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ae0c8a3a1a493f013f75ce9a2748ef89ba2001607240b474b117b9161c0a098a | Text | 4,689 | 58 | # Sort & Slice: A Simple and Superior Alternative to Hash-Based Folding for Extended-Connectivity Fingerprints (ECFPs)
Code repository for the paper [Sort & Slice: A Simple and Superior Alternative to Hash-Based Folding for Extended-Connectivity Fingerprints](https://doi.org/10.1186/s13321-024-00932-y).
This reposito... |
87d79cc428a68fec6f53ebe264ccdac8e361f962d6fcd587996542d31d235162 | Text | 4,693 | 64 | # HMM Analysis on Wakeman & Henson Dataset
The repository contains the scripts to run two different types of Hidden Markov Model analysis on a freely available MEG dataset. The analyses are described in full in our accompanying paper
Quinn, A. J., Vidaurre, D., Abeysuriya, R., Becker, R., Nobre, A. C., & Woolrich, M.... |
21f7d9c4e13519b32a8b1f89fbb8e9a91ee3b29d23e5b9f0d7fb8631e5bc93e1 | Text | 4,717 | 42 | multdist
========
**NOTE: The functions in this repository have been incorporated into [highdim](https://github.com/brian-lau/highdim), a more comprehensive set of Matlab functions for multidimensional statistics.**
Matlab code for non-parametrically testing whether two multidimensional samples were drawn from the sam... |
3561b4620ad631f10043dc4de8942fcc2d593c9fac182f99ee0517c49b10409c | Text | 4,718 | 31 | # Molecule-Discovery-by-Context
Repo for "Molecule-Discovery-by-Context" project in the LLM for Materials Hackathon
See more details in the paper: [14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon](https://arxiv.org/abs/2306.06283)
The escalating ... |
c70a5fa2970d15f5b38c42fb17928364d964f985c983673837135d66cadbe38d | Text | 4,726 | 108 | # Unfold.jl
<img align="right" width="33%" src="https://www.unfoldtoolbox.org/_images/unfold_800x377.png">
Toolbox to perform linear regression on biological signals.
[](https://unfoldtoolbox.github.io/Unfold.jl/dev)
 using the Statistics and Machine Learning Toolb... |
3763b0869fa11c2a7517b5be7ad64cba2aa5d0cd452953e0258217626973dfbe | Text | 4,737 | 32 | # MRI-based Whole-Brain Elastography and Volumetric Measurements to Predict Brain Age
Brain age, as a correlate of an individual’s chronological age from structural and functional neuroimaging data, enables assessing developmental or neurodegenerative pathology relative to the overall population.
Accurately inferring ... |
8200664879eaa333be860bbcf6ae522dcacbda7f2b2b7afad6cb7b4057b640df | Text | 4,745 | 135 |
<div align='center'>
# Calibrated Adaptive Teacher for Domain Adaptive Intelligent Fault Diagnosis
[Florent Forest](https://florentfo.rest)<sup>1</sup>
[Olga Fink](https://people.epfl.ch/olga.fink)<sup>1</sup>
<br/>
<sub>
<sup>1</sup> Intelligent Maintenance and Operations Systems (IMOS), EPFL, Lau... |
f02fd251100204b0569a4d09a509c7e08e76350fa1cb091618560dcf255d8316 | Text | 4,745 | 116 | [](https://github.com/scverse/pertpy/actions/workflows/build.yml)
[](https://codecov.io/gh/scverse/pertpy)
[. DEGage take the raw counts of scRNA-seq as inputs, and thus avoid introducing artificially... |
7ce031699013160dcb1f21049c961ae85df5d83cc2baecb4d3fbf198d7dc0e0e | Text | 4,757 | 99 | <h1>AIDA<i>qc</i></h1>
<img align="right" src="https://github.com/Aswendt-Lab/AIDAqc/blob/main/docs/AIDA_Logo_wide.001.png" width="500">
*An automated and simple tool for fast quality analysis of animal MRI*
<br/>
<br/>
<h3>Features</h3>
- **Input:** Bruker raw data or NIFTY (T2-weighted MRI, diffusion-weighted MRI,... |
2db670ab3115689c46f94ca5e387c6b2417c9f49bc8bc0dfad23d6b3ef5c8aba | Text | 4,780 | 108 | # Autograd [![Checks status][checks-badge]][checks-url] [![Tests status][tests-badge]][tests-url] [![Publish status][publish-badge]][publish-url] [![asv][asv-badge]](#)
[publish-badge]: https://github.com/HIPS/autograd/actions/workflows/publish.yml/badge.svg
[checks-badge]: https://github.com/HIPS/autograd/actions/wo... |
7174052febdb401897037a6deb34b7f3860e4c2cea91e7f7746a7a453c5ae751 | Text | 4,800 | 144 | <p href="https://www.brainimagelibrary.org/">
<align="center" width="100%">
<img width="100%" src="https://i.imgur.com/ljZKq8h.png">
</p>
# Description
View datasets archived at the **[Brain Image Library](https://www.brainimagelibrary.org/)**.
**NOTE: This plugin is under early development. Currently, onl... |
7de87e6101a8c3b57863dbb3ba69c6a04d9ce67dca3c2d8716499ba758d0476a | Text | 4,803 | 95 | # SchNarc
A SchNetPack/SHARC interface for machine-learning accelerated excited state simulations.
# System requirements
A personal computer (suggested RAM: 4GB or larger; suggested CPU: 1 core or more, 2.7 GHz or faster), ideally with a dedicated graphics card (GPU), is needed for installation running Linux. We hav... |
b9bedcdf3cec19cebee28279c69ee904dc07e7267e9cda4b97a86b2881322f31 | Text | 4,805 | 99 | # DeepSIF: Deep Learning based Source Imaging Framework
DeepSIF is an EEG/MEG source imaging framework aiming at providing an estimation of the location, size, and temporal activity of the brain activities from scalp EEG/MEG recordings. There are three components: training data generation (```forward/```), neural net... |
96ee9dd7d66350549b3584487e15fe73c1b069bbf4f91248f6d3e5f4bb974976 | Text | 4,818 | 129 | # SkyMap
<p align="center">
<img alt="Python versions: 9.9 9.10 9.11 9.12" src="https://img.shields.io/badge/Python-3.9_3.10_3.11_3.12-green">
<a href="https://github.com/raulhigueras/skymap_graph_generator/LICENSE"><img alt="License: MIT" src="https://img.shields.io/badge/license-MIT-blue"></a>
<img alt="inport style... |
db8f3d2f54569fb6fe1eed2309429aee55dd2bef25b405187c139bc4a8767c94 | Text | 4,832 | 92 | # Single-Neuron Representations of Odors in the Human Brain
[](https://opensource.org/licenses/MIT)
## Contents
- [Overview](#overview)
- [Abstract](#abstract)
- [Requirements](#requirements)
- [Code and Data structure](#code-and-data-structure)
- [... |
f45c61609d7bde0e0ea99a054f1b11ea8a025416670d9b7ec2dac460583fe08d | Text | 4,840 | 119 | # DynamicBind
Source code for the *Nature Communications* paper [DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model](https://www.nature.com/articles/s41467-024-45461-2).
DynamicBind recovers ligand-specific conformations from unbound protein structures (e.... |
d2e076e788a48e0c86cf6ce25bd83d9565613bb2cfdd09d6068fc0247529a937 | Text | 4,882 | 127 | # MCeleM6
### General Info
***
MCeleM6 is a MonteCarlo tool developed to reproduce the dynamics of protein gradient formation in the C. elegans embryo.
In particular, it focuses on PLK-1 and MEX proteins.
## Requirements
***
* cmake: version > 3.1
* make
* gcc
* Python
* Matplotlib
* numpy
* scip... |
bd31a2f3a164f19084c6faf68a52f687cd3f0a9669a88df847ce4cd4b9eeeb8d | Text | 4,888 | 94 | # Assemblyfire
Detection of cell assemblies, and analysis of their connectome.
[](https://zenodo.org/badge/latestdoi/315388334)
## Examples
```
assemblyfire -v assemblies configs/np_10seeds.yaml # find assemblies (for every repetition)
assemblyfire -v consensus config... |
41f5b16f9c61c4444fba08a05218b15b155a3ac63593b5098fe8e3aab81abfd4 | Text | 4,905 | 57 | Written by R.J. Addante, 3/26/2024
Note on event codes for data used in Muller, Sirianni, & Addante, 2021; Addante et al., 2023; Addante et al., 2024:
-First: be aware that extensive details are provided in the IMAP script files
-Second: Experimental structure of the memory retrieval paradigm had event codes logged i... |
3ecbed7842798545b02f5be9ebee4f2162ace46466eaa6e14b48ca820a24b0e6 | Text | 4,912 | 104 | [](https://www.python.org/downloads/release/python-390/)
[](https://github.com/zeyang-shen/maggie/issues)
[submitted to the Frontiers Artificial Int... |
de208fa8583e539eb3a2f7c90cb63e08ad4523c8c1f3d13aa6bc653e5ffd27ae | Text | 4,933 | 47 | # Adafruit GFX Library  [](https://adafruit.github.io/Adafruit-GFX-Library/html/index.html)
This is the core graphics ... |
46dcdd05e460fd76c1a4c06877cc3e201a114413b6c71394c88be1925fdc944a | Text | 4,934 | 110 | [](https://codecov.io/gh/corail-research/SeaPearl.jl)
![Docs](https://img.shields.io/github/actions/workflow/status/corail-research/Se... |
23472b94b5d828030058de3157cbb8a551a239b6c592433344a5df7707ab2301 | Text | 4,937 | 42 |
# protocol
This GIT contains all materials referenced in "Effects of daily environmental, physiological, and lifestyle factors in functional brain connectivity" pre-registration (see https://osf.io/5hu9c/). This work is later published as "Longitudinal single-subject neuroimaging study reveals effects of daily environ... |
44cb85db16eb68e6704b2564895012b651d6fb9d7420da5459c684bd883bf5c8 | Text | 4,962 | 102 | # Fisher Kernel
Code for Fisher kernel and other methods to predict from Hidden Markov Models.
The Fisher kernel (Jaakkola & Haussler, 1998) is a framework for combining a discriminative with a generative model, making it a mathematically principled approach to using a Hidden Markov Model for machine learning. Beside... |
87d77298050e884bdb73bd4cdfae15e0be35671624f056ca2861282b0ed99c44 | Text | 4,965 | 99 | .. image:: https://raw.githubusercontent.com/esi-neuroscience/syncopy/master/doc/source/_static/syncopy_logo_small.png
:alt: Syncopy-Logo
Systems Neuroscience Computing in Python
========================================
|Conda Version| |PyPi Version| |License| |DOI|
.. |Conda Version| image:: https://img.shield... |
936cc9ef9a85f8629b001314c511399d562ca9e2ee973c2ee95ddc41f4218e7c | Text | 5,017 | 72 | # poolWGS2SNP: a high-performance workflow to identify SNPs from pool-seq data
----
The bioinformatic workflow to call SNPs from Fastq files of raw pool-sequenced pair-end DNA reads.
Related publication:
[Feng S, DeGrey SP, Guédot C, Schoville SD, Pool JE. 2024. Genomic Diversity Illuminates the Environmental Adapta... |
567a8ca9d09f10877ced307c4e79f4689f66edc39ec8a65158ee81fc1652bbd1 | Text | 5,022 | 68 | ## Welcome to the repository for the research project titled **_Machine learning unravels inherent structural patterns in Escherichia coli Hi-C matrices and predicts chromosome dynamics_**
# Abstract
High dimensional nature of the chromosomal conformation contact map (‘Hi-C Map’), even for microscopically small bacte... |
fdce549f2dcd2e6ca10b2f7857d819f85d87b6088eb2389e9bd8641a09663194 | Text | 5,029 | 52 | # BurnICU_MusicTherapy_Signals
# Opensurce code of electrophysiological signals (EEG, ECG, EMG) during Music therapy with adult burn patients in the Intensive Care Unit
## Table of Contents
- [1. Experimental Design](#1-experimental-design)
- [1.1 Study Overview](#11-study-overview)
- [1.2 Electrophysiological M... |
7f6517e66899998c01e19203a66715386bf367d3977a28374b814b7180e4744e | Text | 5,063 | 102 | # A Benchmark for Visual Identification of Defective Solar Cells in Electroluminescence Imagery
[](https://pypi.org/project/elpv-dataset)
[](https://pypi.org/project/elpv-da... |
83412c465b75cc5fae9ecf43044bc9bdf20fbc5cf7ad74c32aaadbdf0afd73c2 | Text | 5,097 | 42 | # Longitudinal single-subject neuroimaging study reveals effects of daily environmental, physiological, and lifestyle factors on functional brain connectivity
This repository contains the code and instructions to analyze the data collected for the article "Longitudinal single-subject neuroimaging study reveals effects ... |
69fd7bbfbb2f94d859f219993bbc27968e26dfd11e432b4ce8e5af8c36e1febb | Text | 5,110 | 62 | # GRAF
Graph Attention-aware Fusion Networks
A large number of real-world networks include multiple types of nodes and edges. Graph Neural Network (GNN) emerged as a deep learning framework to generate node and graph embeddings for downstream machine learning tasks. However, popular GNN-based architectures operate on ... |
2d7eed2535fcc2c11924c583756db65c729f1c4d8b3b76022a8f8c1ccbf06241 | Text | 5,126 | 82 | # The sign is not in the picture (version 2, October 2026)
I am a secondary-school student in Naples, Italy. This record contains my research project on a computer model of the
fruit fly brain. It is not a peer-reviewed paper. Version 1 is the snapshot of 30 September 2026
(doi:10.5281/zenodo.23047886).
## What the p... |
2e3c0883565b6c1430ff5f4dc3c25fae6d0940fe40586b1fe57efd50bad0109a | Text | 5,134 | 103 | # 🧬 GZSper: Illuminating Single-Cell Landscapes with GWAS Insights
[](https://opensource.org/licenses/MIT)
GZSper (GWAS Z-score to Single-cell Phenotypes for Expression Research) is a Python toolkit designed to bridge the gap between GWAS and single-cell R... |
659e016500700259a9afa9b636a099ac65298c30c636be55b77b2c221bbcea17 | Text | 5,146 | 117 | # medical_image_segmentation
Medical image segmentation
Code for : https://towardsdatascience.com/vessel-segmentation-with-python-and-keras-722f9fb71b21
### Data
Available at https://www.isi.uu.nl/Research/Databases/DRIVE/
Unzip in ./input
# Vessel Segmentation With Python and Keras
### Motivation :
Automatic seg... |
3ed7a7cc5271e4a3d31d8648ee271cc3d458dc06040ea052fec74062b62c5eae | Text | 5,148 | 93 | # A Protocol for Artificial Intelligence-Guided Neural Control Using Deep Reinforcement Learning and Infrared Neural Stimulation (Coventry and Bartlett, STAR Protocols 2025 6, 103496)
This repository is a supp... |
2a3defacf24442b50bd102b4b06dc894720df3c2364e809a24603eeb95a50803 | Text | 5,151 | 56 | # DELCODE_SAME
**FADE and SAME scores for multi-center DELCODE study**
This code belongs to the paper "Single-value fMRI scores reflect both stage and risk across the Alzheimer's disease continuum" by Soch et al. (2021), currently under review at *Brain* and publicly available from *medRxiv*. For instructions how to ... |
879c4621bc1cad28f54666165527abbc256339ffbc2df8da8d9968479d588d6b | Text | 5,155 | 96 | #GAP
Short for Genotyping Array Pipeline.
Consist of the following workflow:
```
⎛¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯⎞
⎜ Iscan writes IDAT files to GATTACA {01,02}machines ⎜
⎜ ... |
2e41df29f658e88818504e3bae5e435443292ee219c7a7010af210db18a294b7 | Text | 5,201 | 43 | # Random Promoter Dream Challenge 2022
To address the lack of standardized evaluation and continual improvement of genomics models, we organized the [Random Promoter DREAM Challenge 2022](https://www.synapse.org/#!Synapse:syn28469146/wiki/617075). Here, we ... |
f80c485fb027d0fb4775b6ee19420c138049d6dd3df57146a42b0adfdad11521 | Text | 5,220 | 148 | venn.js [](https://travis-ci.org/benfred/venn.js) [](https://www.npmjs.com/package/venn.js)
=======
A javascript library for laying out area proportional venn and euler diagrams.
Details of h... |
8937a7849f8d06263dd77cf07c27d52b72a55fcd008b2332c67e93b15db50606 | Text | 5,230 | 83 | # TriDy-tools
Tools for creating new selection parameters and distributing featurisation tasks forthe [TriDy pipeline](https://github.com/JasonPSmith/TriDy).
### Setup
There are four pairs of `.py` and `.config` files. Each `.config` file is meant to be changed, then the `.py` file is meant to be executed with the `.... |
b3f7c718c73a33c9c657ad17dde713a5382a5ea980aa62a3bc6463646bbcedb8 | Text | 5,234 | 93 | # toposampling - Topology-assisted sampling and analysis of activity data
An analysis pipeline for joint analysis of neural spiking data and synaptic connectivity.
This repository encompasses all analyses performed in the following manuscript:
### Topology of synaptic connectivity constrains neuronal stimulus represen... |
7bea6464c552402e73ce0d6a93a6c36cda3ed3a574c0fed62846e4d3f81417a3 | Text | 5,258 | 125 | # BeBOP BCI
**Beta Bursts Occurrence Patterns for Brain-Computer Interfaces**
[](https://www.repostatus.org/#active)
[](https://snakemake.bitbucket.io)
[ data. Briefly, m6ATM uses a collection of reads to characterize each transcriptomic site and determines whether it is m6A modified or ... |
f2c1e14df79ad9e2f4d8b835eb456e5bb88c56a326636049938392154d7eee53 | Text | 5,353 | 106 | # AD EV Characterisation
#### *This analysis is complete and should not see major updates.*
**In this project are the code and results associated with the manuscript entitled: “Tau filaments are tethered within brain extracellular vesicles in Alzheimer's disease”.**
```
This file is part of AD-EV-characterisation.
Cop... |
46ab707a39586478105f9c29b26b071d28a54cef8c13e6a12d00a5800cffe9b0 | Text | 5,367 | 83 | # The sign is not in the picture (version 2.1, October 2026)
I am a secondary-school student in Naples, Italy. This record contains my research project on a computer model of the
fruit fly brain. It is not a peer-reviewed paper. Version 1 is the snapshot of 30 September 2026
(doi:10.5281/zenodo.23047886). Version ... |
e254934bcdc3fea4bf7f945e108ee462f4cdc2ce5507c3b812ec8a505a1c24e6 | Text | 5,389 | 50 | [](https://zenodo.org/doi/10.5281/zenodo.11143879)
# WTE_AI_article
White Tailed Eagle Article - place to put the cleaned scripts, functions - and supplementary material for the article
## R and packages used
> 2024-09-11 The packages and versions used are now saved in "r... |
630c41592147513e7d324ec55036fc7cbf7872bf8cc67198f31941f4406d30e6 | Text | 5,436 | 77 | # ICoN: Integration Using Co-attention across Biological Networks
We propose ICoN, a novel unsupervised graph neural network model that takes multiple protein–protein association networks as inputs and generates a feature representation for each protein that integrates the topological information from all the networks.... |
62203bc02c293fb433800fb64725f7eefe33a62a37b4fdf40951e46cad9f1524 | Text | 5,449 | 69 | # The Bio-logger Ethogram Benchmark (BEBE)
This repository contains code for model training and evaluation, presented in our forthcoming work:
> B. Hoffman, M. Cusimano, V. Baglione, D. Canestrari, D. Chevallier, D. L. DeSantis, L. Jeantet, M. Ladds, T. Maekawa, V. Mata-Silva, V. Moreno-González, A. Pagano, E. Trapot... |
3c7e186f499562ee6aefc2f6f26fda8e160390815cd8c76aaf3b81f0121292b1 | Text | 5,458 | 52 | # Neuronal traveling waves form preferred pathways using synaptic plasticity - Reproducibility Code
## What is this for?:
This code is meant to recreate results from the paper "Neuronal Traveling Waves Form Preferred Pathways Using Synaptic Plasticity" by Kendall Butler and Luis Cruz. It implements the BRIAN neural sim... |
b4587119557f32ce6c17d272ed9aba48c1b862f66b1b3cb47b848c66db365408 | Text | 5,487 | 94 | # FOREST - Fetal Organ T2* Relaxometry at Low Field Strength
Here, we present an automatic pipeline for quantitatively analyzing fetal body organs using T2* relaxometry as described in Payette et al "An Automated Pipeline for Quantitative T2* Fetal Body MRI and Segmentation at Low Field" - https://link.springer.com/cha... |
f9dd71f884492f966aa832fe56ecd57e730c6486934470f207bee503287032ac | Text | 5,501 | 75 | # Interpreting machine learning models in neuroimaging
This repository includes Matlab and Python codes and sample fMRI data used in our Nature Protocols paper **[Toward a unified framework for interpreting machine-learning models in neuroimaging](https://www.nature.com/articles/s41596-019-0289-5)**.
## Dependencies
... |
5184fe8fba72a30cc3c5b3b1ae2dd1df04fcf49302e4f8ec309500377d2f9b0d | Text | 5,513 | 88 | # Draw and label trial plots in QGIS
This plot drawing tool for QGIS aims to provide a simple solution to create ploygons that represent your plots over satellite or aerial imagery of your trials. The beauty of this tool is in its automatic labeling capabilities, which in most cases allows you to replicate your labels... |
e17d5d86955f30cbd1aa1904c646a4230b63b01de3e5c62ed47a303e794b967f | Text | 5,521 | 98 | # dcm2bids
Your friendly DICOM converter.
[](https://unfmontreal.github.io/Dcm2Bids)
[](https://zenodo.org/badge/latestdoi/59581295)
[, Enhlink enables linking target genomic regions with their surrounding genomic features. It wa... |
ca4a1d8a24b9b6ac39ca705861eae866f80fe591da4f97a3f2cd3bebc8ebac72 | Text | 5,565 | 141 | Soft DTW for PyTorch in CUDA
===
Fast CUDA implementation of [soft-DTW](https://github.com/mblondel/soft-dtw) for PyTorch.
Based on [pytorch-softdtw](https://github.com/Sleepwalking/pytorch-softdtw) but can run up to 100x faster!
Both `forward()` and `backward()` passes are implemented using CUDA.
My implementation is... |
91e7d59ef661f57549f313c60421b6f1ee10aa78078f65756dd934417e959bc0 | Text | 5,583 | 85 | ***Documentation: Astrocyte Heterogeneity***
**Install Anaconda**
1. Install Anaconda
2. Start Anaconda Prompt with Admin rights
3. python -V # check python version
4. conda install python=3.9.13 # install specific python version
5. python -c "import numpy; print(numpy.version.version)" # check numpy version
6. ... |
c5bf516d352cbce196e95929617a5efdf9c5947e2162e20bc5eff8cb990b25b4 | Text | 5,587 | 68 | # HBP survey plots
This repository hosts the survey plots of the paper `Interdisciplinary and collaborative training in neuroscience: Insights from the Human Brain Project Education Programme`.
The figures 8-11 in the paper are created by the Python file `plo... |
4c7fb3f9798f9a6de08b9024ead7ed90853ad273b5ce153c2d89c1d7c4ff6781 | Text | 5,590 | 159 | # SpliceTransformer
The SpliceTransformer (SpTransformer) is a deep learning tool designed to predict tissue-specific splicing sites from pre-mRNA sequences.
# Installation
## 1. Retrive the repository
The program is developed in Python and the source code can be run directly.
However, the model weights file is to... |
4f7d9dd04a2da98d9292aa0bb342f43c160ba00c7dc6c9712aac47a38a6de80a | Text | 5,619 | 98 | # Equipping-Computational-Pathology-Systems-with-Artifact-Processing-Pipeline
This repository contains source code for the paper "Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs"
#Abstract
Histopathology is a gold standard for cancer ... |
895448f922ca9c086af1479fe4a970c49559095d6e087c82cca83a6aef71960e | Text | 5,663 | 100 | [](https://colab.research.google.com/github/elephant-track/elephant-server/blob/main/elephant_server.ipynb)
## ELEPHANT: Tracking cell lineages in 3D by incremental deep learning
<table>
<tbody>
<tr>
<th rowspan=7><img src="../asset... |
567a2df047b8899951323d51ee8cf4b0c3b0d1fad1eca31ba7ce5714f1315da5 | Text | 5,668 | 121 | # Spall
Implementation of "Spall: accurate and robust unveiling cellular landscapes from spatially resolved transcriptomics data using decompositional network"
## 1. Introduction
Spall is a cell proportion decomposition network for sequencing-based SRT data. Spall works in a transductive learning manner, employing ge... |
aab661032a580c29b91f82a78eb3db829e90240e28ce22a8d00b56e40664f38d | Text | 5,681 | 145 | # maximum_entropy_package
`maximum_entropy_package` is a Python package designed to create maximum entropy models for neural population codes based on empirical data. The package allows you to construct independent, pairwise, and random projection models, leveraging GPU acceleration through PyTorch for efficient comput... |
645649b524f55e3f60036e9f5081b28ab980dc6cc32e0d34686d29b2385dca0c | Text | 5,719 | 90 | # EMATA #
## INSTALLATION ##
The toolbox is compatible with Unix (including MacOS) and Windows systems and can be used in MATLAB. An initial set-up may be required due to dependencies on external MATLAB packages and FSL:
* The external MATLAB packages, i.e. the NIfTI toolbox (https://www.mathworks.com/matlabcentral/fi... |
800e4c1232209cb1f89457989c2bbec8b8ac97c8c099c0c9b1757fc87ddd888f | Text | 5,722 | 133 | # Causal Effect Detection and Correction
[](https://arxiv.org/abs/2307.13868)
[](https://direct.mit.edu/imag/article/doi/10.1162/imag_a_00... |
f47f117c8aa936cdd5f82e3fe9e398211487a6c8d403499c4e27a460cad70ba8 | Text | 5,733 | 65 | # Inter-individual gene expression variability implies stable regulation of brain-biased genes across organs in three ray-finned fishes
Christabel F. Bucao<sup>1,2*</sup>, Consolée Aletti<sup>1</sup>, Alexandre Laverré<sup>1,2</sup>, Sébastien Moretti<sup>1,2</sup>, Alexandra Trouvé<sup>1</sup>, Andrew W. Thompson<sup... |
c106454e8ae7d71ee2b6ab50b314625c66335702867f51820d9cc2475e27c341 | Text | 5,747 | 96 | # Herding Spikes 2 Lightning
Fast spike sorting for high density multielectrode arrays
[](https://badge.fury.io/py/herdingspikes)
[](https://travis-ci.org/mhhennig/HS2)
#... |
c11b0e4c9882b6cdfde28eea2b256840de1fa4fd8d05382da576f20d54ddbae6 | Text | 5,846 | 123 | [](https://travis-ci.org/seung-lab/Julimaps)
# Alembic
ALignment of Electron Microscopy By Image Correlograms
A set of tools for elastic image registration in Julia.
## Alignment
Register coarsely-aligned sections to each other, and k-nearest ... |
ba802567090bc5c456faf41ba1ebe04b2a0cf86c606c09f0830de6272cdafee5 | Text | 5,856 | 110 | # Mesocircuit Model
[](https://mesocircuit-model.readthedocs.io/en/latest/?badge=latest)
<p align="center">
<img src="docs/source/_static/images/network_model_sketch_upscaled.png" alt="Mesocircuit network model sketch" wi... |
3f77f9c7d2bce2d330478ec4a8148475c43dddf0cc74daf3958d96ae57ae2add | Text | 5,859 | 98 | <h1> Computational noise in reward-guided learning drives behavioral variability in volatile environments</h1>
This is a project realised at Ecole Normale Supérieure by Vasilisa Skvortsova and Charles Findling under the supervisions of Valentin Wyart and Stefano Palminteri with collaborator Remi Dromnelle.
<h3> Link ... |
449f90fff67eacd8feb935fb3662eda4973c1c29fe167cd52b66af118cb77543 | Text | 5,870 | 144 | # `pyshot`: a Python interface for the SHOT descriptor
The original implementation originates from the author of [1], [2], [3].
It has been marginally modified to interface the computation of the SHOT
descriptors with other languages.
This project makes use of Cython to bind the implementation to a simple Python
int... |
8049be560c5ed8d28cbf712c52680aae52c8923d3920407d26fe1767b63344fb | Text | 5,888 | 150 | # [Rapid and automated interpretation of CRISPR-Cas13-based lateral flow assay test results using machine learning](https://pubs.rsc.org/sd/article-abstract/4/2/171/870940)
📄 **Paper:** [Xue *et al.*, *Sensors & Diagnostics*, 2024](https://doi.org/10.1039/d4sd00314d) (open access)
*Obtain rapid and accurate lateral ... |
a81914f4f20d38f3324f9162fc4ed27bf9a0efe00574050968c34bef845120bd | Text | 5,967 | 112 | 
========================
[](https://seung-lab.github.io/RealNeuralNetworks.jl/latest/)
[ models predicting chemicals bioactivity towards proteins associated to molecu... |
059c8d78e03a890a642eb2f0cb3d8914410de7c6ef2ce492ad2c7f7c941696fc | Text | 5,997 | 69 | # methAI
Containes python scripts for methAI article
# Summary
[decisionTreeDimReduction.py](https://github.com/bazyliszek/methAI/blob/main/decisionTreeDimReduction.py) uses a decision tree to classify the data, and stores the locations the decision tree used to divide on. These locations are likely to be the most us... |
29949f20f6b6511c42db52cf1c2fa4577ccd3e26f41e22601dcfd9834546fa2d | Text | 6,029 | 124 | # Feature-informed Phase-amplitude coupling estimation
[](https://opensource.org/licenses/MPL-2.0)
[](https://zenodo.org/doi/10.5281/zenodo.12667683)
This repository contains the necessary co... |
36bee8f2787492448b2277d46cd546fba1ab51a62621b3e8f6d3d134368f97bb | Text | 6,079 | 217 | # Article_Modeling_Mouse_ICM
## AI-powered simulation-based inference of a genuinely spatial-stochastic gene regulation model of early mouse embryogenesis
**_Preprint_ Article Link** [_ARXIV_]
[https://doi.org/10.48550/arXiv.2402.15330](https://doi.org/10.48550/arXiv.2402.15330)
__Partial Data Bank Link__ [_Zenodo_... |
bb016cc749ae8597f5b0317bbbcdeddeca1aaa2ff17c02cffe4d5b7ae05fb2a8 | Text | 6,099 | 126 |
<!-- badges: start -->
[](https://www.repostatus.org/#inactive)
[](https://cran.r-project.org/package=hyperSpec)
[](https://doi.org/10.5281/zenodo.13857412)
This is the official code of the paper "MolNexTR: a generalized deep learning model for molecular image recognition".
## :sparkles: Highlights
<p align="justify">
In this work, We propose MolNexTR, a ... |
28577613a86a18ae87f4327fca1a457954651efae908cae4d3e230879b3757c5 | Text | 6,108 | 72 | # methAI
Containes python scripts for methAI, version in Zenodo:
[](https://zenodo.org/doi/10.5281/zenodo.11530986)
# Summary
[decisionTreeDimReduction.py](https://github.com/bazyliszek/methAI/blob/main/decisionTreeDimReduction.py) uses a decision tree to classify the da... |
6e8e57aef84d65ec68436c580217205648994d03cf03a360844b68f07b681396 | Text | 6,123 | 150 | 
[](http://bioconda.github.io/recipes/pymochi/README.html)
[](https://doi.org/10.5281/zenodo.14037782)
This is the codebase for the paper [Du, P., Parikh, M.H., Fan, X., Liu, X.Y. and Wang, J.X., 2024. CoNFiLD: Conditional Neural Field Latent Diffusion Model Generating Spatiotemporal Turbulence. arXiv p... |
4df1b741eee4c4278a43a54eaa6760ce63bacb0b98f5c30448c5315327bdcdda | Text | 6,129 | 64 | # deepImageJ Repository for Bridging the Gap: Integrating cutting-edge techniques into Biological Imaging with deepImageJ
This repository contains the necessary codes and scripts to replicate the case studies presented in the article "Bridging the Gap: Integrating cutting-edge techniques into Biological Imaging with d... |
18c156b7fc5963921e0c3cc0cd011d5648d679b72876a693a23d050ce3ccb94d | Text | 6,139 | 187 | # MicroKPNN-MT
Multi-task microbiome-based knowledge-primed neural network
## Dataset
We employed the mBodyMap database, featuring 34,233 preprocessed samples from 56 projects and 25 diseases. The dataset underwent categorization of BMI and age data, yielding insightful patterns for analysis.
## Usage
**Step 1**:... |
be4f0aeb798884406823f741736d9c53179155ffa51909a520b83f426539723a | Text | 6,152 | 150 | <!-- Improved compatibility of back to top link: See: https://github.com/othneildrew/Best-README-Template/pull/73 -->
<a name="readme-top"></a>
<!--
*** Thanks for checking out the Best-README-Template. If you have a suggestion
*** that would make this better, please fork the repo and create a pull request
*** or simpl... |
08767c27e72ad7bfafbbd151fef2e2a2cb76edaec6c69a49ce628b318eaf4253 | Text | 6,161 | 71 | [![CC BY-NC-ND 4.0][cc-by-nc-nd-shield]][cc-by-nc-nd]
[cc-by-nc-nd]: http://creativecommons.org/licenses/by-nc-nd/4.0/
[cc-by-nc-nd-image]: https://licensebuttons.net/l/by-nc-nd/4.0/88x31.png
[cc-by-nc-nd-shield]: https://img.shields.io/badge/License-CC%20BY--NC--ND%204.0-lightgrey.svg
## ADOS Audio Neural Network fo... |
aa2f03b48a6a521142ebec4ade8ebfea6f9aa1b1fdb2bd55686eec3238e5b3ec | Text | 6,209 | 141 | .. image:: /ONT_logo_deprecate.png
:width: 800
We have a new bioinformatic resource that replaces the functionality of this project! See our new repository here: `remora <https://github.com/nanoporetech/remora>`_.
This repository is now unsupported and we do not recommend its use.
Please contact Oxford Nanopore: su... |
3d681552d4e3035d0e95eac452d602e0dedae5129b28620814beafb3504e2c29 | Text | 6,216 | 151 | ## PoachNet: Predict Poaching with an ontology-based knowledge graph
[FOODS](https://naeima.github.io/fooKG/) is a wildlife knowledge graph dataset used for poaching prediction. As shown in the figure below, it was constructed by populating the Forest Observatory Ontology [FOO](https://w3id.org/def/foo#) with RDF wild... |
a7beb16971406c3ae3e9790110ed8ce55760a2a699e05b391c74216ccc2fbf02 | Text | 6,226 | 83 | # M4Raw
M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI research
## Hugging Face release [2026.8.20]
M4Raw Brain v1.6 is also available as an unarchived, file-level dataset on
Hugging Face:
**[huggingface.co/datasets/mylyu/M4Raw_brain](https://huggingface.co/datasets/my... |
1a49fda6c58d8515ce4deedd6ebfcc836d89ea84e19cb33d04eb139162dfbe7c | Text | 6,227 | 179 | [](https://github.com/AspirinCode/GENiPPI)
[](https://doi.org/10.1101/2023.10.10.557742)
# GENiPPI
**Interface-aware molecular generative framework for protein-protein interaction ... |
8a5f37163df560bf85b576030b506a850ea56835406649095a57d7db2ca76fe4 | Text | 6,230 | 144 | ## Predictors and Implications of Myocardial Injury in Intracerebral Hemorrhage
This github repository hosts source code for training an nn-UNet based model for ICH segmentation.
#### Incoming Datastructure
```
jmcginnis@chouffe:/media/raid3/FelixH/ICH_Scans/ICH_nnunet/final_training$ tr... |
33b4896860977d7a5bee19f454c8fa51c03d8570397a414a0cd69ea1166f5888 | Text | 6,232 | 158 | <!-- https://www.markdownguide.org/basic-syntax/ -->
<!-- https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet -->
# LTAMP
Learning for Task and Motion Planning (LTAMP)
<!--https://github.mit.edu/Learning-and-Intelligent-Systems/ltamp_pr2-->
## Overview
Robotic multi-step manipulation planning for a [PR... |
c57723e06685c0e587a05b0aba701689dec70ba64e97ff6ca47ffed3024a06bc | Text | 6,248 | 127 | # MEGIT
Data analysis package for modified elevated gap interaction test (MEGIT)
## Installation
***3.9 <= Python required.***
### Required Packages
- [NumPy](https://numpy.org/) `pip install numpy` *(Basic requirements)*
- [SciPy](https://scipy.org/) `pip install scipy` *(Basic requirements)*
- [OpenC... |
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