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a8d1718d2ed2f14ea36fbe9d509a8e2594d2298f46676300076db0c95bdb18de | Text | 18,451 | 361 | # Beta cell activity analysis suite
Developed with python 3.11.1
## Provided sample data
We provide sample data in the folder "raw_data/"
## Raw data input
The scripts require a folder with the raw data. You are free to select the name of this folder as well as the names of the two necessary raw data files (time s... |
081e832b6e3999c5e8b4b10ade2f6c1101afc5ddc96eff29f8893b2665be5e4e | Text | 18,468 | 465 | # Dosenbach Lab Preprocessing Pipeline
### Table of Contents
- [Dependencies for Local Install](#dependencies-for-local-install)
* [4dfp](#4dfp)
* [FSL](#fsl)
* [FreeSurfer](#freesurfer)
* [Connectome Workbench](#connectome-workbench)
* [NORDIC](#nordic)
* [MATLAB Compiler Runtime](#matlab-compiler-runtime... |
0517e806a0bc70bcbfd1c010e5dc70832ab047334a49b02f7095062c802e86b4 | Text | 18,480 | 505 | # DRIFT-EM
[](https://doi.org/10.5281/zenodo.21972788)
Locate ultrathin sections randomly placed on a wafer, draw an imaging ROI
around each one, and emit a project file for ZEISS ATLAS.
```
wafer overview image
|
| detect_rectangles.py ... |
e2dacff9ad56bca50c31373a1e87041eef948721b8aa0be001a95185c375c15f | Text | 18,513 | 285 | <p align="center"><img src="https://raw.githubusercontent.com/mims-harvard/TDC/master/fig/logo.png" alt="logo" width="600px" /></p>
----
[](https://tdcommons.ai)
[](https://badge.fury.io/py/PyTDC)
[ and [paper](https://www.biorxiv.org/content/10.1101/2020.06.19.162354v2.full.pdf)
## Building docker image
The current version of regenie has the modifications created in the finngen repo, ... |
9aa905f30bb17ff07af337fe8fddf393d266434f1e8047779d70c71a521dcfb0 | Text | 18,898 | 381 | # ASL Pipeline for the Human Connectome Project
This repository contains the ASL processing pipeline scripts for the Human Connectome Project.
## Contents
- [Prerequisites](#prerequisites)
- [Installation](#installation)
## Prerequisites
The HCP list some prerequisites for their pipelines: https://github.com/Washingt... |
a0459506d77d3d39ea4d5fd052e9824bd5ef6e97b46566d6f30630a88e6b1731 | Text | 19,043 | 199 | # CRITICAL MESSAGE
## Newer Anaconda distributions break the `histo_GUI.py` script
At the moment, an older Python 3.7 distribution of Anaconda still works. Changes were made to Matplotlib in recent versions that gave warnings when running the `hisot_GUI.py` script. Those have finally become errors in the most recent d... |
0f857e5ab7d5f04bcab790a867f41f1a7c434fd93e056112d27bf56a3376a237 | Text | 19,285 | 314 | # ensembl-vep
[](https://github.com/Ensembl/ensembl-vep/blob/release/116/LICENSE)
[](https://coveralls.io/github/Ensembl/ensembl-vep?branch=relea... |
31cefd0692e2609f3737f311d31cef0d4924d4105fedce08d383c4c4b4d7dcb2 | Text | 19,296 | 196 | # Connectome utilities
Complex network representation and analysis layer
[](https://zenodo.org/badge/latestdoi/641456590)
# Table of Contents
1. [... |
6a1f68cfb7e32d2825bbe541fea6dbdcfaa474b8098f6df5ba1c7d366efa089c | Text | 19,386 | 289 | # Platforms
Windows - for all steps except Linux for after LM-EM registration (for exports to render and Neuroglancer)
Linux - should work too but currently untested (probably to adjust: call to concorde linkern for reordering, maybe add some fc.cleanLinuxPath to problematic paths with trakEM)
# Installation
Downlo... |
ad25680f666f4f97aef05bae75410982dfdc439a33cf5d510164ddc10d133829 | Text | 19,529 | 200 | > [!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/ConnectomeUtilities
# Connectome utilities
Complex network representation and analysis layer
[![DOI](http... |
681ac746e7b1520e72874637798e1cf2f3dd7048551b24db9a83f6237f1fb102 | Text | 19,663 | 252 | # <a name="top"></a>ABAnnotate - a toolbox for ensemble-based multimodal gene-category enrichment analysis of human neuroimaging data
*Are you interested in contextualising brain maps, maybe derived from case-control-comparisons, fMRI tasks, or spatial meta-analysis, across biological systems ranging from molecular an... |
64ffcbe7828fa40877ca131457725cd1ba0cc55adc448d96fc95d456e6907726 | Text | 19,675 | 373 | 
Deep learning-based estimates of global migration flows
---
[](https://www.python.org/downloads/release/python-380/)
[](https://www.python.org/downloads... |
f56a94fef529c995735e82ed25b8620641cbe1d9977cffe01784245c561a6033 | Text | 19,979 | 328 | <p align="center">
<img src="https://raw.githubusercontent.com/SeldonIO/alibi/master/doc/source/_static/Alibi_Explain_Logo_rgb.png" alt="Alibi Logo" width="50%">
</p>
<!--- BADGES: START --->
[][#build-status]
[![Documenta... |
c4f8daf7dcec3933a0c31ce91a5ea698306b9a3e2b88e61c57becb8cbeaa4bb8 | Text | 20,070 | 161 | # scBOND: Biologically faithful bidirectional translation between single-cell transcriptomes and DNA methylomes with adaptability to paired data scarcity
A sophisticated framework for bidirectional cross-modality translation between scRNA-seq and scDNAm profiles with broad biological applicability. We show that **scB... |
a133527d786a145bd599d4a0450bf70988c946ea70dd201fd652ebe79ca4a9cb | Text | 20,080 | 399 | ### [Note]
This repo contains a new custom CUDA kernel for depth-wise convolutions, which the original MinkowskiEngine does not support.
[pypi-image]: https://badge.fury.io/py/MinkowskiEngine.svg
[pypi-url]: https://pypi.org/project/MinkowskiEngine/
[pypi-download]: https://img.shields.io/pypi/dm/MinkowskiEngine
[slac... |
af247cc90282d7fd6056a15ca0712d24406c6de7a6797de2dbbb6011767ef025 | Text | 20,259 | 498 | # Trauma-Former: Real-time Prediction of Trauma-Induced Coagulopathy Using an Inverted Transformer
[](LICENSE)
[](https://www.python.org/downloads/release/python-3100/)
[![PyTorch 2.1](h... |
040cffdca71c1fd2215daa6f216241d1c992598e195e29e67f5258d3d78cf8f9 | Text | 20,341 | 410 |
<h1 align="center">
<img src="https://github.com/havakv/pycox/blob/master/figures/logo.svg" alt="pycox" width="200">
</h1>
<p align="center">
<strong>Time-to-event prediction with PyTorch</strong>
</p>
<p align="center">
<a href="https://github.com/havakv/pycox/actions"><img alt="GitHub Actions status" ... |
ca2938309f9f1a3c61514cf39f031ebb2370701f2df64341e0f5acc634925fd0 | Text | 20,406 | 165 | # scBOND: High-fidelity bidirectional translation between single-cell transcriptomes and DNA methylomes with adaptability to paired data scarcity
A sophisticated framework for bidirectional cross-modality translation between scRNA-seq and scDNAm profiles with broad biological applicability. We show that **scBOND**(a)... |
4c851e07b941341690d4801d47faa71bf53bd37e56b4e7bc6c5817de5f58e089 | Text | 20,492 | 280 | # GeneEnrich
_GeneEnrich_ is a tool used to assess enrichment of a selected set of genes in predefined biological pathways or gene sets given a background set of genes expressed in a given tissue. _GeneEnrich_ is capable of controlling for gene expression levels as a potential confounding factor. This program returns... |
b1f25e84c7a020299ab3d11b7dc226e49a35d3effb91e6f3c20ea7875bdaf34b | Text | 20,735 | 277 | # SC_FC_Coupling_Task_Personality
## 1. Scope
This repository contains scripts that were used to conduct the analyses in **"Trait-Relevant Tasks Improve Personality Prediction from Structural-Functional Brain Network Coupling"** coauthored
by Johanna L. Popp, Jonas A. Thiele, Joshua Faskowitz, Caio Seguin, Olaf Spor... |
52ba1cc6ba7cf8b5ccdc64d04e8f5ae854bbc67c98aa4c9a9287dfb82e11a01a | Text | 20,845 | 557 | # Introduction
Here we provide an overview of the preprocessing and analysis pipeline for the fMRI modality, as well as a description and instructions to use the provided code.
**Authors:** *Yamil Vidal, David Richter, Aya Khalaf*
The code for different preprocessing steps and analyses are provided in different fold... |
fade3eaa9bab438f5c3e9d6a589005ede5cf3506394edef244444cfd30483707 | Text | 21,097 | 261 | # ConnectomeInfluenceCalculator
[](https://doi.org/10.1038/s41586-026-10735-w)
[](https://www.biorxiv.org/content/10.1101/2025.07.31.667571v3)
[!... |
f360e664f3dc0510cd086340b7827800218c3c47fac536fcab57a0af7db14b84 | Text | 21,098 | 339 | # [NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size](https://arxiv.org/abs/2009.00437)
Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys
in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
**Abstract**: Neural architecture search (NAS) has attracted a lot of a... |
531f659f15259cd2e980dee4eec36260210082452af611f5c8b7ca1a041f72e8 | Text | 21,201 | 306 |
[](https://en.wikipedia.org/wiki/MIT_License)
[](https://anaconda... |
3686178d505a38cb20a94827917369bcb9d0aa44cf5154d7ddbac740ee06628d | Text | 21,234 | 194 | # RAGTruth
RAGTruth is a word-level hallucination corpus in various tasks within the Retrieval-augmented generation (RAG) setting both for **training** and **evaluating**.
RAG has become a main technique for alleviating hallucinations in large language models (LLMs). Despite the integration of RAG... |
5e8331405f47255a35b6521b8ee1809a5249ba751c54b6370d10596e3ed2bfe4 | Text | 21,293 | 336 | # GangSTR
<img align="right" src="logo/GangSTR_logo_square.png" alt="GangSTR" width="200" height="200">
GangSTR is a tool for genome-wide profiling tandem repeats from short reads. A key advantage of GangSTR over existing genome-wide TR tools (e.g. [lobSTR](https://github.com/mgymrek/lobstr-code) or [hipSTR](https://... |
3e91691e87888dbee2f3851383ad0495d9dbe3d0eced547dc271b83ba40c84e3 | Text | 21,475 | 395 | # Eggsactly
#### Egg Counting Tool for *Drosophila melanogaster* Egg-Laying Assays
## Introduction
This software project provides a web-based application to facilitate the automated counting of eggs laid by *Drosophila melanogaster* during egg-laying assays. In these experiments, specialized chambers are used to hous... |
d0f805699819cf68f82d5f0280358cc3a652b97ca282e66dd3f82ccd7485e6c8 | Text | 21,514 | 319 | <img width="303" height="102" alt="neuroesc_long" src="https://github.com/user-attachments/assets/e185a933-e27d-4436-ab1f-52a4fe389e38" />
# Hillscape_analyses
Code used in the analysis and modelling of our Hillscape apparatus, to be used in conjunction with the [available dataset](https://doi.org/10.5281/zenodo.17634... |
81729456a51d22379fc76ea33f255cae4ab155361a7b3c91fccce4a61d037900 | Text | 21,726 | 263 | [](https://opensource.org/licenses/MIT)
# Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer
<br>
Jia-Ren Lin*, Shu Wang*, Shannon Coy*, Yu-An Chen, Clarence Yapp, Madison Tyler, Maulik K. Nariya, Cody N. Heiser, Ken... |
a384ec62c86d568aeb0fe3e8a3b111f071fbcfacb937b407eb6da24fc70c823f | Text | 21,782 | 293 | # ColabFold - v1.6.3
For details of what was changed in v1.6.3, see [change log](https://github.com/sokrypton/ColabFold/wiki/v1.6.3)!
<p align="center"><img src="https://github.com/sokrypton/ColabFold/raw/main/.github/ColabFold_Marv_Logo.png" height="250"/></p>
### Making Protein folding accessible to all via Google... |
9b9a961fb7475d8882daf35fe6a486a59897a8270334f3e846f207c5c632955f | Text | 22,119 | 333 |
# CroCoNet analyses
This repository contains the code to reproduce all analyses in the
following manuscript:
#### [**CroCoNet: a framework for the quantitative comparison of gene regulatoy networks across species**](https://www.biorxiv.org/content/10.1101/2025.11.18.689002v1)
by Anita Térmeg, Vladyslav Storozhuk, Z... |
3f7f19ad6d35f1e7e6377c8b8dd9dc926274c8d89ba67f9e782f78e682274f1d | Text | 22,120 | 412 | # ecephys spike sorting -- for SpikeGLX data
Modules for processing **e**xtra**c**ellular **e**lectro**phys**iology data from Neuropixels probes, originally developed at the Allen Institute for Brain Science. This fork has been modified to run with SpikeGLX data, including inte... |
94d22bb5ebadf8f642ac9c6215d10f84eb50adaf38dac88e8d0a8cb2d26573c3 | Text | 22,261 | 571 | .. -*- mode: rst -*-
.. image:: doc/logo_large.png
:width: 600
:alt: UMAP logo
:align: center
|pypi_version|_ |pypi_downloads|_
|conda_version|_ |conda_downloads|_
|License|_ |build_status|_ |Coverage|_
|Docs|_ |joss_paper|_
.. |pypi_version| image:: https://img.shields.io/pypi/v/umap-learn.svg
.. _pypi_ver... |
475c8d833d1252aff10e779c4a9862bba6a02d01eb55d582ef976ee88040396e | Text | 22,409 | 441 | 
<hr/>
<!--- BADGES: START --->
[][#github-license]
[](https://a... |
5ac98c3d0c47bc5c3ecca67d2b8dd778a66e98f019da44cfff74710d6d984cf2 | Text | 22,447 | 105 | 
# BiaPy: Accessible deep learning on bioimages
<p align="left">
<a href="https://www.python.org/">
<img src="https://img.shields.io/badge/Python-3.11-yellow.svg" /></a>
<a href= "https://pytorch.org/">
<img src... |
67e886c36d7205d1f07eef9619c6a4ad7cbb1e81631a8aea37f66df16929a3e8 | Text | 22,636 | 559 | # Deep Learning-Based Neuroanatomical Profiling Reveals Population-Specific Brain Changes in Multiple Sclerosis: A Large-Scale Middle Eastern Study
[](https://opensource.org/licenses/MIT)
[ toolbox
[](https://doi.org/10.5281/zenodo.17177018)
<img src = "illustrations/TMFC_toolbox.png">
----------------------------... |
192db6b9a0ed634c9db2bed80dcb2836c674e8ffae846660ccb9db46ccabc94b | Text | 23,471 | 300 | ## Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer
This repository contains code to compute depth from a single image. It accompanies our [paper](https://arxiv.org/abs/1907.01341v3):
>Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset... |
b3ffb0fd57f1c77f2e159eb905f93e130fa3b0d35a202e5aa4d18880685c5b34 | Text | 23,923 | 385 |
<!--  -->
<a href="url"><img src="assets/CRA5LOGO.svg" align="center"></a>
[](https://github.com/InterDigitalInc/CompressAI/blob/master/LICENSE)
[
Modules for processing **e**xtra**c**ellular **e**lectro**phys**iology data from Neuropixels probes, originally developed at the Allen Institute for Brain Science. This fork has been modified to run with SpikeGLX data, including inte... |
92b78c078265d1ce22d12d2563d6ce5056e89fe44baa71c60e116055ad6a4a46 | Text | 24,171 | 261 | <!--
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with this work for additional information
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this... |
a1f036ec187a9c7895ffa3e0539dd0b88d3acbe7942d9287aa62eb89809f1590 | Text | 24,201 | 366 | [](https://zenodo.org/doi/10.5281/zenodo.10829243)
[ -->
**T**ools for **W**orm **A**utomated **R**ecognition & **D**ynamic **I**maging **S**ystem: A collection of pipelines for automated *C. elegans* video and image analysis using Meta's Segment Anything Model 2 (SAM2).
TWARDISv0.1 includes four indepen... |
c383665d4cf0c7080926b5751398ff12ed75cd2c3517e3b15b06faf5dc302f1a | Text | 25,328 | 362 | # Otter Knowledge
The link to the preprint of our work: [Otter-Knowledge: benchmarks of multimodal knowledge graph representation learning from different sources for drug discovery](https://arxiv.org/abs/2306.12802)
AAAI 2024: [Knowledge Enhance Representation Learning for Drug Discovery](https://ojs.aaai.org/index.ph... |
2d848733ae4671cd29de201e82b074dd7fe0382b056023ca005db89b0b89ea3c | Text | 26,092 | 400 |
<!-- README.md is generated from README.Rmd. Please edit that file -->
# spatialLIBD <img src="man/figures/logo.png" align="right" />
<!-- badges: start -->
[](https://www.tidyverse.org/lifecycle/#stable)
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://doi.org/10.1101/2025.07.31.667571)
[](https://doi.org/10.5281/zenodo.20213748)
## Bioinformatics analyst and GitHub repo maintainer
[Anton Zhelonkin, MD](https://github.com/tony-zhelonkin)
## Project supervisor
[Denis Mogilenko, PhD](https://github.com/Mogile... |
5b5c0eb53a5ec602c41d07fb321299dc2f6dc4dcebc3acf5b211df88aeb62154 | Text | 26,928 | 403 | # Dominance-Analysis : A Python Library for Accurate and Intuitive Relative Importance of Predictors
[](https://badge.fury.io/py/dominance-analysis)
[](https://pepy.tech/project/dominance-anal... |
0a957fc8bb5512a1f2060882cf63cec112b9c8f1bdb4c24a4bbb06b139e97383 | Text | 26,983 | 450 | # Toothy: a graphical user interface for curating dentate spikes
<p align="left"><img src="_img/logo.png" width=35%/></p>
# Installation
Requires Python 3.11.
Create a conda environment with Python 3.11. For example, here we create an environment called "toothy-env":
```bash
conda create -n toothy-env python=3.11
`... |
992057b33f7b0dbfe2f6f4fccfeafa83dd2b328f32cd1f545220b49a49ca5089 | Text | 28,669 | 242 | [](https://github.com/netZoo/netZooR/actions/workflows/main.yml)
[](https://github.com/netZoo/netZooR/actions/workflows/bioc-check.yml)
[, [Jiezhang Cao](https://www.jiezhangcao.com/), [Guolei Sun](https://vision.ee.ethz.ch/people-details.MjYzMjMw.TGlzdC8zMjg5LC0xOTcxNDY1MTc4.html), [Kai Zhang](https://cszn.github.io/), [Luc Van Gool](https://scholar.google... |
da31094956eea364bc1657d2750b719f64786a618d1e85cfed7d6dfbad8e79e6 | Text | 29,979 | 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... |
4b7f101da08e0588fce50c3ebff437cc7d5c3aad7c062d7265c4829f78d2c0cc | Text | 30,297 | 713 | # influencer
[](https://natverse.github.io)
[](https://doi.org/10.5281/zenodo.15999929)
[]... |
60a3ae8cecca8488f5381ef54f302396dbd1b0d82ae0d14afc92a4bfd6b34501 | Text | 30,513 | 208 | ## ESC-50: Dataset for Environmental Sound Classification
> ###### [Overview](#esc-50-dataset-for-environmental-sound-classification) | [Download](#download) | [Results](#results) | [Repository content](#repository-content) | [License](#license) | [Citing](#citing) | [Caveats](#caveats) | [Changelog](#changelog)
>
> <... |
b9cee921baf9048d2fad6140b184131dd87ca3d8d8ca8811fe1da6d52cd247da | Text | 30,583 | 849 | ################################
Welcome to ENIGMA ``HALFpipe``
################################
.. image:: https://github.com/HALFpipe/HALFpipe/actions/workflows/continuous_integration.yml/badge.svg
:target: https://github.com/HALFpipe/HALFpipe/actions/workflows/continuous_integration.yml
.. image:: https://code... |
ebc07cb5ebd5a9f2bac3abf2a61b5610d71ee90b3265c85cbd1e26c9d8e53df3 | Text | 31,839 | 641 | # NMFLibrary: Non-negative Matrix Factorization Library
Authors: [Hiroyuki Kasai](http://kasai.comm.waseda.ac.jp/kasai/)
Last page update: July 22, 2022
Latest library version: 2.1 (see Release notes for more info)
<br />
Announcement
----------
We are very welcome to your contribution. Please tell us
- NMF solve... |
c7a56a7dd461d7af86846a581ee84cd5bca24dc4b90eff5d4a1875184fc271ca | Text | 32,253 | 168 | # Derivatives
List of file derivatives generated by scripts and notebooks.
These derivatives are used for the notebooks analysis (if all files are present, all the notebooks should run correctly).
> Note: We plan to make all derivative files publicly available after peer review, so scripts can be executed without rep... |
c275a55ac78559992ba648d85abc8d8fe38aca5e84ad776b07d00c3cfddc0c43 | Text | 32,810 | 364 | # Traffic Prediction
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
Things are usually better defined through exclusions, so here are similar things that I do not include:
* NYC taxi and bike (and othe... |
dbc6582dfef13180a31a4ab83be2ab46a2ca9376c09ee854c07f12b15cf9f739 | Text | 32,845 | 399 | ## User documentation for MiXeR analyses (univariate, bivariate and GSA-MiXeR)
This repository (https://github.com/precimed/mixer) provides user documentation for MiXeR analyses (univariate, bivariate and GSA-MiXeR).
You should use this repository for most up to date instructions on how to install and run MiXeR.
Anoth... |
e9b30b8aee35e78fb87bdbbfcf837e8739f596aef5f6def89e735680d7d8b00e | Text | 33,107 | 353 | <h1 align="center" style="border-bottom: none">
<a href="https://mlflow.org/">
<img alt="MLflow logo" src="https://raw.githubusercontent.com/mlflow/mlflow/refs/heads/master/assets/logo.svg" width="200" />
</a>
</h1>
<h2 align="center" style="border-bottom: none">The Open Source AI Engineering Platform f... |
005df57d03a594f19e13a322912b7c2148a13bc0584e6bf6207b0f3398ce0b29 | Text | 34,889 | 703 | README for RSEM
===============
[Bo Li](https://lilab-bcb.github.io/) \(bli28 at mgh dot harvard dot edu\)
* * *
Table of Contents
-----------------
* [Introduction](#introduction)
* [Compilation & Installation](#compilation)
* [Usage](#usage)
* [Build RSEM references using RefSeq, Ensembl, or GENCODE annotatio... |
39a82c6f8ecfaf16872275167e98ff00109321f8de150edf5212dc9ed36f3763 | Text | 35,387 | 826 | 
# AlphaFold
This package provides an implementation of the inference pipeline of AlphaFold
v2. For simplicity, we refer to this model as AlphaFold throughout the rest of
this document.
We also provide:
1. An implementation of AlphaFold-Multimer. This represents a work in progress
and... |
33326350bb252f4c5e8454063a7e8604ca978eeda166fd7a497ef06c3d15969b | Text | 35,422 | 1,313 | 
# Installation instructions
- You can find [here](http://www.itsnetcal.com/getting-started/) the latest installation instructions.
- Install additional MATLAB toolboxes: Go to the installDependencies folder and execute the mltbx files (or drag and drop in MATLAB).
- Change default M... |
9404afdcb25c933f318a146cd602586b74a5200eb639c0fd3504600f0aa68d9f | Text | 36,208 | 739 | # Design
## Overview
This repository contains **CIPHER** (Cell Identity Projection using Hybridization Encoding Rules), a deep learning framework for designing multiplexed in situ hybridization (ISH) probe sets that can accurately identify cell types from gene expression data.
## What is CIPHER?
**CIPHER** stands f... |
ff5ecc3f0bd805b2eb5310766d730f7a8bbfc9ef96b0d26011b12a93d3d67992 | Text | 36,871 | 466 | # Decodanda
[](https://www.gnu.org/licenses/gpl-3.0)
[](https://decodanda.readthe... |
efc36c8846df26334798a92168dc9841dff8f990b9e95ab7dae49e3a65727aa3 | Text | 37,534 | 821 | # OptiGradTrust: Byzantine-Robust Federated Learning with Multi-Feature Gradient Analysis and Reinforcement Learning-Based Trust Weighting
[](https://opensource.org/licenses/MIT)
[](http... |
2bd02c4d8a7dd800c727da1bdd4d89a2a411e6bb25f9e16fed5e48b6ca072b51 | Text | 37,714 | 1,285 | # Reproducibility README
This file contains an anonymized and consolidated R workflow for the analyses performed in the manuscript:
**Identification of Potential Bioactive Constituents of *Centella asiatica* for Neurodegenerative Diseases Using Network Pharmacology and Molecular Docking**
The workflow was consolidat... |
163e3a390a16639289d93344c07b37d7abcbf9bcb327d1dbd579497f7fd4b6bb | Text | 39,076 | 491 | # Fly Connectome Data Tutorial
Tutorial materials for working with Drosophila connectome datasets at the [San Juan Winter School on Connectomics and Brain Simulation (SJCABS)](https://sjcabs.com/). We will work with all the major, dense connectome datasets for the fruit fly.
**Instructors:** [Sven Dorkenwald](https:/... |
467a6c2738a5b3b8bcf242cb7c4a5da5e0c62fb3e1c33180e81c184fa328ebb4 | Text | 41,056 | 803 | <div align="center">
<a href="https://en.wiktionary.org/wiki/%E7%9C%BC" target="_blank">
<img src="docs/images/clair3_logo.png" width="110" height="90" alt="Clair3">
</a>
<h1>Clair3</h1>
<p><b>Symphonizing pileup and full-alignment for deep-learning-based long-read variant calling</b></p>
<p>
<a hr... |
9d6f69feba5ed981dd42fc5de876c6dc5f0debe29760cb1ca6705e7c60665278 | Text | 43,022 | 696 | [](https://github.com/broadinstitute/gatk/actions/workflows/gatk-tests.yml)
[](https://maven-badges.herokuapp.com/maven-cent... |
3a893aa219b4e3d53653eaa93a9e7d92ce9fbc302f01115c83de545fde96994c | Text | 45,037 | 803 | <a id="readme-top"></a>
[![Contributors][contributors-shield]][contributors-url]
[![Forks][forks-shield]][forks-url]
[![Stargazers][stars-shield]][stars-url]
[![Issues][issues-shield]][issues-url]
[![LinkedIn][linkedin-shield]][linkedin-url]
<!-- PROJECT LOGO -->
<br />
<div align="center">
<a href="https://github.... |
9a2dca23145ecc84b2f839c4d4610f48e8d7e756f1a0e75e20c0f6e6b53476bf | Text | 45,724 | 562 | # TotalSegmentator
Tool for segmentation of most major anatomical structures in any CT or MR image. It was trained on a wide range of different CT and MR images (different scanners, institutions, protocols,...) and therefore works well on most images. A large part of the training dataset can be downloaded here: [CT da... |
be2b1838401cdcdadae8bb190f589d67b224399873ca3e8d761af5ab921da323 | Text | 46,073 | 482 | <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 ... |
8b273c21a322fc9473d1b68d0dd40c8166ab2f89e4a190aa26ca87251b97cba9 | Text | 46,320 | 795 | # Evolutionary Scale Modeling
[](https://esmatlas.com)
***Update April 2023:*** Code for the two simultaneous preprints on protein design is now released! Code for "Language models generalize beyond natural p... |
9ce050428aec8aa0e45ed2c0546014e41f0cb67d4dd539b65a6eeabc4682f184 | Text | 56,034 | 465 | # Protein-coding-gene-IDs-human-mouse-rat-pig
Repository Protein-coding-gene-IDs-human-mouse-rat-pig
Detailed information is available in manuscript “Protein-coding genes in humans and model mammals (mouse, rat and pig): gene identifiers ... |
2acfdafff9ba526261751e9b7f02fcdcc9c2aacc7be0a528ced9db41136b4978 | Text | 60,641 | 490 | <p align="center">
<img height="150" src="https://raw.githubusercontent.com/pyg-team/pyg_sphinx_theme/master/pyg_sphinx_theme/static/img/pyg_logo_text.svg?sanitize=true" />
</p>
______________________________________________________________________
<div align="center">
[![PyPI Version][pypi-image]][pypi-url]
[](https://badge.fury.io/py/ripple-detection)
[](https://www.python.org/downloads/)
[](https://opensour... |
ac0cc4b971344523f2cfa214c1f8e973fe60c8a238b54c81c7983765e9e4cad8 | Text | 82,939 | 2,597 | [ICLE Data Analysis](https://osamashiraz.github.io/ILC_CellLine_Encyclopedia/)
=======
**2026-02-18**
**Osama Shiraz Shah**
**Table of Content**
- [ICLE\_Data\_Analysis](#icle_data_analysis)
- [Publication and Data Availability](#publication-and-data-availability)
- [Analysis overview and downstream workflow](#analy... |
96260519b594ae22cba9f28d1f64622de001f2abf11d406c9da572bfaf145727 | Text | 92,687 | 1,516 | # ***ATTENTION***
Before opening a new issue here, please check the appropriate help channel on the bioBakery Support Forum (https://forum.biobakery.org) and consider opening or commenting on a thread there.
----
# HUMAnN User Manual
HUMAnN is the next generation of HUMAnN (HMP Unified Metabolic Analysis N... |
f6a7372166da957317c30b72be0de5c65a1f2ec433f26eaca3a6680c72457046 | TypeScript | 22 | 1 | import './main-common' |
1c3a62c6ecf2b772c4fd2d5e79a2fae8ce8ef4a9c48f941e271f1c5eab1ef122 | TypeScript | 24 | 1 | export * from "./tabs";
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c266f63738c14b6308afa18fd5ad25dd21578188f14f0b777f4d1b6612a1f5a7 | TypeScript | 30 | 1 | export * as LSF from "./LSF";
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7c5d73c7ccefe7be4c1297428e2a27c3a7b05278879633bc5ea1476eef7edde3 | TypeScript | 31 | 1 | export * from "./tree-select";
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a8ee861406aafec1b55c4ad6abbe59be2dcfb90f2164b0ee5910e2a8f3330a68 | TypeScript | 31 | 1 | export * from "./EditorPanel";
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b7b4b76dbe61f43b18b3f41e47f4880ab1f3bbb448c73be1b49d70d94d438dac | TypeScript | 32 | 1 | export * from "./PreviewPanel";
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1835e04312248d0af33acada0bd3d2ada2b2b5e9663862ea35ffa21bc4be556f | TypeScript | 33 | 1 | export * from "./ai-chat-shell";
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4deb9b99ffd984484a40b58a09379c3952b1877522fc79aa966d27a44972bc0c | TypeScript | 35 | 1 | export * from "../../utils/utils";
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887186f7a47b61b4a77668acb06dafa82f010de39b529e5f55dcc52de35e2135 | TypeScript | 35 | 1 | import '@testing-library/jest-dom'; |
8bc4a42f32769be0684c6d94bb734c1c49a9d551a8e9ea39cd43f242814c4720 | TypeScript | 35 | 1 | module.exports = "test-file-stub";
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8b65f66b3e5fbd9657d3489b94f7082e1c5ec475fe30c4c1b037af397c8abb09 | TypeScript | 37 | 1 | export { Network } from "./Network";
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d49cdcdc383b66973e58bfdb50e540fad8cd816fbb8dca05c66e5c7024aac90b | TypeScript | 37 | 1 | export const STATE_DEBOUNCE_MS = 160
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65996936fbb042915f7b74a200fcdde7e410f32a669b1ab9597cfaa4b0faddb5 | TypeScript | 38 | 1 | /// <reference types="vite/client" />
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966434502f243f493ee67fbea602bdb158f7a712810f4c91f67849aa06346908 | TypeScript | 38 | 1 | export const Version = '3.16.2.dev0';
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d70f5b81a07864c2746246252f9e08aabe317afad5928f7d8c3bb41ee0b1421b | TypeScript | 38 | 1 | export * from "./ai-chat-prompt-bar";
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a6dc5e57e74af04ccb159e9ee89c2d8a59eecc966f543130c82d67fab20b531b | TypeScript | 39 | 1 | export { Sparkles } from "./sparkles";
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4c16276d19c9070125aa375555ae87c840136354c9134a8498e7f17c5b80f1ce | TypeScript | 40 | 1 | export const nameSpace = `[threeSurfer]` |
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