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e14da745bca3bd491fe13c950f7edcf11f472eedd35f93c07a1b93f73292ca4b | Text | 5,852 | 86 |
Paper title: Classifying Polish in Use-Wear Analysis with Convolutional Neural Networks
Anastasia Eleftheriadou1*, Youssef Djellal1,2, Shannon P. McPherron3,+, João Marreiros2, 1,+
1 Interdisciplinary Center for Archaeology and the Evolution of Human Behaviour (ICArEHB), Universidade do Algarve, Faro, Portugal
2 TraC... |
14d323cfbb1dcc558caedbee0904ecc0740fef515e960eb4044990b943b99e97 | Text | 5,878 | 61 | # ITEM-SL-paper
**MATAB Code for the ITEM-SL Paper, submitted to Imaging Neuroscience**
This code belongs to the paper on "Searchlight-based trial-wise fMRI decoding in the presence of trial-by-trial correlations" by Joram Soch, publicly available from *bioRxiv* and currently under review in *Imaging Neuroscience*. I... |
a42eb2b6b15c1fe7b905c8cf836096a35bd698e1ef7d903ff933923f35ad235f | Text | 5,881 | 85 | # Differentiating Motor and Cognitive Deficits in Neurological Disorders via a fixed-point iteration method
## Executive Summary
This repository contains the data cleaning and analysis pipelines associated with the paper **"Mitigating the impact of motor impairment on self-administered digital tests in patients with ... |
5ae986e024721024b8535818ea612db0c81baa3b19a28db11e40b5d3d44cc1a0 | Text | 5,889 | 131 | # Oliva Mapping Hand Function Imaging Neuroscience 2025
## Table of content
* [1.Dependencies](#1dependencies)
* [2.Convert dicom to NIfTI](#2convert-dicom-to-nifti)
* [3.Data Organization](#3data-organization)
* [4.Anlaysis](#4anlaysis)
* [4.1.Installation of python requirements](#41installation-of-python-requirem... |
15c8be392df73938eb6039ce24d10f85b2ec6086abe33c748fbb1ea6aaa85849 | Text | 5,901 | 113 | # Search-Optimized Quantization in Biomedical Ontology Alignment
[](https://pypi.org/project/olive-ai/)
[](https://microsoft.githu... |
221dd86b6856cd3441b32ff85314fbe78b37343e555205e8532ed7a72e32b79a | Text | 5,922 | 55 | # 新型コロナウイルス感染速報
[** for detecting structural and developmental anomalies in fetal brain MRIs. The model l... |
55cbc179786a25d25aeedaffed86199c46ccdf073fe59867b6277c872ce44d6f | Text | 5,934 | 96 | # Mutational Effect Transfer Learning
[](https://github.com/gitter-lab/metl/actions/workflows/test.yaml)
[](https://zenodo.org/doi/10.5281/zenodo.10819483)
This rep... |
cdcce7f8a6a4f7c569b5ef9ee60da0c90f509c24ff652aea20d6b19b2cebde07 | Text | 5,984 | 177 | # Multi-Ethnic Cultural-Spatial Resonance Networks (CSRN)
## Overview
This repository contains the implementation of Multi-Ethnic Cultural-Spatial Resonance Networks (CSRN) for Population Dynamics Prediction. The model combines neural networks with physics-informed modeling through a specialized mixture of experts fr... |
d430fa04083d240c9f0e75aa90bc73c13cb1a874f4c7b4ce29bddbb6366c4a42 | Text | 5,994 | 177 | 
[](https://pypi.org/project/statsmodels/)
[](https://anaconda.org/conda-forge/statsmodels/)
[![Licens... |
98530271fa96b978687a85ef1be97de1de88a15e63163f653177319fa1fa7e38 | Text | 6,011 | 124 | # Experiments on transfer learning for virtual screening of antibacterials
Code accompanying the paper "Transfer learning enables discovery of sub-micromolar antibacterials for ESKAPE pathogens from ultra-large chemical spaces".
## Installation
1. Clone the repo: `git clone git@github.com:mgarort/dockbiotic.git`
... |
d9805d77f43d6d43deb6f028a5fa2a03a9c243cdd3c7954c9f22879602ac90a0 | Text | 6,021 | 181 | <br />
<p align="center">
<h2 align="center">Impact of intermittent lead exposure on hominid brain evolution</h2>
<p align="center">
This repository contains the analysis pipeline (for bulk and single-cell RNA-Seq data) used for the paper titled "Impact of intermittent lead exposure on hominid brain evolution" ... |
b15512fd6e05f939d9cb7c063984ca63c4b0109176fd60bca336c260d4a2afb5 | Text | 6,026 | 150 | > [!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/neurodamus-models
# neurodamus-models
This repo is the aggregate repository featuring all simulation model... |
15ac8c202f86d7dea16630581a92a4b8808573a9a22d7bb4963e0c4731c31e68 | Text | 6,030 | 204 | 
## Interpolating Neural Network
This is the github repo for the paper ["Unifying machine learning and interpolation theory via interpolating neural networks"](https://www.nature.com/articles/s41467-025-63790-8), published in Nature Communications.
INN is a lightweight yet precise network archit... |
5076458528cd0d201cbc94118adc555c2e12b7099a933701fd65ae88e389735c | Text | 6,073 | 117 | <div align="center">
<h1>Data Analysis Pipeline</h1>
<h4>An R pipeline for technical and biological data assessment.</h4>
<p>
<a href="https://doi.org/10.1002/prca.70017" target="_blank"><img src="https://img.shields.io/badge/Published in:-Proteomics_--_Clinical_Applications-blue" alt="Submitted in ... |
475ba42464146785bc19c757e473527533ccde4fd2321169d8debb19d89f1eb8 | Text | 6,076 | 160 | |MIT license| |PyPI| |Discord| |StackOverflow|
Fairlearn
=========
Fairlearn is a Python package that empowers developers of artificial
intelligence (AI) systems to assess their system's fairness and mitigate
any observed unfairness issues. Fairlearn contains mitigation algorithms
as well as metrics for model assessm... |
5d5af555aff7b94e67b38478e20463c09aaa1c6d7202b75d91ee1eb49a262a41 | Text | 6,083 | 69 | # Claude Cookbooks
The Claude Cookbooks provide code and guides designed to help developers build with Claude, offering copy-able code snippets that you can easily integrate into your own projects.
## Prerequisites
To make the most of the examples in this cookbook, you'll need a Claude API key (sign up for free [her... |
1c5d102030d7cf24ba9569693862238125a4d43bedf161ecee4dd3c9868981a5 | Text | 6,114 | 116 |
# MAP: Modular Agentic Planner
Official repository for the paper - "[Improving Planning With Large Language Models: A Modular Agentic Architecture](https://arxiv.org/pdf/2310.00194)."
## Requirements
- python 3.9.17
- numpy==1.24.3
- tqdm==4.65.0
- json==2.0.9
- openai==1.24.1
## Tower of Hanoi (ToH)
For ToH tas... |
51a3978d927e2f83234db4a2f19c07affe5274e4e7a2ce7c40a76a3b27f38269 | Text | 6,152 | 232 | # Hybrid MambaVision and Transformer-Based Architecture for Robust 3D Lane Detection
This repository is hosting the implementation of our “Hybrid MambaVision and Transformer-Based Architecture for Robust 3D Lane Detection” model.
## Environments
For package installation instructions, please see the [installation guid... |
5c1150b093ce16c5f28180168102056a8c9fd9f995488bfffcc216ebfae6f268 | Text | 6,184 | 179 | # CAP Analysis Pipeline
## Overview
This repository contains a comprehensive Co-Activation Pattern (CAP) analysis pipeline for processing fMRI data. The pipeline consists of multiple steps, from extracting time courses from brain regions to analyzing CAP dynamics, synchronicity, complexity, and network properties... |
c89c85bba6274ecfe3f9cbabf541fc34fd59b1c6789b898935d4cb02d1c27b4d | Text | 6,203 | 150 | # Diverse and flexible behavioral strategies arise in recurrent neural networks trained on multisensory decision making
**Thomas S. Wierda¹,\*, Shirin Dora²,\*, Cyriel M. A. Pennartz¹, Jorge F. Mejias¹,#**
¹ Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 109... |
10d41843cbba44c4297e11fd688a4c8412df50496fefee7e414d786b025381cf | Text | 6,218 | 109 | # Snakemake Pipeline: parse_star_junctions
## Overview
Pipeline for taking STAR's SJ.out files and parsing the counts for a given bed of named spliced junctions.
This fork deviates from the [original repository](https://github.com/frattalab/bedops_parse_star_junctions) in the following ways:
- Inputs and parameters... |
fed7f6378bc127ae16c937847b1c32e4ef26e54a1283c01caaec7e3e0e8a5a1c | Text | 6,270 | 76 | ## Overview
__*NEWS (05-2025):*__ The repository now includes a jupyter notebook showing how to run CBASS on __Neuropixel Data... |
bae6941c51700908aedb95fef061ccd88bf105d98c799d8a31cad546d816ffbe | Text | 6,277 | 96 | # The Spatial Complexity of Optical Computing: Toward Space-Efficient Design
> **The spatial complexity of optical computing: toward space-efficient design**
> Yandong Li and Francesco Monticone. *Nature Communications* **16**, 8588 (2025)
> [🔗 Link to the paper](https://www.nature.com/articles/s41467-025-63453-8... |
cb7a73c2684ef92544737e3f297c3e3a3f99086df9125ba18a698e684a607a92 | Text | 6,290 | 220 | # FAST: FrAme-multiplexed SpatioTemporal Learning Strategy
<p align="center">
<img src="./FAST_logo.png" alt="FAST Logo" width="600"/>
[](https://doi.org/10.5281/zenodo.15209897)
## Overview
Pipeline for taking STAR's SJ.out files and parsing the counts for a given bed of named spliced junctions.
This fork deviates from the [original repository](https://github... |
86122a2acbdd4524bd032eddff654d5630d98d216c0a464d168d9437de985380 | Text | 6,317 | 123 | **_Ce_-NeRV3D Blender Add-on**
• This tool allows you to generate high-quality images or videos of your gene of interest within the _C. elegans_ nervous system.
• To use this add-on, you'll need the following:
1. Blender (https://www.blender.org/download/). We used Blender Version 3.6.5, which can be downloaded usin... |
d1418b0e8945c3d3b8bc30a3c947e709f87ad335eadccd0f60432f6541e900ae | Text | 6,342 | 146 | # Comparison of local feature matching algorithms
by Éléa Gros
This repository contains the code used to generate the results presented in the associated manuscript entitled "Alignment of histological and polarimetric large-scale imaging for brain tissue characterization" [10.1117/1.JBO.30.9.096003](10.1117/1.JBO... |
909ff2e0e643c1ac954c058a6b99abc52fcf8332b470365c59192a24dff1435d | Text | 6,365 | 83 | # E-field targeting v1.1.3
[](https://doi.org/10.5281/zenodo.17192323)
This repository is used to solve optimization problems where a set of electric fields (E-fields) are superimposed to focus the E-field at a target location and in target direction. It... |
3a10bdc81c66971bb1e3d3f2ec2a338401f6b849b2b20160b1acaa93c2f8a7eb | Text | 6,395 | 149 | # stPlus
stPlus is a reference-based method for the accurate enhancement of spatial transcriptomics. Based on an auto-encoder with a carefully tailored loss function, stPlus performs joint embedding and predicts spatial gene expression via a weighted k-NN. The spatial transcriptomics enhanced by stPlus can provide bett... |
cbcae76d45a3c9efdf0057d440c487d5130c706dc2e9a51393636d0899d9b2b6 | Text | 6,424 | 149 | # Veyon Fork to comply with the EU general data protection regulation and record remote lab sessions
[](https://github.com/ComputationalReflection/veyon/releases)
[ training on ADME property prediction and subsequent fine-tuning, as employed in the paper **“Improving ADME Prediction with... |
2d480f9777ad712e4a8cbf273683b53bdae84b5e5bf6b32d95c95ee57cbab4e9 | Text | 6,519 | 210 | # MetaBCI
## Welcome!
MetaBCI is an open-source platform for non-invasive brain computer interface. The project of MetaBCI is led by Prof. Minpeng Xu from Tianjin University, China. MetaBCI has 3 main parts:
* brainda: for importing dataset, pre-processing EEG data and implementing EEG decoding algorithms.
* brainflow... |
6b274f7ff8e3cef933e4f647aeaa4c3cfe46c8427b07bacc57278233aefd09fb | Text | 6,524 | 163 | ==============
Jointly
==============
.. image:: https://img.shields.io/pypi/v/jointly.svg
:target: https://pypi.python.org/pypi/jointly
.. image:: https://github.com/hpi-dhc/jointly/actions/workflows/deploy.yml/badge.svg
:target: https://github.com/hpi-dhc/jointly/actions/workflows/deploy.yml?query=... |
0662e91cdf70368ce7c4a421bc011e8bd3760ee996859df3c5e7c15180635123 | Text | 6,526 | 159 | # Duplex-Indel
Duplex-Indel is a pipeline for somatic insertions and deletions (indel) calling from Tn5 transposase-based duplex sequencing data. It is inspired by and expands on the core methods for SNV calling in META-CS, [pre-pe](https://github.com/lh3/pre-pe/) and [lianti](https://github.com/lh3/lianti/). We thank... |
0d40ef6005bd70715c22c6a48052111f180c191aef7dc545b269cb575b1be6af | Text | 6,539 | 59 |
### Description
PLACO+ implements a variant-level formal statistical test of pleiotropy of two traits using summary-level GWAS data, and can account for potential correlation across traits, such as that arising due to measurement of traits on the same set of individuals or due to shared controls in case-control studie... |
f500f05a079f87023efcc2b53b24aff45af4a23b63a3cba4f4a45a8a380f9d46 | Text | 6,562 | 102 | # GREP: Genome for REPositioning drugs `v1.0.0`
GREP can quantify an enrichment of the user-defined set of genes in the target of clinical indication categories and capture potentially repositionable drugs targeting the gene set.
Both can be run in a few seconds!
## Overview
<div align="center">
<img src="https://raw... |
7f4f2a3a737124c1a7f6936d615059b2d5db9ba6ce01e343a2c1846fbfc9a8dc | Text | 6,584 | 157 | # Graph Neural Network and Diffusion Model for Modeling RNA Interatomic Interactions [[Paper](https://academic.oup.com/bioinformatics/article/41/9/btaf515/8254448)]
Welcome to the official repository of GraphaRNA, a novel approach for RNA 3D structure prediction based on **graph neural networks (GNNs)** and **denoisin... |
53a69e456ed6cae45ea46dc78cf0f42b477fd1c56f9ce646a0c93af16075e63f | Text | 6,618 | 108 | # Workflows
---
## Published in Mittler et al.
### A. Analysis of CRISPR/Cas9 screen
#### Hardware, operating systen, software
- Mac (arm64)
- Mac OS v14.6.1 (Sonoma)
- Terminal v2.14
- GNU bash v3.2.57(1)-release (arm64-apple-darwin23)
- mageck v0.5.9.5 (available [here](https://sourceforge.net/p/mageck/wiki/Home/))
... |
70a3374f265dfd529440f4d5675d6e465ecdd92d7a045d55d17ad72d1a35d41d | Text | 6,641 | 176 | # Training Molecular Dynamics Potentials in JAX
[**Documentation**](https://chemtrain.readthedocs.io/en/latest/) | [**Getting Started**](#getting-started) | [**Installation**](#installation) | [**Contents**](#contents) | [**Contact**](#contact)
[](https://badge.f... |
b5a56a7eda31d4bc5bc15e2825ec900d56aa45fc7d1ec40c5e1d33adbf254fac | Text | 6,660 | 150 | # Learning joint Segmentation of Tissues And Brain Lesions (jSTABL) from task-specific hetero-modal domain-shifted datasets
Public PyTorch implementation of [Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets](https://arxiv.org/abs/2009.04009) published in ... |
121b7f436712008c7c84b90964e8f4c40670962c348a4816450de236e160f04d | Text | 6,672 | 164 | ==============
Jointly
==============
.. image:: https://img.shields.io/pypi/v/jointly.svg
:target: https://pypi.python.org/pypi/jointly
.. image:: https://github.com/hpi-dhc/jointly/actions/workflows/deploy.yml/badge.svg
:target: https://github.com/hpi-dhc/jointly/actions/workflows/deploy.yml?query=... |
5aa10d3d9f77b0cdb72beda27d7b0298035b7abadc2c795423081a351bf9c4d2 | Text | 6,681 | 129 | [](https://circleci.com/gh/jbelyeu/PlotCritic/tree/master)
[](http://bioconda.github.io/recipes/plotcritic/README.html)
# PlotCritic... |
ec87afd8167031447d6bf08b7ace447d363e73f31a38ba479426172750c3382e | Text | 6,687 | 95 | # Covariant spatio-temporal receptive fields for spiking neural networks
This repository contains the code for the paper "Covariant spatio-temporal receptive fields for spiking neural networks".
A preprint is available at: [arXiv:2405.00318](https://arxiv.org/abs/2405.00318)
Further explanations can be found at [jeg... |
4a8f686a9ce81c4a44b6400377508f738fcd077a7575240a57350eccfc402532 | Text | 6,728 | 135 | # Neural Speech Decoding
By Xupeng Chen, Ran Wang, Amirhossein Khalilian-Gourtani, Leyao Yu, Patricia Dugan, Daniel Friedman, Werner Doyle, Orrin Devinsky, Yao Wang, Adeen Flinker
## Our Paper is Online!
[Paper Published in Nature Machine Intelligence](https://www.nature.com/articles/s42256-024-00824-8)
[](https://zenodo.org/doi/10.5281/zenodo.13094029)
**Current version: v1.6.0**
This tool provides functionality for sorting and anonymizing DICOM files.
## Features:
- DICOM file sorting with two selectable folder layouts:
- `... |
f79ded19362a567c7902024af989845e7a2f7d3943e9c9f2d71efc27209ef7fd | Text | 6,865 | 104 | 
# Yin-Yang Dataset
This deep learning dataset was developed for research on biologically plausible error-backpropagation and deep learning in spiking neural networks.
It serves as an alternative to e.g. the MNIST datase... |
fc608593909bbc0075de44b3bc26f0db356f26071f15e6e7019e4166d7cba636 | Text | 6,875 | 67 | # Computational modeling reveals biological mechanisms underlying the whisker-flick EEG
This repository contains the code used in the paper [Computational modeling reveals biological mechanisms underlying the whisker-flick EEG](https://www.biorxiv.org/content/10.1101/2024.12.13.628364v1.full).
We simulate EEG signals... |
d1e6f6362129aeec98bfa65cd52400ed9b89081371a87e63b0da60e875b6f7ea | Text | 6,887 | 105 | # Covariant spatio-temporal receptive fields for spiking neural networks
[](https://doi.org/10.1038/s41467-025-63493-0)
This repository contains the code for th... |
9d614cac841fb193cda653f73bf2cafff1d86e7d1e6d0f5230e0bbcc0cd84883 | Text | 6,919 | 147 | PySpike
=======
.. image:: https://badge.fury.io/py/pyspike.png
:target: http://badge.fury.io/py/pyspike
.. image:: https://travis-ci.org/mariomulansky/PySpike.svg?branch=master
:target: https://travis-ci.org/mariomulansky/PySpike
PySpike is a Python library for the numerical analysis of spike train similarit... |
6d298a56f524bc683dca9eafb01c37f424197966d9e9f2e7532b32ca3362cb3a | Text | 6,934 | 79 | # MyRelax overview
"Myelin and Relaxation" (MyRelax) is a collection of command line scripts written in Python 3 for myelin and relaxometry MRI. MyRelax was developed as part of the [CDS-QuaMRI project](https://cordis.europa.eu/project/id/634541), funded under the Europea... |
741cdde858804292431a88e90ad99be659026fa338216f54b47fc6ce0fd4acd7 | Text | 6,937 | 118 | # Torchmeta
[](https://pypi.org/project/torchmeta/) [](https://travis-ci.com/tristandeleu/pytorch-meta) [](https://tristande... |
5ad1cd2647f9a59431de3808a3ba8ea544fcf2a6142ec383489ae848ff6ec6f7 | Text | 6,977 | 154 | # Mesoscale functional connectivity of human V1 — analysis pipeline
This repository contains the complete, end-to-end code used to replicate the study
presented in
**Schmidt et al. (2025).** *Unraveling the mesoscale functional connectivity of the
human primary visual cortex using high-resolution functional MRI.* bio... |
4ddfea917bd71ee50b61f8342047c356828a4c87a068aa5b6a2a2822510e05b5 | Text | 7,025 | 79 | # Cerebellum-Specific ALE (C-SALE)
This repository contains code and data associated with the paper ['A bias-accounting meta-analytic approach refines and expands
the cerebellar behavioral topography'](https://doi.org/10.1101/2024.10.31.621398) by Magielse, Manoli, Eickhoff, Fox, Saberi*, and Valk*.
## Graphical Abst... |
877fda4381532d3e3996e438d502629ed5d797877bf83f66f2cbbd4c0a1ddcc7 | Text | 7,131 | 95 | # BRIC TUS Simulation Tools
MATLAB-based functions for running TUS acoustic simulations using T1-weighted MR and pseudo-CT images acquired at the Brain Research & Imaging Centre, University of Plymouth. To create pseudo-CT images, see https://github.com/sitiny/mr-to-pct.
Currently, the simulation functions work for t... |
72c18d279a53346f808753a6e5bdc875290548d3e20249ab3515895c8333d3ed | Text | 7,143 | 119 | # SimCLR PyTorch
This is an unofficial repository reproducing results of the paper [A Simple Framework for Contrastive Learning of Visual Representations](https://arxiv.org/abs/2002.05709). The implementation supports multi-GPU distributed training on several nodes with PyTorch `DistributedDataParallel`.
## How close... |
d07ac83fa5cd07176bc760bdb6ab952318388c0c1a72851c16c91faaa254114c | Text | 7,143 | 95 | # BRIC TUS Simulation Tools
MATLAB-based functions for running TUS acoustic simulations using T1-weighted MR and pseudo-CT images acquired at the Brain Research & Imaging Centre, University of Plymouth. To create pseudo-CT images, see https://github.com/sitiny/mr-to-pct.
Currently, the simulation functions work for t... |
441c2749c96313891164be28ebcc2ae6910e7d7d811614abeba8d56947f0b117 | Text | 7,146 | 151 | # Identifying opportunities for late-stage C-H alkylation with in silico reaction screening and high-throughput experimentation
[](https://www.python.org)
[
2. [Evans Mudibo](https://github.com/mudiboevans)
3. [SsemuyigaMHC](https://github.com/SsemuyigaMHC)
4. [Hesbon Omwandho](https://github.com/hesbornomwandho)
5. [Olaitan I. Awe](h... |
6a02e9445292e7c2f4bfa65a6985e1e4c1d4f773f253c8761f4ddfc0b8a6580a | Text | 7,165 | 97 | # tcgaAnalyses
Scripts to analyze TCGA cancer genomic data.
## Script 1
vga_makeBoxPlotRsem.sh - compare RNA-Seq gene expression between tumor and matched normal.
* Synopsis: vga_makeBoxPlotRsem.sh generates a high-quality png box plot with the mRNA expression data of a given gene for 15 TCGA tumor and normal matc... |
a6028372f69e1e38d78b2ac6e121fb5ae17027998f03c94a3d96d9423eb5110c | Text | 7,210 | 124 | # RaVAEn
<table><tr>
<td width="250px"><img src="_illustrations/RaVAEn_logo.png" alt="Project sample" width="360px"></td>
<td>
<b>The RaVÆn system</b><br>
<em>We introduce the RaVÆn system, a lightweight, unsupervised approach for change detection in satellite data based on Variational Auto-Encoders (VAE... |
d06d4ebb980e8fabe0833c4838d597b27c304672b353f67b5a3e3cd08a3e69cf | Text | 7,236 | 249 | # PEMapper/PECaller
**Citation**:
Johnston HR, Chopra P, Wingo TS, Patel V, Epstein MP, Mulle JG, Warren ST,
Zwick ME, Cutler DJ. PEMapper and PECaller provide a simplified approach to
whole-genome sequencing. **Proc Natl Acad Sci U S A** **2017**:114(10):E1923-E1932
DOI: [10.1073/pnas.1618065114](https://www.doi.org... |
161c28bd889a9df8b93e4a337251b7b4c5fc080209a16ad09dfd515d993a5214 | Text | 7,248 | 81 | 
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your inputs and analysis parameters. This input drives a parallel ... |
df8a9f41d671dd7c231ce0532605250fd89731c636776d3e26da3a011059e2c2 | Text | 7,269 | 316 | README
======
.. image:: https://github.com/libvips/pyvips/workflows/CI/badge.svg
:alt: Build Status
:target: https://github.com/libvips/pyvips/actions
PyPI package:
https://pypi.python.org/pypi/pyvips
conda package:
https://anaconda.org/conda-forge/pyvips
We have formatted docs online here:
https://libv... |
398d04ac75eb4b93f245e56582d36a0cf5d73a62c1386677d8fe58c69261ff26 | Text | 7,335 | 159 | # DeepChem
[](https://anaconda.org/conda-forge/deepchem)
[](https://pypi.org/project/deepchem/)
[. The code includes a lab-scale hybrid model and a pilot-scale hybrid model for naphtha catalytic cracking. Moreover, a multi-objective optimization algor... |
85cc1e31a451c9802ba727cf655ce1a46ca8d020ae1302545439c894cebd1a89 | Text | 7,466 | 189 | # U-Net: Semantic segmentation with PyTorch
<a href="#"><img src="https://img.shields.io/github/actions/workflow/status/milesial/PyTorch-UNet/main.yml?logo=github&style=for-the-badge" /></a>
<a href="https://hub.docker.com/r/milesial/unet"><img src="https://img.shields.io/badge/docker%20image-available-blue?logo=Docker... |
625d76addae1262b70c808187aa8b71dea5014a7f3f0de995d3312e01c350dcd | Text | 7,496 | 243 | # Autogrid4
Autogrid4 is a support software for docking programs such as AutoDock4 and Autodock-GPU.
Its function is to precalculate the grids used by the docking software.
AutoDock is a suite of automated docking tools. It is designed to
predict how small molecules, such as substrates or drug candidates,
bind to ... |
e487866935958881f64f3c9a78c6d4aa6103bb4458ffd95fb809da0e68764996 | Text | 7,502 | 167 | # NAGL-MBIS
[](https://opensource.org/licenses/MIT)
A collection of models to predict conformation independent MBIS atom-centred charges for molecules, built on the [NAGL](https://github.com/SimonBoothroyd/nagl)
package by SimonBoothroyd.
## Installa... |
e4c9bc3dc92d21273d04d4cea3cffda75d18093e94963576b8f3096bca295025 | Text | 7,625 | 154 | ## Training continuous time Recurrent Neural Networks (RNNs) on various behavioral tasks
This project established a pipeline for seamlessly defining time-constrained behavioral task and training RNNs on it using backpropagation (BPTT) on *PyTorch*.
Further, it contains additional post-training task-performance [analy... |
a97c3ae46c666d0f7ac6f0e4cf81f11d487ee4812bbc8ff9243fdeabbb3cd7a0 | Text | 7,639 | 166 | ## Training continuous time Recurrent Neural Networks (RNNs) on various behavioral tasks
This project established a pipeline for seamlessly defining time-constrained behavioral task and training RNNs on it using backpropagation (BPTT) on *PyTorch*.
Further, it contains additional post-training task-performance [analy... |
556945782a24bbff3d4faa353589a097263448a32072c852ea43cef0ac8a968a | Text | 7,643 | 222 | # CrystalFlow: A Flow-Based Generative Model for Crystalline Materials
Implementation codes for CrystalFlow: A Flow-Based Generative Model for Crystalline Materials.
For MindSpore implementation please refer to [here](https://gitee.com/mindspore/mindscience/tree/master/MindChemistry/applications/crystalflow).
[](https://doi.org/10.5281/zenodo.15210305)
Snakemake pipeline to extract polyA-tail containiing reads (PATRs) from aligned bulk RNA-seq datasets and identify poly(A) site clusters. Broadly mimics workflow re... |
36fb2dddd0d1a9f92504638072e2f5eb0b32e248a105914b2439c89e4d40cefb | Text | 7,697 | 178 | # DeepLION<img align="left" src="Figures/Lion.png" width="45" height="45" >
Deep MuLti-Instance Learning Improves the Prediction of Cancer-associated T Cell ReceptOrs for Accurate CaNcer Detection
------------------------------
DeepLION is a deep multi-instance learning (MIL) method for identifying cancer-associate... |
e483f0f285ed8a712c1afd2dfbb52d24e75a88eabf7d45afcf59cf34cc529bd3 | Text | 7,701 | 169 | *fMRIPrep*: A Robust Preprocessing Pipeline for fMRI Data
=========================================================
*fMRIPrep* is a *NiPreps (NeuroImaging PREProcessing toolS)* application
(`www.nipreps.org <https://www.nipreps.org>`__) for the preprocessing of
task-based and resting-state functional MRI (fMRI).
.. im... |
3698d762b3e9f4312a140ae209ad28fc675a20d89e32e598501a3514b22f71cb | Text | 7,703 | 99 | # Information content and interpretation of CSD non-trivially depends on array density
This repository contains the code used in the paper "Information content and interpretation of CSD non-trivially depends on array density". Steps to reproduce the figures in that paper are as follows:
## System requirements
The ge... |
2a7b2c04d744aac8c452406fb297f91475c2b5a617430d533d850e1ae759bf15 | Text | 7,706 | 256 | 
[](https://github.com/Young0222/MotiL/blob/main/LICENSE.txt)
# MotiL
> **Mo**lecular mo**ti**f **L**earning for molecular property prediction
>
> A motif-centered pretraining fram... |
d72bf64b243a93d05c3cc21bcce51c8b7e234ea514846d5b9c6f25581905b6a0 | Text | 7,722 | 219 | # ECG-XPLAIM: Deep learning tool for accurate and explainable arrhythmia detection from 12-lead electrocardiogram (ECG) signals
#### Panteleimon Pantelidis, Samuel Ruipérez-Campillo, Julia E Vogt, Alexios Antonopoulos, Ioannis Gialamas, George E Zakynthinos, Polychronis Dilaveris, Jose Millet, Theodore G Papaioannou, ... |
a00626868b4e71fdcb11d65267dcffca18cd4d4ec89641f572a93e7d9a7aab16 | Text | 7,781 | 133 | # NOR_Analysis
This repository provides protocols for both manual and automated scoring of NOR (Novel Object Recognition) data. All code used for each scoring method can be found within respective manual or automated folders. Follow the steps below to set up your environment and run the analyses.
---
## 1. Python En... |
a9a5ef13037ec1561d68286b09e849da94f1a36821d3f56e9d92915b474534f6 | Text | 7,788 | 193 | # MetaboGNN
MetaboGNN is a Graph Neural Network-based framework for predicting liver metabolic stability using molecular graph representations and cross-species experimental data.
This code was developed as part of our study:
**"MetaboGNN: Predicting Liver Metabolic Stability with Graph Neural Networks and Cross-Sp... |
dd067772af0ff73590acc576ed391724f64390582aa0a84a523f9a9adde03ad0 | Text | 7,798 | 182 | # BrainScape
*BrainScape: An Open-Source Framework for Integrating and Preprocessing Anatomical MRI Datasets*
> BrainScape automates the download, collation, and preprocessing of **45880 multimodal MRI scans** (T1w, T2w, T1Gd, FLAIR) from **157 independent projects**, spanning **26783 unique participants**.
---
## ... |
3d1dabb0693a1bfbefc4299ae0d983002116de7541be19a87ac272e6f6ca1b2d | Text | 7,819 | 125 | <h1>
<picture>
<source media="(prefers-color-scheme: dark)" srcset="docs/images/nf-core-scrnaseq_logo_dark.png">
<img alt="nf-core/scrnaseq" src="docs/images/nf-core-scrnaseq_logo_light.png">
</picture>
</h1>
[![Open in GitHub Codespaces](https://img.shields.io/badge/Open_In_GitHub_Codespaces-black?labelCo... |
c7caab477e668b33a1907f7f38f728adbb41bab9c8a80f60a1274a3132a1e129 | Text | 7,821 | 182 | <div align="center">
<img src="overview.png" alt="EMG+IMU to model overview" style="max-width: 100%; width: 900px; border-radius: 8px;"/>
# Exoskeleton: IMU/EMG Dataset Analysis and Motion Intention Modeling
Analysis and modeling of the public IMU + EMG dataset using ML models (CNN, LSTM, SVM) for lower-limb motion ... |
0e1f31a2a3ae8c0f9d79a3bf444ce06888cce6aaff9de57ca7b0c177f6fd221e | Text | 7,827 | 185 | # DeepSCEM
Deep Segmentation for Cellular Electron Microscopy 🦠🔬⚛️.
DeepSCEM is an automatic segmentation tool integrating deep learning methods.
DeepSCEM is developed for organelles segmentation in cellular electron microscopy
image segmentation.
The toolkit is developed to be both easy to use and deploy initially,... |
e0b28858ef68c55e87e6cc0267fe9c10753a8584e91122fa3bcd8f4e1a62b2aa | Text | 7,828 | 88 | This repository hosts the analysis code used in preprocessing, analyzing and visualizing the data that is reported in this preprint: https://www.biorxiv.org/content/10.1101/2024.03.02.583127v3
The preprocessed data to reproduce the figures as well as the raw data can be found in this repository: https://osf.io/g8b9v/
... |
f4e326b0f9c3b15e3845dc0c1e8b3b90c31957090e1f2044cd5bacfe1c462586 | Text | 7,834 | 173 | <p align="center">
<img src="https://raw.githubusercontent.com/ESA-PhiLab/pynas/main/docs/images/banner.png" alt="ESA Phi-lab and PyNAS banner" width="100%" />
</p>
<p align="center">
<a href="https://github.com/ESA-PhiLab/pynas/actions/workflows/ci.yml"><img alt="CI" src="https://github.com/ESA-PhiLab/pynas/actio... |
71100da53af1c27277b204959aa31be890a69c246af6bec9f21b6ca7778d4194 | Text | 7,844 | 95 | # ProteinNPT
This is the official code repository for the paper ["ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers"](https://papers.nips.cc/paper_files/paper/2023/hash/6a4d5d85f7a52f062d23d98d544a5578-Abstract-Conference.html)
## Overview
ProteinNPT is a semi-supervised co... |
6c5c616178b91248f2994b89cd4a80e29fcd4ea4c96fc31063de86de9aa978ec | Text | 7,903 | 185 | ********
DockBox2
********
.. image:: https://github.com/jp43/DockBox2/blob/main/Table_of_content_jpg.jpg?raw=true
:alt: Table of contents
:align: center
:width: 900px
Graph Neural Network Model to improve docking predictions
DockBox2 (DBX2) is a sequel to DockBox that combines the concept of consensus dock... |
31ce1055830d1e0b732cfbf0d1b38d88b58609336b2c2889cff5cadc28e88115 | Text | 7,931 | 170 | # NequIP
NequIP is an open-source code for building E(3)-equivariant interatomic potentials.
[](https://nequip.readthedocs.io/en/latest/?badge=latest)
**PLEASE NOTE:** the NequIP code is under active developm... |
74cf2ff1e9db1140bef21197a2c4ac2b0e324cb5d1734648e8ca0ee1c74a13dc | Text | 7,975 | 302 | # 🌊 BiLSTM CO₂ Prediction for Antarctic Waters
### *Deception Island - Advanced Deep Learning for Marine Carbon Dynamics*
---
<div align="center">
[](https://python.org)
[](https://tens... |
37f689bd23db856470bec0c32ad92da38b30f88210cb280c6ca9b6abf11e3e96 | Text | 7,982 | 68 | # Simulation Insights on the Compound Action Potential
This repository provides the code necessary to replicate the results of the paper [Simulation Insights on the Compound Action Potential](https://www.biorxiv.org/content/10.1101/2024.10.16.618681v1.full).
In broad terms, the workflow of the paper is as follows:
... |
4dfaccc65b48e3489205cf93f399e77d6e3104032bad30d29793bf357730b53b | Text | 8,040 | 115 | ## General Information
Study: Genome-wide analysis of brain age identifies 59 associated loci and unveils relationships with mental and physical health
Contact: philippe.jawinski@hu-berlin.de | https://orcid.org/0000-0002-2994-3075
Zenodo doi: 10.5281/zenodo.14826943
## Available Files
brainage2025.discov.gm.gz - GWAS... |
627e5d6d1cd20414e1485763ddbca15427c9ba2de6f3d4e6945f5b5226764dde | Text | 8,042 | 169 |
See links to instruction sections below:
- [Designing a sample sheet](#how-to-make-a-sample-sheet)
- [Running the pipeline](#how-to-run-the-pipeline)
- [Testing and updating the pipeline](#testing-and-updating-the-pipeline)
- [Checklist before pull requests](#what-to-do-before-pull-requests-or-feature-additions)
The... |
e52e331c5d5476ca5289983e8c16409a9cde67c371ab50f93b547d2615a565af | Text | 8,075 | 212 | # Reproducing Results with Additional 3D Information
This guide explains how to reproduce results using extra 3D information with ChemTorch. **Step 1** covers installing all the necessary dependencies. **Steps 2** and **3** are optional, as the files they produce are already available in the `data` folder.
> **⚠️ At... |
0ff2d232d13c487a1d4a9a1f3dc483fa0555efcc167bee83652c62bd67fdb3c4 | Text | 8,174 | 193 | # eAlz: lightweight explainable models for early Alzheimer's detection
[](https://github.com/falahsheikh/eAlz/actions/workflows/tests.yml)
[](https://doi.org/10.... |
a3bef952e2d314fff0427dd9bf53698baff85076608baa6d7c726d5e6332507e | Text | 8,188 | 127 | # Amethyst
*A comprehensive toolkit for single-cell methylation sequencing data analysis*
<!-- badges: start -->
<!-- badges: end -->
<p align="center">
<img src="https://github.com/lrylaarsdam/amethyst/blob/main/images/amethyst.png?raw=true" alt="Amethyst" width="250"/>
</p>
## Welcome to Amethyst!
Single-cell se... |
ee84cdf2a39cffef4f8e97e108b66ddfbb6d7ce0f380f64787d1e1cba64a9ee2 | Text | 8,256 | 206 | [](https://gitlab.com/cheminfIBB/pafnucy/commits/master)
**Pafnucy [paphnusy]** is a 3D convolutional neural network that predicts binding affinity for protein-ligand complexes.
It was trained on the [PDBbind](http://pubs.acs.org/doi/a... |
a8d0e6ec722b7c62ea514b8803f0d9322085c47b26f2cd08bdf9f5b9836abc16 | Text | 8,258 | 191 | # Motor-Circuit vs Single-ROI Features for Parkinson's Disease Subtype Classification
[](https://www.python.org/downloads/)
[](LICENSE)
[![Paper](https://img.shields.io/badge/paper-preprint-orang... |
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