed75f3b0c97089d160c7b555f5a4 | Text | 4,556 | 68 | # Drawing ROIs without GUI
Drawing ROIs with a non-graphical user interface in Matlab
Drawing ROIs is a repetitive task when analyzing calcium imaging data. Despite automatization attempts (e.g., http://neurofinder.codeneuro.org/), in many cases drawing the ROIs manually is still the best solution. This script tries t... |
43bbc1f1f3706e55700126b71a3c644b31ce9a284621fa4025f5be4ff07c3d49 | Text | 4,574 | 78 | # FC-SpatialHeterogeneity: Spatial Heterogeneity and Subtypes of Functional Connectivity Development in Youth
[](https://doi.org/10.1101/2025.01.24.634828)
[![License: MIT](https://img.shields.io/badge/License-MIT... |
b98e41a266126c8b6054a36bac7b16304df2ae4aad07af03f94074d8b82c89fd | Text | 4,579 | 68 | # Aperiodic parameters of the fMRI power spectrum associate with preterm birth and neonatal age
Machine learning regression analysis predicting neonatal postmenstrual and postnatal age from aperiodic offset and exponent parameters of the resting-state fMRI BOLD signal
## Description
This repository provides code for... |
9bd68f944654bc3a4f4df44ed265be5494dce191d9def57a6e7b6c529417d938 | Text | 4,585 | 84 | <div style="padding-top:1em; padding-bottom: 0.5em;">
<img src="src/comet/data/img/logo.svg" width =130 align="right" alt="logo"/>
</div>
# The Comet Toolbox: Multiverse analysis for neuroimaging
[ and PEB analysis of resting-state EEG in long-term meditation practitioners (focus on DMN & SN).**
This repository contains the MATLAB source code used for the effective con... |
13115b6799f5592f5cba1ab8c0b86d0eb9c33cbd9b853c0306a0eb7d855a5312 | Text | 4,620 | 129 | A Multi-plex Visual Search Engine (mViSE) for Brain Tissue Image Analysis.
@copyright University of Houston, Electrical and Electronic Computer Engineering Department, Roysam Badri, Farsight group.
# Paper
[](https://https://github.com/RoysamLab)
##... |
8adde24285e8243d2784e45a620a4ced652057bd7bc7c168e244eae3a4b99872 | Text | 4,622 | 90 | Readme
Open Data Repository
******************************************************************************************************************
Manuscript information
******************************************************************************************************************
2-Deoxy-D-Glucose chemical exchange-se... |
69d130f8b484f42800494f18dc6dec31f73cab479aa3a93ca31276658dc45d99 | Text | 4,635 | 94 | # SpaGCN v1.2.7
## SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network
### Jian Hu*, Xiangjie Li, Kyle Coleman, Amelia Schroeder, Nan Ma, David J. Irwin, Edward B. Lee, Russell T. Shinohara, Mingyao Li*
SpaGCN i... |
280694333045b77af73e38ee209fef8ae18016906b0fb06ff3f1c8da4f384a38 | Text | 4,638 | 90 | Readme
Open Data Repository
******************************************************************************************************************
Manuscript information
******************************************************************************************************************
2-Deoxy-D-Glucose chemical exchange-se... |
7947bfd3af75d7fdeeb627ad28bf7903456c684d7e0edfa745bc8ba7dbb39cb1 | Text | 4,643 | 106 | <h1 align='center'>ISAT_with_segment_anything [isat-sam]</h1>
<h2 align='center'>An Interactive Semi-Automatic Annotation Tool Based on Segment Anything</h2>
<p align='center'>
<a href='https://github.com/yatengLG/ISAT_with_segment_anything/stargazers' target="_blank"><img alt="GitHub forks" src="https://img.shield... |
33b327888d3138ef98886561332d9a7b1e64ca9d9526c5f145c8425e74b62a94 | Text | 4,687 | 89 |
# README for Synthetic 2D XRD Patterns Dataset
## Overview
This dataset collection comprises synthetic two-dimensional X-ray diffraction (2D XRD) patterns
generated from Crystallographic Information Files (CIFs) sourced from the Inorganic Crystal Structure Database (ICSD) \[Belsky et al., 2002].
The origi... |
5a73d5883e0bc97fcf91164c53dcc6cfb99038bc98655f515b207c82de3b3653 | Text | 4,688 | 128 | # Equivariant Graph Mechanics Networks with Constraints (ICLR 2022)
Wenbing Huang\*, Jiaqi Han\*, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang
[](https://github.com/hanjq17/GMN/blob/main/LICENSE)
[**[OpenReview]**](https://openreview.net/forum?id... |
6200644d66402df24a82d13644e6cf742fc36480d7e63362b08bbb473a853b82 | Text | 4,701 | 56 | **BioDecoder — A Universal Platform for Electrophysiological Signal Classification and Biological Interpretation**
**Project Overview**
BioDecoder is a universal platform dedicated to the analysis and biological interpretation of electrophysiological signals. It performs automated signal classification and deciphers e... |
21132ac4c664ae2f75432ee2e0c1c8d13cf7d8a8438fe89d405dee25aab05334 | Text | 4,708 | 100 | # Visual Imagery EEG Dataset
## Overview
This dataset contains EEG recordings collected from 22 participants performing visual imagery (VI) tasks involving three categories: animals, figures, and objects. Each subject participated in two sessions (ses-01, ses-02), where they were instructed to vividly imagine the... |
afe2e617f5d8619c8f670df63af78f936efedc7a6e1d47361d8d56d035721761 | Text | 4,723 | 131 | # JanusDDG
<img src="./images/JanusDDG_image.png" alt="JanusDDG logo" width="500">
Instructions for using the protein stability prediction tool presented in the paper titled *JanusDDG: A Thermodynamics-Compliant Model for
Sequence-Based Protein Stability via Two-Fronts Multi-Head
Attention*. [ArXive](https://arx... |
850213fca395ad6895b2b4e7f373a1c97cbbb63501be53d6ec742bb1dbd97483 | Text | 4,753 | 63 | # FetMRQC SR
[FetMRQC SR](https://arxiv.org/abs/2503.10156) is the super-resolution extension of FetMRQC [[paper1](https://arxiv.org/pdf/2304.05879.pdf),[paper2](https://arxiv.org/pdf/2311.04780.pdf)] is a tool for quality assessment (QA) and quality control (QC) of T2-weighted (T2w) fetal brain MR images.
It builds... |
237ffb6601ebdfa330c3ba723205a650d8254b42fc08337cf5f056a86bd6e6a0 | Text | 4,755 | 91 | # Combining federated learning and travelling model boosts performance and opens opportunities for digital health equity
<div align="center">
</div>
<p align="center">
<img src="Fig1.png?raw=true">
</p>
Implementation for decentralized quality control that is published by the npj Digital Medicine: "Combining fede... |
565a6241681d9ca949127873381f72b88b90e2fca37618eb97b97ef765b4c03a | Text | 4,760 | 122 | ## 项目概述
本项目实现了用于水平斜视手术剂量预测的多输出深度回归与多标签分类模型，覆盖数据预处理、模型训练、超参数搜索、交叉验证、Bootstrap 不确定性评估及推断流程，旨在为临床提供高精度的手术规划辅助工具([docs.github.com][1], [github.com][2])。阅读本 README 可快速了解项目功能、环境搭建、使用方法及代码结构([makeareadme.com][3], [hackernoon.com][4])。
## 目录
* [功能亮点](#功能亮点)
* [环境与安装](#环境与安装)
* [数据预处理](#数据预处理)
* [模型结构](#模型结构)
* [训练流程](#训练流程)... |
2d4aad2ab696aa354045f28a7d44d0ce837840c505f80656b7c6aa33851432c7 | Text | 4,784 | 83 | # Brainways
[](https://doi.org/10.1101/2023.05.25.542252)
[](https://github.com/bkntr/brainways/raw/main/LICENSE)
[
InsightGWAS is a Transformer-based deep learning framework designed to prioritize genetic variants associated with complex diseases using **genome-wide association studies (GWAS) summary statistics** and **multi-moda... |
b09d8d4d44ef0123b0a1121c6695508d9ee5c53f5aa167cae6c5cf06a5389e12 | Text | 4,828 | 39 | # CorticalNeuropixelProcessingPipeline
This is code and instructions for the exatraction of the Neuropixels LFP data to then perform manual tracking and interpolation to adapt to movement artifacts in human Neuropixels recordings for the paper: "Large-scale recordings of individual neurons in human cortex using high-... |
21193b3cfa8003631a68a47b83f8a3ef4ddc927fd01b51f15c136d16e5bf3b84 | Text | 4,835 | 107 | # **BioLM-NET**
## BioLM-NET: An interpretable deep-learning model combining prior biological knowledge and contextual LLM gene embeddings on multi-omics data to predict disease.
## Overview
Biologically informed deep neural networks which connect input features to hidden layers based on known gene–pathway relation... |
f8d96618363b54147dd6f85f59b6f30be2846017219bb1b07624b1cb57a73203 | Text | 4,836 | 162 | # ``BrainTrace`` experiments on spiking neural networks
## Requirements
```bash
pip install BrainX[cuda12]
# or
pip install BrainX[cuda13]
pip install h5py matplotlib msgpack tonic prettytable
pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
```
## RSNN long-term dependency eval... |
7f5102591205a40d6e7a698820f31c48464e11985c13408580ade7eb9cd5285a | Text | 4,837 | 86 | ##### FEDERATED LEARNING FOR THORACIC DISEASE CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORKS AND DIFFERENTIAL PRIVACY ####
This repository consists of two distinct experiments which are; -
1. Federated Learning on CheXpert with EfficientNet-B3
2. Federated Learning with Differential Privacy on CheXpert
Each exper... |
2e2ef8404b6d708026f30d968c4041af8fc68b2f9bdab04b7b2cee97efa8047a | Text | 4,846 | 75 | <div align="center">
<pre>
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███████... |
b8152d04c5239a3f5e7879b2422219120ca9a5200d886463ccf03f2e095074a8 | Text | 4,849 | 111 | # DinoTracker
App for dinosaur footprint analysis via disentangled variational autoencoder.
Youtube DinoTracker mini-doc (English): https://youtu.be/ZbGp8tIOfqw
## Selected media coverage
The project and the Dinotracker app have been covered by international media outle... |
f8d568f7a5d06ff91b818cde96efc7282e88ff77f262b38f161a361db5a46201 | Text | 4,850 | 120 | # Behavior Annotator
<img src="bannotator/resources/bg_readme.png" height="300">
# Table of contents
- [Installation](#installation)
- [Usage](#usage)
- [GUI](#GUI)
- [Video](#video)
- [Annotation](#annotation)
- [KeyPress Functions](#keypress-functions)
- [Contributing](#contributing)
- [Acknowledgement](#a... |
fb0b13d05b9c4320341340bc973822de4838d77460398ef13aa80d326f1801fe | Text | 4,852 | 136 | Reconciling emergences: Identifying causal emergence in multivariate data
=========================================================================
This code provides basic functionality to test hypotheses about causal
emergence in time series data. This repository contains the companion software
for the paper:
Rosas... |
8f6f247e9cb241da779dc438634127e02502af878db3f25675851edc137fafe3 | Text | 4,870 | 104 | # Overview
This Mathematica framework constructs and optimizes the geometry of complex network manifolds. It models a physical network as a continuous surface manifold composed of cylindrical tubes (edges) that meet at polygonal junctions (vertices).
Using Mathematica's FEM package, the script finds the network's equ... |
9d5060afa384cb1fb860388883a7e317189197939b5b107bac2594c5dca424c9 | Text | 4,879 | 49 | # A chromosome region linked to neurodevelopmental disorders acts in distinct neuronal circuits in males and females to control locomotor behavior
## Highlights
- 16p11.2 hemideletion (16p11.2 del/+) induces sex- and cell type-specific transcriptomic signatures in spiny projection neurons (SPNs).
- Transcriptomic cha... |
482fe19d9c1a3e694dff9f7c17f757aeb4a4504fe61bc1baee681081a0c61094 | Text | 4,894 | 43 | # TUSNet: A deep-learning model for one-shot transcranial ultrasound simulation and phase aberration correction
[Kasra Naftchi-Ardebili](https://bioengineering.stanford.edu/people/kasra-naftchi-ardebili)†, [Karanpartap Singh](https://karanps.com)†, Reza Pourabolghasem, Gerald R. Popelka, [Kim Butts Pauly](https://kbpl... |
89c62a1bf5e6105f570f533db726f6f0dd50dd89d0eb52fa2e9142229fc7e05e | Text | 4,896 | 96 | # 202404_Speckle_Analysis
FIJI and Qupath pipeline to quantify speckle size and number.
## (Optional) Speckle Enhancement (FIJI)
- Install the CLIJ2 plug-in. (https://clij.github.io/)
- Drag and drop "202404_Speckle_Analysis\scripts\1_fiji\MecP2_analysis_script_preprocessingforQupath.ijm" to FIJI.
- Click "Run"
- Set ... |
f17b51b47cd31bd589edb15360312c28784a1d1eb736338efe2a0dbc6eedf0ca | Text | 4,899 | 140 | ------------------------------------------------------------------------------------------------------
# SCILD: Advancing spatial cellular communication inference in spatial transcriptomics
## Authors
- yujiating@amss.ac.cn
- lywu@amss.ac.cn
- dcsun@sdu.edu.cn
---
## Overview
**SCILD** (Spatial Cellular communicat... |
d16c9a3bbc97bf19a7f5e64472a9fbedc3309a949dbada04013e610dacc31649 | Text | 4,911 | 100 |
# napari-dmc-brainmap
*DMC-BrainMap is an end-to-end tool for multi-feature brain mapping across species.*
This [napari](https://napari.org/stable/) plugin was generated with [Cookiecutter](https://github.com/cookiecutter/cookiecutter) using napari's [cookiecutter-napari-plugin](https://github.com/napari/cookiecutte... |
1471a938614999afc42407b85d3feaccc214836e54357430a87d98222d314076 | Text | 4,924 | 117 | # 🧠 Single-Cell-Synaptic-Clustering
This repository contains code and analysis from my Master's thesis project in computational neuroscience. The project investigates how **dendritic calcium-mediated action potentials (dCaAPs)** influence **synaptic clustering** in a simulated single cell.
---
## 🧩 Project Summary... |
4463ed38ecec93f800c72028f423e9831404d25565df13a91c98225ace88076a | Text | 4,942 | 111 | 
A **Dynam**ic Programming Approach to Segment **ONT** Signals.
Dynamont is a segmentation/resquiggling tool for ONT signals.
Dynamont was tested on
* RNA002
* RNA004
* DNA R10.4.1 5kHz (I applied the trained transition parameters from the RNA004 model to the DNA R10 models. These should ... |
8b867f0280f1fc92b0c88101a29465252165d66dc2a1cf4161b0e0eda0c9410a | Text | 4,944 | 103 | 
[](https://github.com/alan-turing-institute/distinctipy/actions/workflows/pythonapp.yml)
[![build](h... |
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