sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1d8d11e45c9e042e9e75619a7fac5993819a546a09dadb4c8556479787a0796c | Text | 14,909 | 252 | # AutoTransOP: translating omics signatures without orthologue requirements using deep learning
Github repository of the study:
> AutoTransOP: Translating Omics Signatures without Orthologue Requirements using Deep Learning <br>
> Meimetis, N., Pullen, K. M., Zhu, D. Y., Nilsson, A., Hoang, T. N., Magliacane, S., & Lau... |
88c7702414222ab7bdc57ed54b8618177067410ba96d401c5c6c882fe1d41d78 | Text | 14,960 | 329 | <div align="center">
# Two-stage video-based convolutional neural networks for adult spinal deformity classification
[](https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1278584/full)
</div>
## Abstract
**Introduction**: Asse... |
1f5b38f860c0ec15121c863e677b19a3ac4e6b5652a592f68b020075687f4081 | Text | 15,064 | 218 | # RodentAddiction
Annika Vannan, email: avannan@asu.edu \
https://github.com/SexChrLab/RodentAddiction \
Last modified: 05/22/2023
## Project Description
The purpose of this project is to create a pipeline for prioritizing candidate genes identified from preclinical rodent neuroscience studies based on translational v... |
bbfae4d9cd5b43d5901d47c79c9c96e153f8b9a8728315482ac3820c089418e1 | Text | 15,245 | 278 | 
## Current Version: v1.4.0 (released May 10, 2024)
- Added support for compressed (gz) hapcount/dosage and phenotype files.
- Improved file reading efficiency by implementing fread in chunks, mitigating memory errors.
- Implemented parallel processing for regression, resulting in significa... |
69ad75cdc622c7bb335df1252407c70a8a34a338474d50ad886967bc03a74621 | Text | 15,366 | 195 | # Gluon CV Toolkit
[](./LICENSE)
[](https://pypi.python.org/pypi/gluoncv)
[
# General
This repository contains the source code accompanying the paper [Modelling local and general quantum mechanical properties with attention-based pooling](https://www.nature.com/articles/s42004-023-01... |
d5ff384eb7c3637f389f48d3b320d1ec9bdfcd211fbd510510068add07786b85 | Text | 16,303 | 215 | # CLOUDe
CLOUDe is an R implementation of Campelo dos Santos, DeGiorgio and Assis' (2023) suite of machine learning methods for predicting evolutionary targets of gene deletion events from expression data in two species.
-------------
Citing CLOUDe
-------------
Thank you for using the CLOUDe classifier and predictor.... |
3cf7cc49f91382d1c070d71c20aaee0546be34afed4936f8c5942a442496c353 | Text | 16,353 | 280 | # cuteSV
[
Author: Piotr Różański <piotr@develancer.pl> ⓒ 2015–2023
**Cite as:**
> Piotr T. Różański:
> _empi_: GPU-Accelerated Matching Pursuit with Continuous Dictionaries,
> ACM Transactions on Mathematical Software, Volume 50, Issue 3, Article 17 (2024),
> DOI: ... |
fa469623bebcd7184ec13179e739a732dcdda652ae17060978a2576f850dbb80 | Text | 16,457 | 189 | # DeepGAMI - Deep auxiliary learning for multi-modal integration and estimation to improve genotype-phenotype prediction
Genotype-phenotype association is found in many biological systems such as brains and brain diseases. However, predicting phenotypes from genotypes remains challenging, primarily due to complex unde... |
278225d06de4e612b03e5a24015ab1f74949853f5cb1ca95305eac1ee74a7592 | Text | 16,794 | 153 | # OPaver: Omics Pathway Viewer
OPaver is a web-based tool to integrate multiple types (e.g. transcriptomics and proteomics) and time series data to KEGG maps. OPaver is written in Python3 and leveraging Python's http.server module to provide a web-based interface for users. The image below is a preview screenshot for ... |
eb5066afba05606dce7978e561a9593194037397ae9eed9570b0065b9aaa8f08 | Text | 16,819 | 353 | fast BAM/CRAM depth calculation for **WGS**, **exome**, or **targeted sequencing**.
[](http://bioconda.github.io/recipes/mosdepth/README.html)
](https://zenodo.org/badge/latestdoi/498570644)
Model metamers reveal divergent invariances between biological and artificial neural networks.<br>
Feather, Leclerc, Mądry & McDermott. Nature Neuroscience (2023).
==============
<img align="right" height = 240 src="https://github.com/adgpta/NuCLear/assets/77382748/b9d478f2-9fd3-4b71-8d13-59aea0c0fb59">
### Nucleus-instructed tissue composition using deep learning - _A neural network based cell ty... |
e76bd4540b89c99edd820aafcf5d2a778315dd8069c440196bf35c77b0d2dc5f | Text | 17,208 | 191 | Our program will help you find loci under selection with a bulked segregant approach and produce publication-quality figures. We emphasize user-friendliness so do not hesitate to email Andre Kurlovs (a.kurlovs@gmail.com) if you have any questions or concerns.
This code was used in [Wybouw et al, 2019](https://doi.org... |
a79ebdcec5f66ba79fe419d226a1deba54bf452189c314ba9cb52f43e15e5065 | Text | 17,285 | 326 | <h1 align="center">
windows-rapl-driver
</h1>
<p align="center">
<img src="https://repository-images.githubusercontent.com/421079628/f695abc0-c8e6-46a3-a6f4-6c7c0f617b87" width="800">
</p>
# Windows driver for RAPL metrics gathering
## Installation (for testing/troubleshooting purposes, in test mode)
### Enab... |
8abb18c2ada5d4bc2948125edae4d688a641e9a4273f6093341dac473d344f52 | Text | 17,378 | 449 |
# Solving Olympiad Geometry without Human Demonstrations
This repository contains the code necessary to
reproduce DDAR and AlphaGeometry,
the two geometry theorem provers
introduced in the [Nature 2024](https://www.nature.com/articles/s41586-023-06747-5) paper:
*<center>"Solving Olympiad Geometry without Human Demo... |
d4b656906942a5847c82b69c82d31f61259b91541a5aa707f6f19f9a56ec4410 | Text | 18,029 | 605 | .. image:: https://docs.celeryq.dev/en/latest/_images/celery-banner-small.png
|build-status| |coverage| |license| |wheel| |semgrep| |pyversion| |pyimp| |ocbackerbadge| |ocsponsorbadge|
:Version: 5.7.0rc1 (Collider)
:Web: https://docs.celeryq.dev/en/stable/index.html
:Download: https://pypi.org/project/celery/
:Source... |
74a4e43fc11dc619dd8088f20c59457f45c6f5bb3908d9461507c67589b8dbe8 | Text | 18,184 | 402 | <h1 style="word-break:break-word;">Towards Efficient COVID-19 CT Annotation: A Benchmark for Lung and Infection Segmentation</h1>
- [Task 1: Learning with limited annotations](#1)
- [Task 2: Learning to segment COVID-19 CT scans from non-COVID-19 CT scans](#2)
- [Task 3: Learning with both COVID-19 and non-COVID-19 CT... |
20683e52228a25abf5c6f98382d25b5f1e63457f320ea454c2700385caa9bc9b | Text | 18,470 | 164 | # Frontiers FLIM Denoising
This is the folder contains all the results used in the pre-trained CNN for FLIM lifetime denoising and phasor denoising.
# Installation of the plugins
[Simple Instructions](https://github.com/ND-HowardGroup/Instant-Image-Denoising/blob/master/Plugins/Instructions_to_Install_Image_denoising_... |
a41aea1c4883779a3805472dd617a4c08f9ab6114ad64a06280579cd8103a48b | Text | 18,474 | 308 | # ensembl-vep
[](https://github.com/Ensembl/ensembl-vep/blob/release/116/LICENSE)
[](https://coveralls.io/github/Ensembl/ensembl-vep?branch=relea... |
09cc52974c29bc72020d8dd83ed9b821017ac65e170020a1af0ea963731a6de3 | Text | 18,643 | 221 | # xyz2swc
This repository contains the source code for the *xyz2swc* software — a universal online service for converting digital reconstructions of neural morphologies into standardized SWC format.
## Features
- Online file converter app (accessible at <https://neuromorpho.org/xyz2swc/ui/>, and is our preferr... |
21dd82ed36349cf3e0d79bfd7a11adc0b40a0ea5657a58a22c120ad6456be53b | Text | 18,713 | 287 | # <img src="img/mTRF-Toolbox_logo.png">
[](https://github.com/mickcrosse/mTRF-Toolbox/graphs/commit-activity)
[](https://sourceforge.net/projects/aespa/files/latest/dow... |
42f4609678c0d1fdc71ccfb3c36bb8cdb5a2d0007206606c4518693cc7d8a2a0 | Text | 19,563 | 332 | ThermImageJ - Functions and Macros for ImageJ
================
ThermImageJ is a collection of ImageJ functions and macros to allow for import and conversion of thermal image files and to assist in extracting raw data from infrared thermal images and converting these to temperatures using standard equations in thermogr... |
2d325a7612c4a77c1b0a30cccce6d15d12647c59de8e8ffb1fe108a8f9fc651a | Text | 19,872 | 461 | # DepMap Public 22Q1
##############
## Overview ##
##############
This DepMap release contains data from CRISPR knockout screens from project Achilles, as well as genomic characterization data from the CCLE project.
###############
## Pipelines ##
###############
### Achilles
This Achilles dataset contains the res... |
c87032a5afa779526455ae816027fc5a8630986879ba8fe2e3e83424c3b708bd | Text | 19,927 | 468 | [](https://github.com/tseemann/snippy/actions/workflows/CI.yml)
[](https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html)
, a pharmacology-informed neural network that enables model discovery from longitudinal tumor size data. This implementation of TDNODE p... |
0fe6280bc258c239836933dff2c033c14d0d8e84333364d20d09a01f234a4667 | Text | 20,297 | 490 | # arpack-ng
[](https://github.com/opencollab/arpack-ng/actions/workflows/build-ubuntu.yml)
[](https://github.com/openco... |
b9da8f87142a7342a1b9f9a87ad11843c294149c899f0883b69175def0d90cd4 | Text | 20,586 | 251 | # NeuroGym
| Badges | ... |
835966ffa1fdac56361fa5b8a9a1c07a60689a87e2961cdf6a4f2ee7a6467358 | Text | 20,792 | 403 | # Efficient Pre-Trained CNNs for Audio Pattern Recognition
In this repository, we publish the pre-trained models and the code described in the papers:
* [Efficient Large-Scale Audio Tagging Via Transformer-To-CNN Knowledge Distillation](https://arxiv.org/pdf/2211.04772.pdf). The paper has been presented in
[ICASSP 20... |
119ff4c5a5a0cb4d54e3df7b0ad1d31c9e052b119cf9b00e6f5d3d21e78a26c7 | Text | 20,810 | 231 | # Multi Atlas Segmentation and Morphometric Analysis Toolkit (MASMAT)
> Originally designed for mouse brain MRI, but is applicable to any spicious (e.g. Non-human primate, or even human neuroimages)
Author: Da Ma (dma@wakehealth.edu; d.ma.11@ucl.ac.uk)
## Description
> Automatic brain structural parcellation throug... |
673d173418931cca0ba44ed7db21606426597b9fd6d47dcf4c5492d119251510 | Text | 20,985 | 149 | # Installation of the plugins
[Simple Instructions](https://github.com/ND-HowardGroup/Instant-Image-Denoising/blob/master/Plugins/Instructions_to_Install_Image_denoising_plugins.docx)
# Instant-Image-Denoising
This repository includes the code used for the image denoising of our Noise2Noise and DnCNN ML models traine... |
48468fec42bcb7af95fc6d2fd980bccfb85cd07a982590316a3fa7b7a0b0370f | Text | 21,237 | 471 | # COVID-Net Open Source Initiative
**Note: The COVID-Net models provided here are intended to be used as reference models that can be built upon and enhanced as new data becomes available. They are currently at a research stage and not yet intended as production-ready models (not meant for direct clinical diagnosis), ... |
b3f41c6fb0d88af1f3f591b6df41d458281dc3a28241053a236ef173589773de | Text | 21,329 | 266 | # Bertalign
An automatic mulitlingual sentence aligner.
Bertalign is designed to facilitate the construction of multilingual parallel corpora and translation memories, which have a wide range of applications in translation-related research such as corpus-based translation studies, contrastive linguistics, computer-as... |
6ecd1dcea1f796db3f772e270d541687991ace35260fef93db7bb342d8c30f9d | Text | 21,914 | 357 |
<p align="center">
<img src="https://raw.githubusercontent.com/shap/shap/main/docs/artwork/shap_header.svg" width="800" />
</p>
---
[](https://pypi.org/project/shap/)
[](https://anaconda.org/conda-forge/shap)
![Lic... |
6f3a04e5b4ad7ba38054c5b9d989f1260b3df84f415ea970017036aca80f179b | Text | 22,937 | 356 | # Manifold discovery and analysis
This code implements the manifold discovery and analysis (MDA) algorithm presented in "Revealing Hidden Patterns in Deep Neural Network Feature Space Continuum via Manifold Learning, Nature Communications, 2023".
Please run demo_MDA.ipynb for analyzing deep learning features for five... |
bbb20a84a004534ad8264a37b2350935063a5fbdfd8d3e9611b21a440167b23f | Text | 23,261 | 591 | # Fiber photometry analysis
MATLAB toolbox to process, plot and export fiber photometry data.
## Prerequisites
- [MATLAB][MATLAB] (last tested with `R2023b`)
## Installation
- Install [MATLAB][MATLAB] with the following toolboxes:
- Curve Fitting Toolbox (for `curvefit`, `fittype`, ...)
- Signal Processing Toolbox ... |
b0ff857824f1b5f9695689182b9b022e2a2fdbc4e2d04bfb2f87e267436633a5 | Text | 24,950 | 447 | # larvaworld
<p align="center">
<a href="https://github.com/nawrotlab/larvaworld/actions/workflows/ci.yml?query=branch%3Amaster">
<img src="https://img.shields.io/github/actions/workflow/status/nawrotlab/larvaworld/ci.yml?branch=master&label=CI&logo=github&style=flat-square" alt="CI Status" >
</a>
<a href="h... |
daccae018c8f3f991159f796551141b5db9fcc739483465a6b55db7dead09c67 | Text | 25,073 | 314 | <p align="center">
<img src="https://github.com/Nico-Curti/Deepskin/blob/main/img/logo.png" width="128" height="100">
<br>
</p>
| **Authors** | **Project** | **Documentation** | **Build Status** | **License** |
|:------------:|:-----------:|:------------------:|:----------------:|:-----------:|
| [**N. Curti**](... |
0dbaba56da1c8372d460956e2609bfb89acf8f3aadd65d132b1697d221069619 | Text | 25,270 | 604 | # FlashAttention
This repository provides the official implementation of FlashAttention and
FlashAttention-2 from the
following papers.
**FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness**
Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré
Paper: https://arxiv.org/abs/2205.... |
28fa40c11cd67a4af9ae4841c545b4658663eca6a1216559b05b739158af1f8b | Text | 25,574 | 332 | # annotate_my_genomes
Transcriptome annotation pipeline using short and long sequencing reads from non-model (and model) animal organisms.
#### See publication here: https://doi.org/10.1093/gigascience/giac... |
08255efd40f9b49229b3006cbeda7468c65b0d65376cb192a4f9a7d63477d6a0 | Text | 25,885 | 345 |
Shield: [![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa]
This work is licensed under a
[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].
[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]
[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-... |
57ca3ce3d48808a5d974e6c6e851f4bd83a6d7bbe4bd55f2b977ce37041acc58 | Text | 28,006 | 379 | All the code used in the development and testing of "Evaluation of surface-based hippocampal registration using ground-truth subfield definitions"
written by Jordan DeKraker at McGill University under the supervision of Alan Evans and Boris Bernhardt
Each original dataset is in the `BIDS/` directory, including manua... |
c91792a286d31a875cf1c728e6074d36b40a9a4ed2a7cbe94fe0e82485fa2bdd | Text | 28,745 | 140 | [](https://travis-ci.org/datalad-handbook/book) [](http://handbook.datalad.org/en/latest/?badge=latest)
[
The goal of this repo is:
- to help to reproduce research papers results (transfer learning setups for instance),
- to access pretrained ConvNets with a unique interface/API inspired by torchvision.
<a href="https://travis-ci.org/Cadene/pretrained-models.pytorch"><i... |
c304c1adde7bf9b618d7c5833d28ce3ee272fbfc6876da1cf748075bf0dcfc46 | Text | 29,493 | 410 | [](https://github.com/torognes/vsearch/actions/workflows/build-and-test.yml)
# VSEARCH
## Introduction
The aim of this project is to create an alternative to the [USEARCH](https://www.drive5.com/usearch/) tool develo... |
6fdaeb6353afa1c9353b09fe5f0e73c1983000a0c17cf06518be4b240c164f23 | Text | 29,992 | 564 | # ***ATTENTION***
Before opening a new issue here, please check the appropriate help channel on the [KneadData bioBakery Support Forum](https://forum.biobakery.org/c/infrastructure-and-utilities/kneaddata/8) and consider opening or commenting on a thread there.
For additional information, visit the [KneadData Tut... |
aa2b8ef7d73c98977570d1649b81367f8b959fb5eb41f836ad3f6dcdaef73a29 | Text | 30,313 | 607 | # Open Chinese Convert 開放中文轉換
[](https://github.com/BYVoid/OpenCC/actions/workflows/cmake.yml)
[](https://github.com/BYVoid/OpenCC/actions/workflows/bazel.yml)... |
68eef8af35d4accf98c744eaf4a522be4c887dd9284af3de64e7132ce79189f6 | Text | 30,686 | 148 | # Paper 7 AD cross-cohort — methodology evaluation testsuite
> **External readers start here.** This testsuite contains the codebase
> behind the Paper 7 manuscript *HC-Anchored Rank Normalization for
> Cross-Cohort EEG Classification of Alzheimer's Disease: An Open
> Methodology with Held-Out Validation*
> (`papers/p... |
d28cd816c89036777e93aef3ba6d5e30d9dc31c3706471a7a307abff692d7556 | Text | 32,170 | 703 | ThermImageJ - Thermal Image Functions and Macros for ImageJ
================
<img src = './images/ThermImageJSticker1.png' align="right" height="165">
ThermImageJ is a collection of ImageJ functions and macros to allow for
import and conversion of thermal image files and to assist in extracting
raw data from infrared... |
1b73d5693e185d37ac38ba2961b78ee9b442744bea45fcf4588672b71bd00f86 | Text | 35,552 | 163 | [](https://ci.appveyor.com/project/mih/book/branch/main)
[](https://github.com/datalad-handbook/book/actions/workflow... |
274c96f82540873225e2e352981317712b0a164a783acfd194688353fd466108 | Text | 36,716 | 1,290 | [](https://travis-ci.org/rajewsky-lab/mirdeep2)
# miRDeep2 `README`
## About
Authors: Sebastian Mackowiak & Marc Friedländer
This is miRDeep2 developed by Sebastian Mackowiak & Marc Friedländer.
miRDeep2 discovers active known or novel mi... |
12c4c8c971df193bbcebcd51ae6ce47bde4dd1767c14fe917c94b22760aa9e0c | Text | 37,367 | 329 | # Mesoscopic Model 1.0
### A discrete, stochastic, on-lattice, multicompartmental, mesoscale and 3D computational simulation tool to study evolutionary dynamics and heterogeneity during tumor growth
## 1. Description
Here we put forward the mesoscopic model, a simulation platform intended to reproduce tumor growth a... |
e94f4272f14b99031df72bbe92f5501bb3cdc51c0152a3656bfe834b737d97d2 | Text | 37,871 | 736 | # <img src="https://raw.githubusercontent.com/johnmarktaylor91/torchlens/main/images/logo.png" width=8% height=8%> TorchLens
[](https://pypi.org/project/torchlens/)
[](https://pypi.org/pr... |
5e5b20b776043450c95ac871646f67404bd0163ebd222fbfd57fbc280ef84fa1 | Text | 38,333 | 682 | # Scripts for training and validating neural network models for gnina
* train.py - Takes a model template and train/test file(s)
* predict.py - Takes a model, learned weights, and an input file and outputs probabilities of binding
* clustering.py - Takes an input file, and outputs clustered cross-validation train/t... |
c2ea9cef8b2bfd9af7b50e3fd949449dedf6edec0a650c227b999cda62396840 | Text | 38,565 | 302 | <div align="center">
<p>
<a href="https://www.ultralytics.com/yolo/yolo27?utm_source=github&utm_medium=social&utm_campaign=yolo27-launch-2026&utm_content=banner" target="_blank">
<img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png" alt="Ultralytics YOLO ... |
ea88cc9df413127c3d84fcf566e9ac4d4e47142ee592f0b7ca79a0d32e9d1c43 | Text | 42,720 | 489 | <a name="top"></a>
[](https://github.com/lightly-ai/lightly/blob/master/LICENSE.txt)
[![Unit Tests](https://gi... |
36aca208f1f4bcd822917bbf1782edf819f61de79e636918c7e66b68dc106ab6 | Text | 45,079 | 525 | # ReplayBG
<img src="https://i.postimg.cc/gJn8Sy0X/replay-bg-logo.png" width="250" height="250">
[](https://github.com/gcappon/replay-bg/COPYING)
[](https://github.com/gc... |
689f5288bcd55fe267fdfa69c121342e8a74a5d56eff2fdac5f81198ffdc6196 | Text | 45,119 | 768 | # CLAWS (CNAG's Long-read Assembly Workflow in Snakemake)
Snakemake Pipeline used for de novo genome assembly @CNAG. It has been developed for Snakemake v6.0.5.
It accepts Oxford Nanopore Technologies (ONT) reads, PacBio HFi reads, illumina paired-end data, illumina 10X data and Hi-C reads. It does the preprocessing ... |
7dbb9458ba3656451b07307270078f676127500f6b11a431d3d0b0416f56c8ad | Text | 67,597 | 575 | [python-img]: https://img.shields.io/github/languages/top/yueliu1999/Awesome-Deep-Graph-Clustering?color=lightgrey
[stars-img]: https://img.shields.io/github/stars/yueliu1999/Awesome-Deep-Graph-Clustering?color=yellow
[stars-url]: https://github.com/yueliu1999/Awesome-Deep-Graph-Clustering/stargazers
[fork-img]: https:... |
ecf16f383418b130f45a37ad9330067c167b628c4a5380c94a991cd5b02f052c | Text | 102,610 | 519 | # aging-clock —— 蛋白质组衰老时钟的公开数据复现环境
> 路线 A：**纯计算、零生物样本、零试剂**，复现英矽智能 rentosertib 研究
> （*Nature Biotechnology* 2026, DOI 10.1038/s41587-026-03286-y）的分析链。
>
> 建立日期：2026-09-11 ｜ 路径刻意用 ASCII（`E:\aging-clock`）以规避中文用户名导致的 pip/构建问题
---
## 快速开始
```bat
E:\aging-clock\run_all.bat
```
分步：
| 命令 | 作用 |
|---|---|
| `venv\Scripts... |
8f0a98d86fb4563abd41cafd3270cc6733347889a5b09206593970b5eb50fc16 | Text | 200,459 | 523 |
<!DOCTYPE html>
<html
lang="en"
data-color-mode="auto" data-light-theme="light" data-dark-theme="dark"
data-a11y-animated-images="system" data-a11y-link-underlines="true"
data-css-features="site_disable_smooth_scrolling"
>
<head>
<meta charset="utf-8">
<link rel="dns-prefetch" href="htt... |
47f5d8874607d379a85138c974062e842357531eabeccbeb5492bb3c548e4451 | TypeScript | 49 | 1 | export { useFilterObjectArray } from "./filter";
|
7671bda2c8c9764bc3a7d7707954c053702c158506d4d77b168f2bd8b1eba2a0 | TypeScript | 54 | 1 | export { vGTooltip } from "@galaxyproject/galaxy-ui";
|
e13cc26dd44291542a0e35cfb676be3afb6f075b0a31c2f23672b81f5f3065b8 | TypeScript | 56 | 1 | export { useMarkdown } from "@galaxyproject/galaxy-ui";
|
2bd28061f3eb6611aa9ad1f1cd4f679ceb630fb19a512808db62e1b3aa4c24db | TypeScript | 62 | 1 | export { type QuotaUsage, toQuotaUsage } from "./QuotaUsage";
|
c0f7fbb155a507a1991c074e54429275464b823633e4fc7f69121f8d9c241ead | TypeScript | 62 | 1 | export { useResolveElement } from "@galaxyproject/galaxy-ui";
|
7dbc39b326acaa71c49e19ffd9a0c8819f9a85a070c1056bc5ff751be0445bc4 | TypeScript | 63 | 1 | export { useAccessibleHover } from "@galaxyproject/galaxy-ui";
|
930b1dd5f1ba276afd1d5940a60902cf32265ed841b4ad9130bd7ec54bdf2200 | TypeScript | 73 | 4 | declare module "*.yml" {
const data: any;
export default data;
}
|
400f1b4a203b01aa4c9f5f0fda2b3b3e14fa6f61f5a6e51365918fce7096958c | TypeScript | 78 | 4 | declare module "*.vue" {
import Vue from "vue";
export default Vue;
}
|
05c2f7cf0a9c9f8336474412592c74eb9e8e64cc5631e4ef54929ccdf5647162 | TypeScript | 79 | 3 | declare module "node-pre-gyp" {
export function find(path: String): any;
}
|
a8423b7386fc95504b6c75147eb5d2bd47d88741240cbe4e50b636026795637b | TypeScript | 80 | 1 | export { type HasTitleProps, useCurrentTitle } from "@galaxyproject/galaxy-ui";
|
7aa88abd9e338aa7c0a85a24974d23065a80d9717e65534b3ec542f307b5f087 | TypeScript | 85 | 1 | export { type ClickableProps, useClickableElement } from "@galaxyproject/galaxy-ui";
|
321f015efaf5ba91c645a869cf195dc31b86f30644823440f6f50580d02a6bf6 | TypeScript | 86 | 4 | export interface HelpElementReference {
element: HTMLElement;
term: string;
}
|
d12ff8de93abb4239c942ef0211f76b7b2969056985246c2cccdc1a54380c9a2 | TypeScript | 89 | 1 | export { type components, type GalaxyApiPaths } from "@galaxyproject/galaxy-api-client";
|
6d0db249d253e0f723f15c84cc53d351eb4d5e719570db8eb1480f9db7710361 | TypeScript | 90 | 1 | export type DetailsLayoutSummarized = "both" | "annotation" | "tags" | "none" | "hidden";
|
86af2c81802b45651db013a8214b6e501bf922b0f73afae61505fd7aa3c1ec6d | TypeScript | 90 | 5 | export interface DataValuePoint {
id: string;
label: string;
value: number;
}
|
41fe675d9698062de819d8fc7a0b4076ce912e68e0389c68136fb4396dca3cd2 | TypeScript | 98 | 5 | export interface OptionType {
id: string;
name: string;
data?: Record<string, any>;
}
|
edfc07c45ea1d1a19b9af4288c8536eafcbb3985ab1cb3ffebeecb069ec2a004 | TypeScript | 103 | 3 | // Build-injected globals
declare const __buildTimestamp__: string;
declare const __license__: string;
|
4700d1c6b95c1aedb1ef4713aa884a540dc0eb98eaa23fdb55edfbf64f01cf16 | TypeScript | 119 | 3 | import type { components, paths as GalaxyApiPaths } from "./schema";
export { type components, type GalaxyApiPaths };
|
46c1107eba024262ccfff7a2c103843fa00a2bd3422280d58ac6fd6e80ea3633 | TypeScript | 126 | 5 | import { createPinia, setActivePinia } from "pinia";
export function setupTestPinia() {
setActivePinia(createPinia());
}
|
a0e93993cfe98e276983faf29fc1b1dcf4168ca2eaa2b8655cc89f5f4957014c | TypeScript | 142 | 5 | export {
DEFAULT_TOOLTIP_HOVER_DELAY_MS,
INTERACTIVE_POPOVER_CLOSE_DELAY_MS,
useDelayedAction,
} from "@galaxyproject/galaxy-ui";
|
ddb6e125d913915068e189f8735d8bf4828b4cff34fb84c486d7c75dfc79514c | TypeScript | 142 | 3 | import type { components } from "@/api/schema";
export type UserConcreteObjectStore = components["schemas"]["UserConcreteObjectStoreModel"];
|
a340047dd1e4f80001261685a936cfe89449d7b7ea74a9cb22b3fe19c052e4d3 | TypeScript | 154 | 7 | export type WhichListBuilder =
| "list"
| "list:paired"
| "rules"
| "list:paired_or_unpaired"
| "list:list"
| "list:list:paired";
|
03c844ee4f7e733986f70e5ca4e967dccfd127a3176c54d9d0a2cc7d6426eee5 | TypeScript | 160 | 5 | type BorderVariant = "primary" | "default";
export function borderVariant(isPrimary: boolean): BorderVariant {
return isPrimary ? "primary" : "default";
}
|
9aa6370bdbe8c9839cee36c006e322c2c08c936c2d870eb9ca4ddb241f0d36de | TypeScript | 163 | 6 | // Interface to match the `Workflow` interface from `WorkflowCard`
export interface SelectedWorkflow {
id: string;
name: string;
published: boolean;
}
|
d45161e1650fe90252e13d8be079b347f3ca5318b75515158bc3b717b931e52e | TypeScript | 163 | 2 | export type { SelectionItem } from "@/components/SelectionDialog/selectionTypes";
export type { RemoteFileBrowserMode } from "@/composables/useRemoteFileBrowser";
|
3075aa77cadcd019a1ec91c7edaf1364ecf6ecebf315b68e417dc56f24dd9d71 | TypeScript | 171 | 6 | import { type ClassValue, clsx } from "clsx";
import { twMerge } from "tailwind-merge";
export function cn(...inputs: ClassValue[]) {
return twMerge(clsx(inputs));
}
|
5aa9894000f4666407536b5f3da6c3cb350a2536587cfe0082c327c53345856b | TypeScript | 174 | 7 | // Vue SFC module declaration
declare module "*.vue" {
import type { DefineComponent } from "vue";
const component: DefineComponent;
export default component;
}
|
954c62b7fd4fbcce93cb36a43c3ffc4ff4ee75de1b7e6e433d568231abbdc35c | TypeScript | 177 | 2 | // Lives in galaxy-ui so the Tool Shed can use it too; client code and tests keep this path.
export { type SanitizeHtmlBinding, vSanitizeHtml } from "@galaxyproject/galaxy-ui";
|
709650387516a1a40562b3f8351a13d41e1d59d94c6bf9d73c37b66bbb5171fe | TypeScript | 179 | 6 | import { ref } from "vue";
// set to always mock in tests/vitest/setup.ts
export function useUserLocalStorage<T>(_key: string, initialValue: T) {
return ref(initialValue);
}
|
e94abf8fff3acdaaacafbb788700997f6dd2f82b65f99a921b8cf4f25a5a1666 | TypeScript | 186 | 3 | import { buildInstanceRoutingComposable } from "@/components/ConfigTemplates/routing";
export const useInstanceRouting = buildInstanceRoutingComposable("/file_source_instances/index");
|
0656b73648fafb7db205d0117f291da8432bea81707d3f75dd39c7e8ec3beb56 | TypeScript | 187 | 3 | import { buildInstanceRoutingComposable } from "@/components/ConfigTemplates/routing";
export const useInstanceRouting = buildInstanceRoutingComposable("/object_store_instances/index");
|
e5480e810e12add1cb11409a1960cc2b75d09d2d45c8f48eb98729ac8d02e332 | TypeScript | 189 | 9 | export type ItemUrls = {
display?: string;
edit: string;
rerun?: string;
visualize?: string;
reportError?: string;
showDetails: string | null;
view?: string;
};
|
5f1fa3f84b3f642af7963e4ea7163c93aec2dc63f21cd7a231b90df8219a6fb2 | TypeScript | 193 | 2 | // Lives in galaxy-ui so the Tool Shed can use it too; client code and tests keep this path.
export { PROFILE_CONFIGS, sanitizeHtml, type SanitizeHtmlProfile } from "@galaxyproject/galaxy-ui";
|
dbc30346b5d201a568dac741d152cfcf422140d0a3c5b825562af502e3fbeb55 | TypeScript | 207 | 8 | import { computed } from "vue";
// set to always mock in tests/vitest/setup.ts
export function useHashedUserId() {
const hashedUserId = computed(() => "fake-hashed-id");
return { hashedUserId };
}
|
9d7f82dd675852f26fdad7c63e404dac7d903f9ba6b65f9d8f90fa96a011d09b | TypeScript | 215 | 4 | import type { components } from "@/api/schema";
export type ClaimLandingPayload = components["schemas"]["ClaimLandingPayload"];
export type WorkflowLandingRequest = components["schemas"]["WorkflowLandingRequest"];
|
7d9e1198bdfc3b987975a6a7f6021fc8bb6487c12a3a68de2f1876105037268b | TypeScript | 216 | 4 | import type { components } from "@/api/schema";
export type ObjectStoreTemplateSummary = components["schemas"]["ObjectStoreTemplateSummary"];
export type ObjectStoreTemplateSummaries = ObjectStoreTemplateSummary[];
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.