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4b548a13b50354c9d72b2bba2edf97f7d6afbe18dae4462ce521279da5bde354 | Text | 8,500 | 90 | # SC-shapes-the-maturation-of-cortical-morphology
This repository provides core code and relevant toolboxes for data analysis in the article "Liang X, Sun L, Liao X, Lei T, Xia M, Duan D, Zeng Z, Xu Z, Men W, Wang Y, Tan S, Gao J, Qin S, Tao S, Dong Q, Zhao T, He Y, Structural connectome architecture shapes the mat... |
cfb46098e47627b5bb83bf8d41e1411a6f1f47c281f85b3fdca597f19361eb56 | Text | 8,558 | 77 | ## Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions
This repository contains code and data accompanying:
Greta Tuckute*, Jenelle Feather*, Dana Boebinger, Josh H. McDermott (2023): _Many but not all deep neural network audio mo... |
b285c0e5f27b15364dc546e8cc0f0dbaa887c693eca5ddbb02768a3a29ca020a | Text | 8,590 | 193 | <div align="center">
<h1 align="center">GradientAccumulator</h1>
<h3 align="center">Seemless gradient accumulation for TensorFlow 2</h3>
[](https://pypi.org/project/gradient-accumulator/)
[![PyPI version](https://bad... |
24743d8f3f84e33212aa7c160cc83a2c96ad39f0c25358f672f1c44f839f8b99 | Text | 8,602 | 164 | This repository includes scripts and source data that were used in the following peer-reviewed publication:
__Martianova, E.__, Sadretdinova, R., Pageau, A., Pausik, N., Doucet, T., Leblanc, D., Marroquin Rivera, A., Labonté, B., Proulx, C.D _Hypothalamic neuronal outputs transmit sensorimotor signals at the onset of ... |
6be9b340a1d37fbf679dcc1db5fbfb9c988dbd1827f8db88c80ee23ea1b5a8f4 | Text | 8,606 | 246 | > [!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/eFEL
<img src="https://raw.githubusercontent.com/BlueBrain/eFEL/master/docs/source/logo/eFELBanner.png" alt... |
238b3fbba02ce3d3bdcd4beae04bfa0d136c59828997f599f9cc80fd4bb58de8 | Text | 8,623 | 139 | # Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations
## Installation
Install the conda environment from the bioconfpred.yml file:
`conda env create -f bioconfpred.yml`
The conformer generation step, RMSD calculation and GOLD docking requires the tools from CCDC through... |
4afad357056e3653d7f681311ee6dad9e857a399c99b155eb11758eee77977fd | Text | 8,631 | 139 | # Atherosclerosis Subclinical Endotype Prediction (ASep)
## Background
This is the software for subclinical carotid atherosclerosis endotype prediction.
## Before using
We much appreciate it if you could cite the paper when using the tool.
Please note that the Endotype Prediction Tool is exclusively intended for a... |
ee371b8404128ff3218c6702fce7982efda4d4fac9461ddd7ddff590b6bed159 | Text | 8,648 | 261 | Reaction–diffusion simulations in simplified to complex astroglial branchlet geometries
Supplementary code and data accompanying the manuscript:
"Modeling reaction–diffusion processes in simplified to complex astroglial branchlet geometries using different simulation tools"
Authors: Laura Keto*, Saana Seppälä*, Derek... |
232c31884b19be2d55c6505d3a5d92255b794bd9966dfdf5c85730d0b80bd53b | Text | 8,670 | 147 | # Fiji-Macros
##### Macros for image analysis, scalebars (ICH microscopes), automating standard tasks. All are covered under an MIT License, so can be freely used and distributed.
---
## **Published Macros**
### **Cilia Lengths & spots:**
[Cilia_Lengths_2D.ijm](/Cilia_Lengths_2D.ijm) & [Cilia_Spots_2D.ijm](/Cilia_S... |
62cb14fe9b0b79b73eecf9ee2c6dceaf01ea47af17f3a079de2fd03203928705 | Text | 8,671 | 127 | # CoDeS3D: Contextualising Developmental SNPs in Three Dimensions
## Installation
Clone the repository using the following command:
```
https://github.com/Genome3d/codes3d.git
cd codes3d/
```
## Setup
(The following guide has been tested on Ubuntu 14.04+.)
Install required apt packages:
```
sudo apt update
sudo ap... |
1fd880b25e7b5e6699f25df8d0a9d3322d4df1dae7a6d7531da7fe4c25d1d406 | Text | 8,712 | 130 | # MisER-project
An annotation based method to find and fix small exons missed alignment defects in Nanopore long reads.
<img src="examples/pictures/ex1.png" width=800>
The example plot above show the misaligned exon in the middle is find by compaired the reference annotation BED and realigned to the correct position. ... |
ae9bea9fc94889aa83517b07c744a2c79fbf7cc36ccc3ee33031d53c9684b65e | Text | 8,814 | 187 | # README
* Release Version 3.0
# What is this code for?
This package is for the MODA (Massive Online Data Annotation) Groups Consensus (GC) set of spindles.
For more details, and to leave comments or questions for the project, see MODA on Open Science Framework at https://osf.io/8bma7/
The PSG files used in this p... |
1c626873a06da768a156ebd03955db7a876f8c72f361567a87ed7d5d9af8e24a | Text | 8,858 | 210 | <a href="https://zenodo.org/badge/latestdoi/15686/josephryan/alien_index"><img src="https://zenodo.org/badge/15686/josephryan/alien_index.svg" alt="10.5281/zenodo.21029"></a>
Citation: Ryan, JF, 2014. Alien Index: identify potential non-animal transcripts or horizontally transferred genes in animal transcriptomes. DOI... |
f35698c66d2f421bc1d5efd92f402ffcb7916f220d9a3f8474129f56477b8344 | Text | 8,862 | 93 | [](https://reporter.nih.gov/project-details/10525501)
[](https://osf.io/a6t8k)
[](https://osf.i... |
b6102eb1005a577fed1adaae81c35b02db1e91c1c95b6f9299446dfc827e5006 | Text | 8,870 | 242 | # Overview
Cellxgene Gateway allows you to use the Cellxgene Server provided by the Chan Zuckerberg Institute (https://github.com/chanzuckerberg/cellxgene) with multiple datasets. It displays an index of available h5ad (anndata) files. When a user clicks on a file name, it launches a Cellxgene Server instance that loa... |
6112ec4840435f0ede1529fd2aea100f07239428681991c36660b09bde032467 | Text | 8,914 | 163 | # SRDTrans: Spatial redundancy transformer for self-supervised fluorescence image denoising
<p align="center">
<img src="assets/SRDTrans.gif" width='600'>
</p>
<div align="center">
✨ [**Method**](#-Method) **|** 🚩 [**Paper**](#-Paper) **|** 🔧 [**Install**](#-Install) **|** 🎨 [**Datasets**](#-Datasets) **|** ... |
61ef2e65e652ad13e66f05602b07c01b293a04d6dd0d96c171e6ba5fe65eabae | Text | 8,915 | 93 | [](https://reporter.nih.gov/project-details/10525501)
[](https://osf.io/a6t8k)
[![Stage 2 RegReport DOI](https://img.shields.io/badge/DOI_Stage_2-Registe... |
4dbb3450a866bfc2fa7da7002391bf55ce99b7ecded5b0e0a4c0e0e67f523286 | Text | 8,920 | 122 | <img src="https://raw.githubusercontent.com/JEFworks-Lab/STalign/main/STalign_logos_fin.png">
`STalign` aligns spatial transcriptomics (ST) tissue sections to each other and to 3D atlases like the Allen Brain Atlas using algorithms that build upon diffeomorphic metric mapping.
More information regarding the overall ... |
2a4c9038df924b44c7bb719a33bab1dcd6b50828c526ceeedf46755ead6808db | Text | 8,926 | 90 | # [The neuropeptidergic connectome of Caenorhabditis elegans](https://www.cell.com/action/showPdf?pii=S0896-6273%2823%2900756-0)
Lidia Ripoll-Sánchez, Jan Watteyne, HaoSheng Sun, Robert Fernandez, Seth R Taylor, Alexis Weinreb, Mark Hammarlund, David M Miller III, Oliver Hobert, Isabel Beets, Petra E Vértes, Willi... |
c869644a1db1ef4c618c67691a81ed8753129b3eb7f797a2fdc7210eed2d1e9b | Text | 8,939 | 164 | <h1 align="center">🔬<ins>ToMoDL</ins>🔬<br>Model-Based Deep Learning Architecture for Optical Tomography Projection 3D Reconstruction</h1>
<p align="center">
<a href="https://www.linkedin.com/in/marcos-obando-22a816170">Marcos Obando</a>
·
<a href="https://www.creatis.insa-lyon.fr/~ducros/WebPage/">Nicolas Ducro... |
1625a9dac6053d32225d4c8036aa8ae7420e60a4956c9e3e0505dd75cb13abe9 | Text | 8,972 | 163 | # SRDTrans: Spatial redundancy transformer for self-supervised fluorescence image denoising
<p align="center">
<img src="assets/SRDTrans.gif" width='600'>
</p>
<div align="center">
✨ [**Method**](#-Method) **|** 🚩 [**Paper**](#-Paper) **|** 🔧 [**Install**](#-Install) **|** 🎨 [**Datasets**](#-Datasets) **|** ... |
c3fa2dce3fc305ca4b64d4a6381f7c877f341bef2065ef8c4e310d428bf649df | Text | 9,015 | 144 | [](https://github.com/psf/black) [](https://circleci.com/gh/ENCODE-DCC/caper)
## Introduction
Caper (Cromwell Assisted Pipeline ExecutoR) is a wrapper Python package for ... |
edd81dece269de82b061b2728434bdf6e55e33a0541760c15460270201dc7176 | Text | 9,041 | 157 | # Pyrosm
[](https://anaconda.org/conda-forge/pyrosm/)
[](https://badge.fury.io/py/pyrosm)
[](https://travis-ci.org... |
6bb8110e4ec6d8c0403eba48471701dbebb7bbbf35910d1a744ac86d93fc0616 | Text | 9,128 | 225 | [](http://godoc.org/github.com/thegreenwebfoundation/grid-intensity-go)  ](https://github.com/john-veillette/mne_ari/actions/workflows/pytest.yml) [](https://codecov.io/gh/john-veillette/mne_ari) ... |
59d36bd5874da119d27bceadca6ed2db5e0fcb2b04defd91f473c538138cd5a3 | Text | 9,129 | 161 | <img src="https://raw.githubusercontent.com/scverse/muon/main/docs/_static/img/muon_header.png" data-canonical-src="https://raw.githubusercontent.com/scverse/muon/main/docs/_static/img/muon_header.png" width="700"/>
`muon` is a multimodal omics Python framework.
[Documentation][] | [Tutorials](https://muon-tutorials.... |
b27b4601538740b52fe8c46addba9bb6c9875b5290360b484b8e2d4b1d18eab7 | Text | 9,160 | 121 | # Brain-behaviour relationship in scene categorization
This code was used for the project "Empirically identifying and computationally modelling the brain-behavior relationship for human scene categorization" by Karapetian et al. (2023). The code was written in Matlab 2021a, Python 3.6 and Tensorflow 2.7.
To clone ... |
b8c9760f1dd27932606a20338b65028982de9d8ddbb07328648cc00e859c3cd2 | Text | 9,322 | 119 | # Tigramite – Causal inference for time series datasets
Version 5.2
(Python Package)
[Github](https://github.com/jakobrunge/tigramite.git)
[Documentation](https://jakobrunge.github.io/tigramite/)
[Tutorials](https://github.com/jakobrunge/tigramite/tree/master/tutorials... |
dbc10e837ecf4f210ae3b2f434bb1a52be914b19e73d676f23a34bb06bd6d3c6 | Text | 9,327 | 216 | 
<a href=https://www.frontiersin.org... |
d07834b7d0392bb79f9e3d7972fb1009ae7d71cb6654ec61d19b54a086bc05ab | Text | 9,393 | 137 | # Volitional activation of remote place representations with a hippocampal brain‐machine interface
## Overview
This repository is associated with the following paper:
**Lai C, Tanaka S, Harris TD, Lee AK. Volitional activation of remote place representations with a hippocampal brain‐machine interface. Science, 2... |
e182d088453fce383ec958fbb134793abccb5652bb4b38554b509b8eed839a26 | Text | 9,472 | 151 | # Dynamic and selective engrams emerge with memory consolidation
This repository contains the code used to perform the simulations and data analyses reported in our manuscript:
```
Tomé, D.F., Zhang, Y., Aida, T., Mosto, O., Lu, Y., Chen, M., Sadeh, S., Roy, D. S., Clopath, C.
Dynamic and selective engrams emerge wit... |
f12dea326562c83d26c71c40db437364da174de8afe726dd5c3aaa0d1ce4b88c | Text | 9,493 | 151 | # Dynamic and selective engrams emerge with memory consolidation
This repository contains the code used to perform the simulations and data analyses reported in our manuscript:
```
Tomé, D.F., Zhang, Y., Aida, T., Mosto, O., Lu, Y., Chen, M., Sadeh, S., Roy, D. S., Clopath, C.
Dynamic and selective engrams emerge wit... |
72436c57eec78cd191d58cbb333082adc2c186f6d17de1be546230f774449930 | Text | 9,527 | 132 | [](#contributors-)
[](https://zenodo.org/badge/latestdoi/224148416) [](https://badge.fury.io/py/vb-toolbox)
# VBIndex
V... |
f8eb720e499c919a297d16af6c9661e387292590f67a4b6ff49122fd73d58288 | Text | 9,547 | 122 | # scHiCluster
## Introduction
scHiCluster is a comprehensive python package for single-cell chromosome contact data analysis. It includes the identification of cell types (clusters), loop calling in cell types, and domain and compartment calling in single cells.
<img src="example/plot/Introduction.png" width="700" hei... |
90102e9762e4d39fb63137ce7b702e05b0a76f0cda86c433d30dcebed2de1466 | Text | 9,587 | 140 | # PromptSource
**PromptSource is a toolkit for creating, sharing and using natural language prompts.**
Recent work has shown that large language models exhibit the ability to perform reasonable zero-shot generalization to new tasks. For instance, [GPT-3](https://arxiv.org/abs/2005.14165) demonstrated that large langua... |
60ee122938d3861ab53b97e59b216fbc3da50a34b23cd8fce7937200eed47fcf | Text | 9,590 | 91 | <img src="vignettes/maftools_hex.svg" align="left" height="140" /></a>
## maftools - An R package to summarize, analyze and visualize MAF files
[](https://github.com/poisonalien/maftools/issues)
[](https://github.com/john-veillette/mne_ari/actions/workflows/pytest.yml) [](https://codecov.io/gh/john-veillette/mne_ari) ... |
294c2e169e8a3bcf5c9ae3ff07bc8800bfabc7e1c596ab66a8a6afbd708ef24e | Text | 9,687 | 166 | # RepECN
This repository is an official PyTorch implementation of the paper **"RepECN: Making ConvNets Better again for Efficient Image Super-Resolution"** from **Sensors** ([paper](https://www.mdpi.com/1424-8220/23/23/9575), [pretrained models](https://github.com/qpchen/RepECN/releases), [visual results](https://gith... |
4fab72d6043b66f31d85f522d32318dc76bbd20467050686aa8515a2425d7e04 | Text | 9,719 | 129 | # 4D-OR: Semantic Scene Graphs for OR Domain Modeling
Official code of the paper 4D-OR: Semantic Scene Graphs for OR Domain Modeling (https://link.springer.com/chapter/10.1007/978-3-031-16449-1_45) published at MICCAI 2022.
PDF Paper: https://link.springer.com/content/pdf/10.1007/978-3-031-16449-1_45.pdf?pdf=inline%2... |
b24914c553aa18ff927874d56c496fcdda917e7b0166b1bb42ead73f39a9fe28 | Text | 9,724 | 161 | # GEVA
Genealogical Estimation of Variant Age (GEVA)
This document describes the usage of the computational framework that we developed to estimate the age of the allele observed at a single locus in large-scale haplotype sample data.
> **Dating genomic variants and shared ancestry in population-scale sequencing da... |
59294712c0eb4b41743f667b1164a37aa52c34d285a42529bb40c2bab29add4a | Text | 9,725 | 166 | A universal workflow for creation, validation, and generalization of detailed neuronal models: demo
===================================================================================================
+----------------+------------+
| License | |license| |
+----------------+------------+
| Build Status | |bui... |
af7a9279efbe046c92901e3a7ae7ab014699a4495b0be75213e05b6fd93b69a8 | Text | 9,793 | 341 | - [About](#org22ec0ea)
- [Example Usage](#org957541e)
- [Example Set CSV Input File](#org57e4646)
- [Example Trials CSV Ouput File](#org83b94a0)
- [Installation](#orgfa92b9c)
- [Development](#orgf6d2be8)
<!-- This file is generated automatically from metadata -->
<!-- File edits may be overwritten! -->
<a id... |
2fd0e6c17f293746a6cf5f2bcd09f492477be09946ba533ea57bb2b52f24a5dc | Text | 9,811 | 225 | # Introduction
This script implements several Convolutional Neural Network (several versions of U-net, DeepLavb3+) to perform the semantic segmentation of 2D images. The framework used is Keras by Tensorflow.
The type of data that we are going to manipulate consists in:
- a jpeg image with 3 channels (RGB)
- ... |
5c36b019feca9c7d3e51e5fdd88eea5b48d30c9a4923a23c4147536630abad67 | Text | 9,830 | 270 | # Reliable interpretability of biology-inspired deep neural networks
## Folders
(Not all of these folders are included in the git repository.)
- `data`: output files generated by P-NET and DTox (available from https://doi.org/10.5281/zenodo.7760561)
- `doc`: project documentation
- `docker`: files for creating [Dock... |
2fab3fc01cf08a442b773d758f5cdf5ab52004de721b815b4e319fbf400a3415 | Text | 9,836 | 108 | # MDeePred: Multi-Channel Deep Chemogenomic Modeling of Receptor-Ligand Binding Affinity Prediction for Drug Discovery
**Motivation:**
Identification of interactions between bioactive small molecules and target proteins is crucial for novel drug discovery, drug repurposing and uncovering off-target effects. Due to the... |
aad1b19c637e68bf47c51b7f2d0e3ba5bccdd8f594ed116b5b3f904ac24276cf | Text | 9,859 | 186 | # GNTD
Graph-guided Neural Tensor Decomposition (GNTD) is program for reconstructing whole spatial transcriptomes from spatial gene expression profiling data such as the dataets generated by Visium ST and Stereo-seq. GNTD employs tensor structures and formulations to explicitly model the high-order spatial gene express... |
2e7e80054426775039631c451289ccdc9ef94459bee76de971baf8bd96ec67cb | Text | 9,905 | 186 | # GNTD
Graph-guided Neural Tensor Decomposition (GNTD) is program for reconstructing whole spatial transcriptomes from spatial gene expression profiling data such as the dataets generated by Visium ST and Stereo-seq. GNTD employs tensor structures and formulations to explicitly model the high-order spatial gene express... |
2f185360f4fcf59dd8485965614781d802a6b2c5b591834f8129326e8fad3e33 | Text | 9,968 | 203 | # MOOSY-32 e-Nose Dataset for Prostate Cancer Assessment
[](https://doi.org/10.1186/s12911-023-02312-2)
[](https://doi.org/10.5281/zenodo.21699350)
[
## What is MaskTheFace?
MaskTheFace is computer vision-based script to mask faces in images. It uses a dlib based face landmarks detector to identify the face tilt and six key features of the face necessary for applying mask. ... |
3ba03e7d5b046681ee4a89e631cf59966574e8feb6e750a8e6211f4c36e91014 | Text | 10,263 | 237 | # PtychoPINN: physics-constrained deep learning for rapid, high-resolution diffractive imaging
PtychoPINN reconstructs the complex object (amplitude and phase) of a
ptychography or scanning coherent diffraction imaging (CDI) scan with a neural
network trained **without ground-truth objects**. The network's output is p... |
d06d3e22c5553ec4685e25f4c41c39ead18c98d01778a9b0f6b855f6e090c0c9 | Text | 10,263 | 183 | # MuDCoD: Multi-subject Dynamic Community Detection
MuDCoD (Multi-subject Dynamic Community Detection) provides robust community detection in time-varying personalized networks modules.
It allow signal sharing between time-steps and subjects by applying eigenvector smoothing.
When available, MuDCoD leverages common sig... |
aefdb0bc6718ae37af8f8e267d4a941a655d468e1240fe8ab4fcf18ed72b0ab9 | Text | 10,290 | 357 | The Oxford Mouse Polysomnography Benchmark Data Set
===================================================
This archive contains electrophysiological recordings from freely behaving mice, with each 4-second epoch having been annotated with the corresponding vigilance state by multiple sleep experts. The recordings are ei... |
d285632088c180d3b7b53b6cd2b191e1800e0137824312992c08ab7194e2e607 | Text | 10,297 | 213 | # MOOSY-32 e-Nose Dataset for Prostate Cancer Assessment
[](https://doi.org/10.1186/s12911-023-02312-2)
[](https://doi.org/10.5281/zenodo.21699350)
[
# Track & reduce CO₂ emissions from your local computing
Estimate and track carbon emissions from your computer, quantify and analyze their impact.
[](https://pypi.org/project/codecarbon/) [.
This program is distributed under the terms of the GNU General Public
License. See COPYING for details.
## Documentation
Online documentation is available at: https://github.com/mtpearce/idyom/wiki
... |
4aa3e9c084cc4752c1ddb6b336c0b1418c516194f31caa0d08b8ab9592bcea54 | Text | 10,579 | 183 | # Protein 3D Structure Prediction with DeepFold
> We have developed a new pipeline of protein structure prediction called **DeepFold**, that improves the accuracy of side-chain predictions as well as that of backbones by leveraging AlphaFold2.
- First, we optimized the loss functions of side chains by considering the... |
f2c156bd0157773549db60e427af0045880e846dadbb0a3c38c561091cec03aa | Text | 10,674 | 134 | A deep learning based library for segmentation of high grade serous ovarian cancer on CT images.
The library contains the code and the finals models created during my [PhD Thesis](https://doi.org/10.17863/CAM.87940) some of which have been described in our [paper](https://eurradiolexp.springeropen.com/articles/10.1186/... |
7fae10c77d195a9b7902678ec154103643b29fb26d7ed92b0606a1855c85e9ee | Text | 10,704 | 265 | # LLSpy: Lattice light-sheet post-processing utility
[](https://opensource.org/licenses/BSD-3-Clause)
[ caused by single-point amino acid substitutions. The core algorithm of ThermoNet is an ensemble of deep 3D convolutional neural networks. ThermoNet was benchmarked against a l... |
eae274641f03ed08ec1a37678983aad5f9ba7938b9e88b35ad74e746ab28a2ea | Text | 10,760 | 268 | # rcc-xcorr
A Python library to compute normalized 2D cross-correlation of images using GPU acceleration and python multiprocessing.
**Contents**
1. [Requirements](#requirements)
2. [Installation](#installation)
3. [Usage](#usage)
4. [Benchmarks](#benchmarks)
* [Benchmarking CPU vs GPU](#benchmarking-cpu-vs-gpu)
... |
ea5f65a3d92129db1e69cb44bcb6bb39efd52c987a406f93e257071b5f9fa941 | Text | 10,841 | 274 | [](https://biomedisa.info)
-----------
- [About](#about)
- [Hardware Requirements](#hardware-requirements)
- [Installation (command-line based)](#installation-command-line-based)
- [Installation (3D Slicer ... |
c61083af6b5f4784b81305dd6e1168d654aafbc099eb14c23fa2e8832ff361af | Text | 10,924 | 175 | # Principal Interaction Component Analysis through Likelihood Optimization (PICALO)
Expression quantitative trait loci (eQTL) offer insights into the regulatory mechanisms of trait associated variants, but their effects often rely on contexts that are either unknown or unmeasured. We introduce PICALO, a method for hid... |
2df15ad3c674cbf55b1b0aac15b1b6223e2740b2a09a66aa216307979393acd2 | Text | 11,022 | 199 | # HD-GLIO
## Introduction
This repository provides easy to use access to our HD-GLIO brain tumor segmentation tool. HD-GLIO is the result of a
joint project between the Department of Neuroradiology at the Heidelberg University Hospital, Germany and the
Division of Medical Image Computing at the German Cancer Resear... |
36897e72144ac8e8092375f12cda4d8cd3205ea8e699610c83a4e46fb07714f3 | Text | 11,140 | 213 | # About
This project seeks to address data analysis through the
development of a series of comparative analysis tools for connectomic data in an effort to make a
foundational basis of analysis for all researchers in connectomics. These scripts include total dendritic branch number per neuron (dendritic density), and E... |
f70f8b802a210f1da338e5bc1bac76526ee3b320c35f8fa5da3e26ede90edad0 | Text | 11,196 | 236 | # **carbontracker**
[](https://github.com/saintslab/carbontracker/actions)
[](https://pypi.org/project/carbontracker/)
[. Should work with any imputed VCF file that has GT o... |
821398885dfc03d0aa789d12a37f1eff4238e8e286880e9339edf004d83f6a1a | Text | 11,343 | 331 | # Reliable interpretability of biology-inspired deep neural networks
[](https://doi.org/10.5281/zenodo.8386694)
This code supplements the [publication](https://doi.org/10.1038/s41540-023-00310-8) by Esser-Skala and Fortelny (2023).
## Folders
(Not all... |
fa06b9fbf91aef818202aecddc399ab7ac4118d8bece9f5e88b54cf9438f58bd | Text | 11,574 | 205 | # Meta-Learning for Compositionality (MLC) for modeling human behavior
Meta-Learning for Compositionality (MLC) is an optimization procedure that encourages systematicity through a series of few-shot compositional tasks. This code shows how to train and evaluate a sequence-to-sequence (seq2seq) transformer in PyTorch ... |
5095541fd45271718eb616cecad8365d3e1937d4c655c50e9d01b23d813b8e76 | Text | 11,698 | 159 | [](https://github.com/bwa-mem2/bwa-mem2/releases)
[](https://anaconda.org/bioconda/bwa-mem2)
[](https://opensource.org/licenses/BSD-3-Clause)
[](https://github.com/rutish... |
8b3ea5ab4a52cd88b843a88b6f22deddb23e56504998a174602108cfc11e7938 | Text | 11,787 | 139 | # Asteroid Impact
<img src="https://raw.githubusercontent.com/medianeuroscience/asteroid_impact/master/misc/ai_new1.png" width="400"> <img src="https://raw.githubusercontent.com/medianeuroscience/asteroid_impact/master/misc/ai_new2.png" width="400">
Asteroid Impact is an open-source video game stimulus for conducting... |
9751a11be2bbd950f19cc1bce0e369b702c07ce624e54713ce1027309aafe41f | Text | 11,890 | 255 | <img src="https://raw.githubusercontent.com/oncoray/mirp/master/icon/mirp.svg" align="right" width="120"/>
[](https://pypi... |
fd360dc7bb63bea27ff2c39409e191d5dd34b2150dc9c699e819a0fc96e8939a | Text | 11,994 | 249 | ## Please note: Current v1.8.3 not compatible with Tensorflow >= 2.16.0, please downgrade to 2.15.1
`pip install tensorflow-cpu==2.15.1`
Please see issue [here](https://github.com/cytham/nanovar/issues/77)
We are actively working on this, thank you for your understanding.
## NanoVar - Structural variant caller usin... |
b60926ab2141c83a59440d0bef0faa01959054eca4d4fef432309e26c85bd1d2 | Text | 12,018 | 344 | # react-cytoscapejs
The `react-cytoscapejs` package is an MIT-licensed [React](https://reactjs.org) component for network (or graph, as in [graph theory](https://en.wikipedia.org/wiki/Graph_theory)) visualisation. The component renders a [Cytoscape](http://js.cytoscape.org) graph.
Most props of this component are [Cy... |
5ccc2bb268468aa5df4a8d578f0755b049277360318c146f819efc663e3e2d0e | Text | 12,079 | 170 | # cleared_brains
## Purpose
The goals of this repo are:
1. to build on PRA repo, which produced the 2024 Dennis et al manuscript
2. include new tools and documentation as environments/processes evolve
3. share with our collaborators and later the public as we produce manuscripts
## To use
1. Clone this repo
2. Make s... |
4fe095a6ec40637808e271c6dc0cbca51921c42368ab574160049c656ac6e4ba | Text | 12,080 | 193 | # SSU Project
Welcome to the Saccades for Scene Understanding (SSU) project. This is a tech demo that showcases the power and versatility of ... |
e7dadccf673a675129e6042cd3e51bf6b3edf7ee0ec35474c3164dc707c04b5b | Text | 12,136 | 178 | # msemalign
#### tools for alignment of serial section multi Scanning Electron Microscopy (ssmSEM) acquired datasets
For a high-level introduction, please refer to the following manuscripts:
[msemalign: A pipeline for serial section multibeam scanning electron microscopy volume alignment](https://doi.org/10.3389/fni... |
bf44731b0e3c65d9e0b65e066339679b9e0008e176da1c6d910f738940d0ba77 | Text | 12,168 | 269 | <p align="center">
<a href="https://academic.oup.com/bioinformatics/article/28/18/i333/245403/DELLY-structural-variant-discovery-by-integrated">
<img height="150" src="https://raw.githubusercontent.com/dellytools/assets/main/delly-logo/delly-logo-539x600.png">
</a>
<h1 align="center">Delly</h1>
</p>
[](https://anaconda.org/conda-forge/pyrosm)
[](https://badge.fu... |
910ad3e56a68c9b843a20af84823afdb1d1e767b920d9db20f0c641b2db11f14 | Text | 12,334 | 134 | English | [简体中文](README_cn.md)
<p align="center">
<img src="./.github/paddlehelix_logo.png" align="middle" height="90%" width="90%" />
</p>
------
[](https://github.com/PaddlePaddle/PaddleHelix/releases)
![python version](https://img.shield... |
b9fd66952a41182b3b5aaec668b307ff57f9b12d78df6d3cf5b2645525399e4b | Text | 12,367 | 285 | # AGNOSTIC: Adaptable Generalized Neural-Network Open-source Spectroscopy Training dataset of Individual Components
<div>
Published in Imaging Neuroscience: <a href="https://doi.org/10.1162/imag_a_00025">Application of a 1H brain MRS benchmark dataset to deep learning for out-of-voxel artifacts</a>
</div>
---
<ul styl... |
8c4b78edba6cd9b9293b818af87582b35c8a37f596b80f782f37c69d53b09147 | Text | 12,508 | 129 | RETAIN
=========================================
RETAIN is an interpretable predictive model for healthcare applications. Given patient records, it can make predictions while explaining how each medical code (diagnosis codes, medication codes, or procedure codes) at each visit contributes to the prediction. The interp... |
09a250d2778a2b5ab46e69118351f98f63cfe8e3aad7433b93f711972d585fd4 | Text | 12,605 | 178 | # SynaptosomesMacro
*This toolset is aimed at quantifying the proteins' proximity and their recruitment on synaptosomes, on a structure per structure basis.*
## What was the user's request ?
The user has a set of two channels acquisitions, captured on a widefield microscope. The sample is a spread of isolated synapto... |
20264a15241fa7689a73e65eeddeaf04a6c3b7a318b98ddcd7b14b646a684eef | Text | 12,942 | 310 | # Identification of spatial domains in spatial transcriptomics by deep learning
## Update
<img src="https://raw.githubusercontent.com/EsdenRun/DeepST/main/Fig/Update.jpg" alt="Image Description" width="20%" height="20%" />
May 28, 2025
<font color="red">(1) Updated the installation method for DeepST.</font>
<font c... |
f1cd61d0a8e74097943d403a044c274f2dc6a3474e8b7dcb571434f9895c8304 | Text | 13,104 | 117 | # keller-networks
This code is used to conduct analyses in ABCD data relating personalized functional network (PFN) functional topography to cognition, as a replication and extension of Cui et al. 2020.
This pipeline will expect that PFNs have already been generated for each participant using NMF. Details and code to a... |
21b069407ff79f7f39b1aec98431028b6784b84724a35ca4bdfff4dd713c3c9a | Text | 13,189 | 305 | # ***Cellos***: High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology
<p>
<img src="docs/pipeline3d.png" width="1000"/>
</p>
- [Overview](#overview)
- [Data description](#data-description)
- [Installing the pipeline](#installing-the-pipeline)
- [Running the pipeline... |
72989412036f26ca547771fc6f54502380f379564a11ac784ede54aa92e35d20 | Text | 13,423 | 259 | # Convolutional Neural Network (CNN) for head and neck outcome classification
Image based prognosis in head and neck cancer using convolutional neural networks: a case study in reproducibility and optimization.
- [Convolutional Neural Network (CNN) for head and neck outcome classification](#convolutional-neural-netw... |
2f7b04281364cc88a13e23726e949da099c0c2408834d82ed7f2a1307714b4f8 | Text | 13,475 | 143 | # Covid-19 India Data 🇮🇳
[](https://github.com/IBM/covid19-india-data/blob/main/LICENSE)
[](https://ibm.biz/covid-data-india)
[](h... |
d6bca965451c1fae04a23090091b59131cd455c8f1e0ccf4733fbd558a2d88b3 | Text | 13,533 | 387 | The NMODL Framework
===================
WARNING
_______
**NMODL has been fully integrated into the NEURON repository.**
There will be no further development efforts on NMODL as an independent project.
All future development will happen at:
`https://github.com/neuronsimulator/nrn <https://github.com/neuronsimulator/n... |
92fc2c995cbec4b93ce081b411959a90ddc3ce7df6d61d7cf3c8372ca5bfbb4e | Text | 13,540 | 467 | <p align="center">
<img src="https://github.com/pievos101/Ensemble-GNN/blob/main/logo2.png" width="400">
</p>
# Ensemble learning with graph neural networks for disease module discovery and classification
## Installation
The GNN-Subnet package is required
https://github.com/pievos101/GNN-SubNet
To install GNNSubNe... |
05f0bb34dce1d84de6dfd8d307205ea19bacf0b7a4bf1cd365831f9ee2c2b7a4 | Text | 13,646 | 376 | # pyrho
Fast demography-aware inference of fine-scale recombination rates based on
fused-LASSO
## Table of Contents
* [Human Recombination Maps](#human-recombination-maps)
* [Human Population Sizes](#human-population-sizes)
* [Installation](#installation)
* [Usage](#usage)
* [make_table](#make_table)
* [hype... |
775860be20ca85b2f7851bc4016ae9ed710ea4c95472ff13fd4c35fce73c74df | Text | 13,842 | 179 | # DeepCORE: An interpretable multi-view deep neural network model to detect co-operative regulatory elements
Gene transcription is an essential process involved in all aspects of cellular functions with significant impact on biological traits and diseases. This process is tightly regulated by multiple elements that co-... |
87500c3eac13e9636c32255df0f43bf26ee2ff556dcce339dbb973f1d8472607 | Text | 14,093 | 218 |
# *synconn_build* : Synthetic dataset generator for testing control-oriented neural networks for building dynamics
Applying model-based predictive control in buildings requires a control-oriented model capable of learning how various control actions influence building dynamics, such as indoor air temperature and ener... |
5b38a9cf50f8f42f0e8670756b3f2b65abde0df8e8e1e523d11a971573970887 | Text | 14,155 | 115 | # StarDist Napari Plugin
[](https://pypi.org/project/stardist-napari)
[](https://anaconda.org/conda-forge/stardist-napari)
[, Ameya Daigavane (@ameya98), and Krzysztof
Mierzejewski (@mierzejk)
<!-- README.md is generated from README.Rmd. Please edit that file -->
<!-- badges: start -->
[, electromyograph (EMG), or local field
potentials (LFPs).
The approach taken here consists of two parts: linear discriminant
analysis (LDA) and a hidden Markov model (HMM). Linear discriminant
analysis (LDA) per... |
711f3d79d396bb7bc5521c552ba14874e98200d66ceea045e6a9250ec2d1e3e1 | Text | 14,707 | 257 |
[](https://github.com/MannLabs/alphamap/actions/workflows/publish_and_release.yml)
[](https://pypi.org/project/alphamap)
[![GitHub release](https:... |
2994d042c5d7b348d187a66e1f0bf73587362d91f0477c32cd54ffeb2ae3cd59 | Text | 14,833 | 347 | =========================
Spectral Parameterization
=========================
|ProjectStatus| |Version| |BuildStatus| |Coverage| |License| |PythonVersions| |Publication|
.. |ProjectStatus| image:: https://www.repostatus.org/badges/latest/active.svg
:target: https://www.repostatus.org/#active
:alt: project statu... |
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