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d8bb8feb9beac4c44ac26c820d61e6ef187c33a74761d08cb87b2242affe0864 | Text | 4,420 | 65 | # DeepDTI Tutorial
**Diffusion MRI physics-informed DeepDTI pipeline**. The input is a single b = 0 image and six diffusion-weighted image (DWI) volumes sampled along optimized diffusion-encoding directions that minimize the condition n... |
3830cb5d5e27c10e17917349934b616568600ff39fea75b8355be1fcfcd8d985 | Text | 4,421 | 68 | # Welcome to our Spiking network Simulation code "BrainCode"
## Theory of Neural Dynamics Group
### Tatjana Tchumatchenko
Contributors:
- Ahmed, Saif
- Becker, Sophia
- Bertolin, Antoni
- Dutine, Alexander
- Ekelmans, Pierre
- Konrad, Sara
- Kovalevskaya, Elizaveta (Group of Algorithm Engineering)
- Nold, Andreas
... |
731d4f45973b72410c193a786d5901194930eb29d67b2d55f075cd595416f7bd | Text | 4,435 | 67 | # Pytorch implementation of Variational Network for Magnetic Resonance Image (MRI) Reconstruction
This repository contains a pytorch implementation of the variational network for MRI reconstruction that was published in these papers.
- Hammernik et al., [*Learning a variational network for reconstruction of acce... |
855da616d6cb7b606f1aca6e04d7fdd24c7c8c189d856d4362c38aa8780eab33 | Text | 4,458 | 58 | # DDI-recursive-NN
This is a code repository from the paper "Drug drug interaction extraction from the literature using a recursive neural network", https://doi.org/10.1371/journal.pone.0190926.
We upload the Recursive NN model, which is based on the tree-lstm implementation using the Tensorflow Fold https://github.c... |
4b50d98f6d1e2a0c6a065335e6b5f4838057caf4b2b2e6f1c124b6bb38423dc5 | Text | 4,516 | 33 | # Generalized Neural Closure Models with Interpretability
**Source code**: This directory contains the source code for Generalized Neural Closure Models with Interpretability, published in Nature Scientific Reports: [https://www.nature.com/articles/s41598-023-35319-w](https://www.nature.com/articles/s41598-023-35319-w... |
f8e3dbc27889c1a17798b233038e06c4a44f9de30c51e35dd94edaef05937774 | Text | 4,538 | 52 | # EWS systematic analysis and Optimisation
Code to estimate and opptimise the performance of EWS in approaching bifurcations and their sensitivity to the interplay of b-tipping and n-tipping. Associiated to the manuscript: Proverbio et al., "Systematic analysis and optimization of early warning signals for critical tr... |
0c0db4d212f5c2415f650ed54f20b08e2b9bc78a9fef685ca2c79d8c904666b0 | Text | 4,544 | 75 | # Bayesian optimization for design of multiscale biological circuits.
Python code for optimizing genetic control architectures and parameter values simultaneously using Hyperopt. Data and figure files under the Github size limit are included; large data files are listed and available upon request. This code accompanie... |
d92f3655fb2a2ff0e51515031676e05ad9f55602ee275ad188391027aa13abcf | Text | 4,577 | 58 | ************************************************************************************************************************************************
Welcome to our Spiking network Simulation code "BrainCode"
********************************************************************************************************************... |
cc6b76e802790b824e89917875be538597171f6ac1c9315035f4ed11a491e232 | Text | 4,580 | 80 | 
# Spatially Transformed Inferential Force Maps (STIFMaps)
STIFMaps predict the stiffness of breast tissue using the morphology of collagen fibers and nuclei.
, y-maze and c-Fos experiments
This repository contains the analysis scripts for the following manuscript:
"Cerebellar contributions to a brainwide network for flexible behavior",
Jessica L. Verpeut, Silke Bergeler, Mikhail Kislin, F. William Townes, Ugne Klibaite, Zahra M. Dhanerawala, ... |
57ce18321142e8a0040b78014f52514106ce82b4b2fe3db756029b0012c2f3c9 | Text | 4,631 | 97 | # DABEST-Matlab
## About
DABEST is a data analysis tool that is intended to make estimation statistics more accessible to scientific communities. Estimation statistics is a superior alternative to null hypothesis significance testing (NHST), in which effect size and confidence intervals are used to interpret results ... |
47e80c2e814c1755dc8e0cd9ec638794d075c60d518d68974e6d278f943a0ced | Text | 4,684 | 154 | # Investigating Graph Embedding Neural Networks with Unsupervised Features Extraction for Binary Analysis
This repository contains the code to reproduce the experiment of the paper accepted at the Workshop on Binary
Analysis Research (BAR) 2019. https://ruoyuwang.me/bar2019/pdfs/bar2019-paper20.pdf
## Tasks
You can ... |
20ca1e54a63aa7a31b4ba7fbba07c6856cf370328a64e1d2bf5799f2e93b1c0e | Text | 4,713 | 141 | # In Nomine Function
Models and code for the paper:
**In Nomine Function: Naming Functions in Stripped Binaries with Neural Networks** [[PDF]](https://arxiv.org/pdf/1912.07946)
**TL;DR**: We used a transformer model to predict function name in a stripped binary.
If you are using this code please cite:
```shell s... |
38dc25f40ca8c0c6d7999d1da060814fdd5c51b14a59fb6cd69481066d623a52 | Text | 4,785 | 103 | # Model identification of neural encoding (MINE)
Repository for the code used in developing, testing and using MINE.
The paper "Model discovery to link neural activity to behavioral tasks" which publishes this code can be found at:
[Costabile JD, Balakrishnan KA, Schwinn S, Haesemeyer M (2023) eLife 12:e83289](https:... |
8ef4d9188cafb6d443b67db5c3a09afbbd5e09c7f56060afd0eb3949c4386b67 | Text | 4,860 | 94 | # Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition
This repository contains all the code for preprocessing the raw EEG and fMRI data of the bimodal Inner Speech Dataset.
The dataset is publicly available in OpenNeuro: https://openneuro.org/datasets/ds004197
```bi... |
4397b728a2d0b8f680788f966a1c334694f3f36cdbeabf7e03e4915dbf89ec42 | Text | 4,958 | 178 | # pyRDTP
<!-- vim-markdown-toc GitLab -->
* [The 5+1 W](#the-51-w)
* [Installation](#installation)
* [Dependencies](#dependencies)
* [Manual installation](#manual-installation)
* [Automatic installation](#automatic-installation)
* [Jupyter-Lab integration](#jupyter-lab-integration)
* [Usage](#usage)
* [B... |
2e39d0a6eb0ca9adaedeefccf9fd37960764ba9c61a2ac5bdaddf195c8211073 | Text | 4,972 | 102 | # About Dataset
Data published along with paper: *Learning-induced reorganization of number neurons and emergence of numerical representations in a biologically-inspired neural network*
In this data is shared: models (before & after training), stimuli used to train and test, and activity of the model in test.
```
dat... |
266af915fa2a8b41ba40913aac6bcb18448d054350b04960968fc8929000af87 | Text | 4,975 | 170 | # Pytorch Classification
- A general, feasible and extensible framework for 2D image classification.
## Features
- Easy to configure (model, hyperparameters)
- Training progress monitoring and visualization
- Weighted sampling / weighted loss / kappa loss / focal loss for imbalance dataset
- Multiple me... |
31380ad2c0cdcf67877b3808175ad993cb9ef12eab18f9f34a9d49db91d1543c | Text | 4,986 | 126 | # Carbohydrate-Protein Interaction Site Prediction #
Official repository for [CArbohydrate-Protein Site IdentiFier](https://www.frontiersin.org/articles/10.3389/fbinf.2023.1186531/full): from the paper
Structure-Based Neural Network Protein-Carbohydrate Interaction Predictions at... |
bbf6360860b8c31859895de5e0faa4636eb2a30f424d772fa9f50fc38776e795 | Text | 5,006 | 31 | # `smart-ml`
This repository contains the latest machine learning efforts for automated interpretation of rapid test kits (e.g. LFA).
Within each directory inside this repository, you will find a `README.md` which lists preliminary information about the directory and its contents. These documentations will often refe... |
400689623f28b910bf3d8b6cdb0138ad080e0bdecc11a8d277546371bfcb8104 | Text | 5,010 | 104 | # QuickNat and Bayesian QuickNAT - Pytorch implementation
A fully convolutional network for quick and accurate segmentation of neuroanatomy and Quality control of structure-wise segmentations
-----------------------------------------------------------
The code for training, as well as the Trained Models are provided ... |
9227a2eaf8ac52b3725ffb84b162eb2305c0caecfc89e3460ae50c17cbc286d3 | Text | 5,022 | 100 |
<!-- disableFinding(IMAGE_ALT_TEXT_INACCESSIBLE) -->
<!-- disableFinding(HEADING_REPEAT_H1) -->
<!-- disableFinding(SNIPPET_INVALID_LANGUAGE) -->
<!-- disableFinding("github") -->
<!-- disableFinding(LINK_CL_HEAD) -->
# OpenSpiel: A Framework for Reinforcement Learning in Games
[![Documentation Status](https://readt... |
c3d242836c68be035fc55c9a96c3a24db6711d292e6864455f02c396d7b2cf7e | Text | 5,022 | 91 | <img src="https://github.com/conchoecia/odp/blob/main/figs/dotplot_fig_v2-01.jpg" width="250">
# odp - Oxford Dot Plots
This software creates dotplots of protein synteny in genome assemblies. This software was visually modelled on the dotplots found in [Simakov, Oleg, et al. "Deeply conserved synteny resolves early e... |
93865718c6debebf42977d752d299720f37c9ba04103188818423b12b0001962 | Text | 5,031 | 70 | # TF binding matrix
[](https://doi.org/10.5281/zenodo.5283416)
> A sparse 3D matrix of ~~1,817,918~~ 2,503,732 bound and open regions across ~~163~~ 175 transcription factors and ~~52~~ 70 cell and tissue types
Audio Toolbox Version 3... |
a1e05df90653864d1e44870d19c92baddd73a2294e182c862071159bf0009e99 | Text | 5,334 | 134 | <p align="center">
<img width="400" src="https://raw.githubusercontent.com/rkansal47/JetNet/main/docs/_static/images/jetnetlogo.png" />
</p>
<p align="center">
<b>For developing and reproducing ML + HEP projects.</b>
</p>
______________________________________________________________________
<p align="center">
<... |
2a840ce2eba05934b61969ab4e530ea5e50fd42c4968309c2df10b10756aa687 | Text | 5,345 | 100 | # pciSeq: Probabilistic Cell typing by In situ Sequencing
[](https://github.com/acycliq/pciSeq/actions)
[](https://github.com/acycliq/pciSeq/)
[).
Each DFT simulation is stored as an `ase.atoms.Atoms` object, containing the main informat... |
2c5dfdb38e064e1cd57781600c56d10606a7a877c2b74dd1ce8b73b327751232 | Text | 5,384 | 94 | # Denoise Pretraining for ML Potentials
<strong>Denoise Pretraining on Nonequilibrium Molecules for Accurate and Transferable Neural Potentials</strong> </br>
<em>Journal of Chemical Theory and Computation</em> [[Paper]](https://pubs.acs.org/doi/10.1021/acs.jctc.3c00289) [[arXiv]](https://arxiv.org/abs/2303.02216) [[P... |
b057fc507ee20e6d440efddd228221b57d4f0db0c7e7c6aacd88cb4e657f019e | Text | 5,402 | 218 | ..
This file is generated by setup.py
Read and write ImageJ ROI format
================================
Roifile is a Python library to read, write, create, and plot `ImageJ`_ ROIs,
an undocumented and ImageJ application specific format to store regions of
interest, geometric shapes, paths, text, and whatnot for ima... |
4d6c49eff4eefd6da707e10f7b19cf2c8e452b6d27002f7993791dace0823206 | Text | 5,481 | 118 | # IMFSegNet for intramuscular fat segmentation
[](https://opensource.org/licenses/BSD-2-Clause) [](https://jipipe.hki-jena.de/)
A comparative assessment of various imag... |
ba2cab11d87ffc88fe7a911d242530f3fc9ae5ec292d2b485748e23eea4140d0 | Text | 5,535 | 114 | # XTC synapse tracking
## Overview:
Main script for running all modules of the synapse tracking pipeline.
The modular layout below means that individual components of the pipeline can
be easily replaced/improved. Currently, this includes the following sequentially:
1. Timeseries registration with ITK-Elastix package... |
e91cf0e04ca6fc3edffc9fad91ab3096c8b33dc52258138892eee2551414cabe | Text | 5,579 | 64 | # A large-scale fMRI dataset for human action recognition
Human Action Dataset (HAD), a large-scale functional magnetic resonance imaging (fMRI) dataset for human action recognition. HAD contains fMRI responses to 21,600 video clips from 30 participants. The video clips encompass 180 human action categories and offer a... |
89fd9aa50681c61038965fe4bc95c16897457e0780179fab474567af7dac6d89 | Text | 5,645 | 67 | # CAJAL <a href='https://github.com/CamaraLab/CAJAL'><img src="docs/images/logo.png" align="right" width="24%"/></a>
[](https://github.com/CamaraLab/CAJAL/actions/workflows/python-package.yml)
[, Martin Becker (1,2), Cátia Marques (3), Marika Oksanen (1,2), Danyang Li (1,2), Francesca Mastropasqua (1,2), Michelle Evelyn Watts (1,2), Manish Ar... |
8332621198a1f7296b2bafabd6ff9105a5b3cc847bae2f9f6160b368cbee8d7c | Text | 5,726 | 71 | This dataset contains data from overground walking trials of 166 subjects with several trials per subject (approximately 2900 trials total).
- - - - - DATA ORIGINS & LICENSE INFORMATION - - - - -
The data comes from four existing open datasets collected by others:
Schreiber & Moissenet, A multimodal dataset of... |
a04363ac35f61ca368032fdb682a3ca8057421ca50920680959acad60082bf3c | Text | 5,763 | 110 | <p align="center">
<a href="https://github.com/asreview/asreview">
<img width="60%" height="60%" src="https://raw.githubusercontent.com/asreview/asreview/master/images/RepoCardGithub-1280x640px.png">
</a>
</p>
## ASReview: Active learning for Systematic Reviews
[ based on bilateral homotopic connectivity
This compendium of code accompanies the following publication:
Fraize, J., Convert, G., Leprince, Y., Sylvestre-Marconville, F., Kerdreux, E., Auzias, G., Lefèvre, J., ... |
554a6dc6bf6ed1593c433602c98cc7117251632f4fb712e45a438b7ab56fe4d7 | Text | 5,802 | 79 |
# Impact of Multi-source Data Augmentation on Performance of Convolutional Neural Networks for Abnormality Classification in Mammography
CBIS-DDSM dataset is widespread in the deep learning community especially for those who develop deep learning models classifying and detecting breast cancer tumors. What happens whe... |
6511cb6050d4528aad9c7cf9ef0b59a8d64433f7d6a4181782eb2bd2f380ce38 | Text | 5,869 | 89 | <p align="center">
<img src="doc/iguana.png">
</p>
[](https://www.gnu.org/licenses/gpl-3.0)
<a href="#cite-this-repository"><img src="https://img.shields.io/badge/Cite%20this%20repository-BibTeX-brightgreen" alt="DOI"></a> <a href="https://do... |
1959d511d3865d224d5b21a75b513463957e679015642c8becf09c458b130476 | Text | 5,961 | 100 | # Description
This repository contains code used to processes a dataset of tsetse fly wing images and 11 landmarks on each image using deep learning models. We provide the training scripts as well as the complete pipeline used to process the images. We also include the resulting data from this process.
The resulting... |
74a910a12814768c0985de4209bdb350419a22b5083da2b3fb5a076192164ac4 | Text | 6,016 | 115 | # Brain Data Standards Ontologies 
A repository for building ontologies for the Brain Data Standards Project.
Status: Draft
### Cite:
[BioRxiv Preprint](https://www.biorxiv.org/content/10.1101/2021.10.10.463703)
... |
e61a3519a427254a07b84f41ddb5567176679a23e9950194194a5b7d6d597e38 | Text | 6,151 | 98 | # Rare-disease-identification
This repository presents an approach using **ontologies** and **weak supervision** to identify rare diseases from clinical notes. The idea is illustrated below and the [data annotation](https://github.com/acadTags/Rare-disease-identification/tree/main/data%20annotation) for rare disease e... |
98bb05a71c0821088fb4d4b0066fbe9d2d2d38e1b1cae3d40dce49b1ab95158b | Text | 6,229 | 61 | # Networks for Affine Medical Image Registration
This repository contains the implementation of 20 neural networks for affine registration of medical images, which were originally published in research papers. Since three-dimensional data was used, all networks were adapted accordingly. In order to provide a benchmark... |
cb0020a9ebcb94819e71b3647f4e8c5a7fb24552df6ac9fa6911a043ee87bcdd | Text | 6,302 | 150 | .. image:: https://zenodo.org/badge/14990424.svg
:target: https://zenodo.org/badge/latestdoi/14990424
ANLffr
==========
From the `Systems Neuroscience of Auditory Perception lab at Purdue University <https://engineering.purdue.edu/SNAPLab>`_,
a set of tools to analyze and interpret auditory steady-state responses... |
d4731823e59072dabb76352a2c97e23e866d6b563b3bf093f59fae26dba5ed70 | Text | 6,343 | 73 | [](https://github.com/rgcgithub/regenie/actions/workflows/test.yml)
[![install with conda](https://img.shields.io/badge/install%20w... |
df70c5ea3b136d145655ebfc50e8256d2e139226419a60f27e37401e3fae42c3 | Text | 6,436 | 116 | # CTULIP - Canine TUmor CLassIfication Predictor <img src = "images/tulip.svg" alt = "tulip" width = "50" height = "50">
CTULIP (the Canine TUmor cLassIfication Predictor) classifies Canine RNA-Seq samples into tumor types.
## Description
CTULIP is a modified framework of [TULIP](https://github.com/CBIIT/TULIP) whic... |
a8957da740c073d959dadb2c41ad640abaf411b7e13c681f2e5fb3ae3f2499a6 | Text | 6,461 | 176 | # 
[](https://doi.org/10.5281/zenodo.2595043)
[](http://ampligraph.readthedocs.io/?badge=latest)
[Join th... |
a2c1ada99786d20c78e1dc57d7c30b45020ea0d12bccc3d5af9cebc9cb6ce90f | Text | 6,496 | 102 | # BoostMEC: Boosting and Markov for Efficient CRISPR
A pipeline for predicting CRISPR-Cas9 cleavage efficiency using feature engineering and [LightGBM](https://lightgbm.readthedocs.io/).
## Requirements
The software requirements for BoostMEC are listed below. To simplify the management of software packages, we a... |
a5c1ae7c2561d0abdd44bb11adcda4ccad9b2d0638ae43547d0dd2c67689777e | Text | 6,571 | 101 | # pyontutils
[](https://pypi.org/project/pyontutils/)
[](https://travis-ci.org/tgbugs/pyontutils)
[ is a tool to fascilitate the analysis of 2D histological Mouse brain images. It is written purely in python and has a modular design and consists of the following modules:
- Cell detection Module
- Localization Module
- Atlas generator module
- Re... |
a3bf5b5888647c7bfbd37a0d0d55966d5b0176980c75600aa996f1da47420d88 | Text | 6,704 | 188 | Python Word Segmentation
========================
`WordSegment`_ is an Apache2 licensed module for English word
segmentation, written in pure-Python, and based on a trillion-word corpus.
Based on code from the chapter "`Natural Language Corpus Data`_" by Peter
Norvig from the book "`Beautiful Data`_" (Segaran and Ham... |
1305eb9d59e918f2fb1781435a11ffb40cac951f572150072d2e6f6d014d7763 | Text | 6,731 | 225 | #################
svgbit quickstart
#################
.. image:: https://badge.fury.io/py/svgbit.svg
:target: https://badge.fury.io/py/svgbit
For further detail, please visit our `API reference`_ on readthedocs.org
Folder ``slides`` contains 10X Visium slide layout GPR files used in our
publication. Please refer ... |
69a4635363bad02fbfb59fd849ab69ef8ab22564b8c3835028a7a0290149d73a | Text | 6,811 | 123 | # Bisected graph matching improves automated pairing of bilaterally homologous neurons from connectomes
Benjamin D. Pedigo, Michael Winding, Carey E. Priebe, Joshua T. Vogelstein
[](https://direct.mit.edu/netn/article/doi/10.1162/netn_a_00... |
16f80e67f02d757e94c79f909385a6b2d97f2c5cfdda49fd7af4b012e63e963d | Text | 6,904 | 77 | # NLGC
Understanding how the brain processes the sensory information requires the ability to draw causal connections across different cortical areas of the brain. In the study, we propose a statistical framework, called network localized Granger causality (NLGC), to capture causal relationships at the cortical level f... |
f8ed24bedcabd629b0613426c652e3d15a5099fc6598aa39f6b46a00015c919c | Text | 7,102 | 181 | # 
[](https://doi.org/10.5281/zenodo.2595043)
[](http://ampligraph.readthedocs.io/?badge=latest)
[](https://badge.fury.io/py/genomic-benchmarks)
# Genomic Benchmarks 🧬🏋️✔️
In this repository, we collect benchmarks for classification of genomic sequences. It is shipped as a Python package, together with functions helping to download & manipulate d... |
de36dd8a06fb1b0d9b836188ae26a88560082aee7bcdb2ef17e67a47a9a4804a | Text | 7,418 | 129 | ===========
NetworkUnit
===========
A SciUnit_ library for validation testing of spiking networks.
.. _SciUnit: https://github.com/scidash/sciunit
.. image:: https://readthedocs.org/projects/networkunit/badge/?version=latest
:target: https://networkunit.readthedocs.io/en/latest/?badge=latest
.. role:: py(code)
... |
d03754ebe169ad679fa51c7725173ffef93ef4b204aeb20d1024aca2f28c2922 | Text | 7,428 | 255 | # graynet
[](https://doi.org/10.21105/joss.00924)
graynet builds single-subject morphometric brain networks from structural neuroimaging features such as cortical thickness, curvature, and volumetric gray-matter density.
It is designed for neuroscien... |
da9144810a697ac34e5a4886b9991ec532d618c3fab7f1815dcfc59a39152b92 | Text | 7,441 | 161 | # MEMES
**MRI Estimation for MEG Sourcespace (MEMES)** is a set of tools for estimating an appropriate structural MRI for MEG source analysis in Fieldtrip and/or SPM.
If you use MEMES or any of the scripts in this repository, we ask you to please cite the DOI link below:
```MATLAB
Robert Seymour. (2018, October 8). ... |
eb4fc34133eecd3e43274a69f8210551406d46ed4f1d879da257175473fe17cd | Text | 7,503 | 91 | <p align="center" style="display:flex; justify-content:space-between; width:100%;">
<a href="https://www.epfl.ch"><img src="assets/epfl_logo.png" alt="EPFL" style="height:80px; object-fit:cover;"></a>
<a href="https://www.hug.ch/"><img src="assets/hug_logo.png" alt="HUG" style="height:80px; object-fit:cover;"><... |
8f9d2904b82b8779f8e3436718c7110c5f645cf242eb679a233381d3df253d00 | Text | 7,527 | 161 | <a name="readme-top"></a>
<h3 align="center">UnitedNet</h3>
<p align="center">
An interpretable multi-task learning neural network for single cell-multi-modality biology
<br />
<a href="https://www.biorxiv.org/content/10.1101/2022.06.03.494730v1.full.pdf"><strong>Explore the manuscript (A new version wi... |
3c9826cfdd7035ededaca20536eecaf6dcb6646769361ec311fca2f07f754947 | Text | 7,644 | 181 | # Progressive Subsampling for Oversampled Data - Application to Quantitative MRI
This repository is the official implementation of our paper accepted in: Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022 [MICCAI version](https://link.springer.com/chapter/10.1007/978-3-031-16446-0_40) and [arxiv ... |
2ac3f0fbd3964b16b8a5caa46ef9c2e95d603fe2f8ae8c58e1b153808f618b31 | Text | 7,658 | 155 | [](http://bioconda.github.io/recipes/stream/README.html)
<!-- [](https://travis-ci.org/pinellolab/STREAM) -->
[![CI](https://github.com/pinellolab... |
e2f779cef212fbc54c3f9b1e273583720edac1ac9cc6ce6813b1e0386a968f0d | Text | 7,738 | 168 | <div align="center">
<img src="https://www.tensorflow.org/images/tf_logo_horizontal.png">
</div>
[](https://badge.fury.io/py/tensorflow)
[](https://badge.fury.io/py/tensorflow)
[![DOI](https://zenodo.org/b... |
fda6145b005f11534e35c481a2fca93c0fc1f36022a33e5098633d9aef739c32 | Text | 7,745 | 198 | <p align="center">
<img width="400" src="https://raw.githubusercontent.com/rkansal47/JetNet/main/docs/_static/images/jetnetlogo.png" />
</p>
<p align="center">
<b>For developing and reproducing ML + HEP projects.</b>
</p>
---
<p align="center">
<a href="#jetnet">JetNet</a> •
<a href="#installation">Installatio... |
69476a5c24c2c21efbc54f7a96a5ea5286cef57d2390915fd5e2533d7d9f158c | Text | 7,796 | 101 | # TSignal
TSignal is a deep architecture for Signal Peptide (SP) and cleavage site (CS) prediction inspired by the popular sequence translator model introduced in "Attention is all you need" [1]. We introduce the first unstructured predictor model in this field and provide extensive analysis to visualize its advantage... |
5b449b9d2fd91614a32460759d224116fb4a4551f66a1874978cbb7e99767919 | Text | 7,814 | 269 | # gpt3-relationship-extraction-to-kg
This repo hosts the code for Graham, Yates, and El-Roby 'Investigating Antiquities Trafficking with GPT-3 Enabled Knowledge Graphs: A Case Study'.
### OpenAI
Get a key for OpenAI, and save it to your machine's environment:
```
$ export OPENAI_API_KEY=[Your_GPT-3_API_KEY]
```
##... |
c30adaae9e6cef772a00a4aa42d9dbc2ec24f049f58162577e2ab73668675c53 | Text | 7,855 | 119 | # CloMu: Modeling and Predicting Cancer Clonal Evolution with Reinforcement Learning
CloMu is a neural network reinforcment learning based software for cancer phylogeny analysis. Specifically, it uses a special case of the GReinSS (generative reinforcement learning on structured states) technique: https://github.com/e... |
e20e466078dec10275a42384d614dbca36a6bf369d6255c34ef6df8762a88a6b | Text | 7,879 | 90 | # CBDA
<a href="http://socr.umich.edu/HTML5/CBDA/"><img align="middle" src="https://raw.githubusercontent.com/SOCR/CBDA/master/Images/CBDA_wordcloud.png"></a>
**Compressive Big Data Analytics (CBDA)**
Table of contents
=================
<!--ts-->
* [Table of contents](#table-of-contents)
* [Overview](#overvie... |
126e0a132acad6db67857035cd337632d17ed5bbaea3063f3207d4dd6609b52c | Text | 7,910 | 271 | # gpt3-relationship-extraction-to-kg
This repo hosts the code for Graham, Yates, and El-Roby 'Investigating Antiquities Trafficking with GPT-3 Enabled Knowledge Graphs: A Case Study'.
[](https://zenodo.org/badge/latestdoi/603109188)
### OpenAI
Get a key for OpenAI, and ... |
5c0be0112e36beb71181dce06624793ab179e5a723439b2db3a2907a479dfd3a | Text | 7,932 | 149 | |License| |PyPI version| |doi| |Python versions| |Documentation Status|
==============================================================
siibra - Software interface for interacting with brain atlases
==============================================================
Copyright 2018-2025, Forschungszentrum Jülich GmbH
*Auth... |
2490cff8a89c7f5a7a2c6cd8bc33d2f34cfc647c5073bb3743529ac279bbb2b0 | Text | 7,954 | 177 | # A Hybrid Approach to Full-Scale Reconstruction of Renal Arterial Network
Xu, P., Holstein-Rathlou, NH., Søgaard, S.B. et al. A hybrid approach to full-scale reconstruction of renal arterial network. _Sci Rep_ **13**, 7569 (2023).
https://www.nature.com/articles/s41598-023-34739-y
Here we provide the code files us... |
c6af83e1f72eb7633c09292885c9ce4583385fe67cdf0bb693f7754daa0c2bc2 | Text | 7,980 | 124 | # Fast Evaluation of the Adsorption Energy of Organic Molecules on Metals via Graph Neural Networks
<div align="center">
<img src="./media/GNN2.gif" width="60%" height="60%" />
</div>
## Overview
This is the code repository related to the work "*Fast Evaluation of the Adsorption Energy of Organic Molecules on M... |
b56cce7a4c8f36f312973149e466352d79086bcf41c6a298dc0b171a6c755b3a | Text | 8,059 | 170 | # Robust enhancer-gene association prediction using single cell transcriptomes and epigenomes
[](https://pypi.org/project/robustlink/)
[](https://pypi.org/project/robustlink/)
[
For more information about PPAD, read our paper at: https://academic.oup.com/bioinformatics/article/39/Supplement_1/i149/7210436
PPAD is a deep... |
09f465473c707f20a26b326db950806f2cf44d3d2f7621041508e1f1c35cb631 | Text | 8,200 | 151 | <!--
Copyright (c) ONNX Project Contributors
SPDX-License-Identifier: Apache-2.0
-->
<p align="center"><img width="40%" src="https://github.com/onnx/onnx/raw/main/docs/onnx-horizontal-color.png" /></p>
[](https://pypi.org/project/onnx)
[![CI](https://github.co... |
d4391b4721a4e4e634034d705a0101889259d1c590fb3dede524bdf667d706f2 | Text | 8,221 | 156 | |License| |PyPI version| |doi| |Python versions| |Documentation Status|
==============================================================
siibra - Software interface for interacting with brain atlases
==============================================================
Copyright 2018-2026, Forschungszentrum Jülich GmbH
*Auth... |
428ae02cdcd1d01d6092c6da5197b58b7ab2313d58efe0e0df90db8eaa95b29c | Text | 8,364 | 106 | # BA-Net: data-driven estimation of tissue attachments
<div align="center">
<img width="800" height="160" src="pictures/teaser.png" alt="data-driven estimation of anatomical attachments">
</div>
This repository shares a dataset of manipulation (grasping and lifting) of deformable (silicone) phantoms with the dVRK Pat... |
0f13ec95526acc9b1e024a1675f21ec7d9a623e107aa7aefd7ec972868844868 | Text | 8,422 | 172 | <a name="readme-top"></a>
<h3 align="center">UnitedNet</h3>
<p align="center">
Explainable multi-task learning for multi-modality biological data analysis
<br />
<a href="https://www.nature.com/articles/s41467-023-37477-x"><strong>Explore the manuscript
</strong></a>
</p>
</div>
<!-- TABLE OF CONTE... |
068659c5723a28dfc417d1c5db2b4957458d723a7a1a6658d33103b0a5f65eee | Text | 8,487 | 80 | # Microstate Template Editor and Explorer
## Installation
1) Make sure you have installed Matlab 2022b or above.
2) Download the two files MSTemplateEditor.mlappinstall and MSTemplateExplorer.mlappinstall
3) In MATLAB, select the APPS tab, hit the Install App button, and select the two downloaded files
4) The Apps sh... |
ef2e33b1a506ef777ba02b4089c3475b7aa79ba7e4b5626b871f973438c76deb | Text | 8,547 | 183 | |Travis| |Codecov| |Codacy|
Important
=========
This project is not actively maintained anymore and I would suggest you check out: https://github.com/powerfulbean/mTRFpy
pymtrf
======
pymtrf is a translation to Python 3.6 of the mTRF Toolbox (v.1.5) for MATLAB, which can be found at http://www.mee.tcd.ie/lalorl... |
f4155121fbf1c098c0f6a22ddd6b0664892d16b2ac3d5e6f12f42bdcad68d376 | Text | 8,877 | 281 | CRISPRO
[CRISPRO logo]
Analysis and Visualization of Saturating Mutagenesis CRISPR Screens
CRISPRO is a pipeline to process next generation sequnecing data from
saturating mutagenesis CRISPR screens, whereby sgRNAs are mapped to
amino acids of the protein, allowing for the inference of functional
scores for amino ac... |
6c1de657911b483352ca757d8164cc63777ee1ea83ac4983f5cf540014794405 | Text | 8,889 | 199 | # There Is No Free Lunch in RLVR
### Every pass@1 Gain Has a pass@k Price
[](LICENSE)
[](https://www.python.org/)
[](https://github.com/leylabmpi/ResMiCo/actions/workflows/pythonpackage.yml)
# Introduction
ResMiCo is a deep... |
7939c5265f02c2b5d5b0731117375354b6f0ecad5b6c708a9bb5fd4d31c1b620 | Text | 9,291 | 152 | # Lorentz Group Equivariant Jet Autoencoder
[](https://zenodo.org/badge/latestdoi/361547423)
## Descriptions
This jet data generative model exploits the symmetry of the [Lorentz Group](https://en.wikipedia.org/wiki/Lorentz_group), a [Lie group](https://en.wikipedia.org/wi... |
3384b6c2f822178368293e1dba9dd6d465e651734ebe0c3be6255011ba53c473 | Text | 9,436 | 152 | # Lorentz Group Equivariant Autoencoders
[](https://zenodo.org/badge/latestdoi/361547423)
## Overview
This autoencoder model exploits the symmetry of the [Lorentz Group](https://en.wikipedia.org/wiki/Lorentz_group), a [Lie group](https://en.wikipedia.org/wiki/Lie_group) t... |
3a4bf90f3aa018e181f6f6e43a775680b0a55388899ca457ffafe45995c43cfb | Text | 9,544 | 173 | # MUSE: multi-modality structured embedding for spatially resolved transcriptomics analysis
MUSE is a deep learning approach characterizing tissue composition through combined analysis of morphologies and transcriptional states for spatially resolved transcriptomics data.
> Citation:
> Bao, F., Deng, Y., Wan, S. et ... |
7ebe4236c3b22dcb21c7094176f8562b3fcaaf608d733dddefdcbe0b17b5a6d5 | Text | 9,550 | 108 | # EMG-denoising
Functions to denoise High Density EMG signals.
## Table of Contents
* [ECG Contamination](#ECG-Contamination)
* [Movement artifact, PLI, WGI contamination](#Movement-artifact,-PLI,-WGI-contamination)
* [Baseline wander filter](#Baseline-wander-filter)
* [Technologies](#Technologies)
* [Setup](#Setup)
*... |
db0a4e120f94855df477a84e1e966bd5c022049b320a36d3813081b3e75c407b | Text | 9,587 | 215 | # MolGAT Model
The MolGAT model is a deep learning model for molecular property prediction. It is based on the Graph Attention Networks (GAT) architecture and is designed to work with molecular graphs.
Unlike the GAT model, the MolGAT model takes n-dimensional edge features as input, which allows it to incorporat... |
32e0c513dc83fa5b8d3d6ed564a5b918d927b4570b24c1386779df6e1a78dcf5 | Text | 9,681 | 196 | # *SleepStages* installation and usage guide
## Required packages
SleepStages runs on Windows and Mac machines with Python 3 installed. Required packages can be installed using pip (Python package installer).
```
pip install torch pytorch-ignite torchsummary pyserial PyQt5 tqdm scipy matplotlib scikit-learn
```
If ... |
203b9a0953d3b216010b12e3d9b1de08d6b9a3623978ed54dc4272f65f3340ff | Text | 9,977 | 262 | =================
Welcome to ROILoc
=================
ROILoc is a registration-based ROI locator, based on the MNI152 09c Sym template, and the CerebrA Atlas. It'll center and crop T1 or T2 MRIs around a given ROI.
Results are saved in "LPI-" (or "RAS+") format.
.. image:: https://raw.githubusercontent.com/clementpoi... |
f4af1763aec26b9ff38299caec2add173adf4a41710acb29c7a42314fd8894fb | Text | 10,124 | 273 | ========================================================
bycycle - cycle-by-cycle analysis of neural oscillations
========================================================
|ProjectStatus| |Version| |BuildStatus| |Coverage| |License| |PythonVersions| |Publication|
.. |ProjectStatus| image:: https://www.repostatus.org/b... |
a25e362eee3a12554194840e3381b5ca1b09455385b63ffb10f496fe8e01830f | Text | 10,314 | 188 | # ArtifactClassifier-pySEAS
Collection of scripts utilized to classify artifact components vs neural signal from Independent Components that are outputs from pySEAS.
**Publication**:
Weiser SC, Mullen BR, Ascencio D, Ackman JB (2023) Data-driven segmentation of cortical calcium dynamics. PLOS Computational Biology 1... |
e549230ae588a5b74da70cad2f62e8040dc8a67aa1ed9e8d58bc7b1080e51f03 | Text | 10,476 | 149 | ## EXPERT - a scalable model for quantifying source contributions for microbial communities
[](https://pypi.org/project/expert-mst/)
[](https://pepy.tech/project/expert-mst)
![](https://img.shields.io/badge/... |
f7da85ef464827b71c4f00fba1a29a18c6fab06d907af2925c6f48db01325a98 | Text | 10,623 | 304 | CRISPRO
=======
.. image:: ./CRISPROlogo.png
:alt: CRISPRO logo
Analysis and Visualization of Saturating Mutagenesis CRISPR Screens
-------------------------------------------------------------------
CRISPRO is a pipeline to process next generation sequnecing data from
saturating mutagenesis CRISPR screens, whereb... |
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