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527cbafb966769245a75e23fd444b256e324f311262ee9bb5e57340b9b1e5522 | Text | 298 | 3 | # FCD3 promoter methylation landscape
Code to reproduce the *de novo* network enrichment analysis reported in the article "The specific DNA methylation landscape in Focal Cortical Dysplasia ILAE Type 3D". To run the code, open the notebook `analyses.ipynb` and follow the instructions given there. |
60e8124eddf2492a39f0b3717a78036b1335a11d7bfb98aeeabb63c8a6268b7f | Text | 312 | 7 | Computational study of types of noise and adaptation in binocular rivalry.
- simulation contains the Matlab code to simulate binocular rivalry dynamics.
- data contains the results from the simulation, including supplementary data.
- analysis contains the Python notebooks used to analyze the simulated data. |
cde4e6bff35c164d5a5738cdc6412758e832aa3b2b53ac88f2c3cf6905feaf4f | Text | 316 | 5 | Code for the paper:
Hale, B., Ratnayake, S., Flory, A., Wijeratne, R., Schmidt, C., Robertson, A.E., and Wijeratne, A.J. (2022). Gene regulatory network inference in soybean upon infection by Phytophthora sojae. bioRxiv: 2022.10.19.512983.
Codes for Deep Neural Network (DNN) model:
https://github.com/ajwije/synet |
390f53f3ddb5dbb0147a2f9b423ffff0159a8950e780a2977a5b98c7e89a259c | Text | 337 | 5 | # Neuronal Network with Astrocyte Ensheathment
Code to reproduce the key figures in: G Handy, A Borisyuk. Investigating the ability of astrocytes to drive neural network synchrony. 2023
Matlab/Mex code is also include to run the microscale (aka DiRT model), the non-spatial spiking network model, and the spatial spiki... |
f02d78b350d10ec775eefc9966eb8bdfc2ff8f06cbabca7ae3dc983f22fe1dc0 | Text | 337 | 5 | # multimodal
R code to integrate with deformetrica (http://www.deformetrica.org/) using PLS from mixomics (http://mixomics.org/) to integrate clinical, structural, and diffusion data.
Used in the manuscript: Structural Thalamocortical Network Atrophy in Sporadic Behavioural Variant Frontotemporal Dementia (link to pu... |
ec06ceae85c243ab554b6b470a99865ba73d61384c99602e66e194746b580a58 | Text | 358 | 8 | ## Content:
This code is developed for the paper "Imaging brain tissue architecture across millimeter to nanometer scales"
The repository consists of 2 parts, which provide analysis of coCATS and rCATS data.
1) [coCATS analysis](./cocats_image-analysis/)
2) [rCATS analysis](./rcats_image-analysis/)
More detailed ins... |
b463f248373ab7a2568c6746c37b10f7bca5eb7d504fbefdc7785346bab78337 | Text | 369 | 7 | # Maximally-Error-Tolerant-Mesh-ONNs
Code that trains and tests maximally error tolerant Mach-Zehnder mesh optical neural networks
All the trained model parameters are available at the following Google Drive link:
https://drive.google.com/drive/folders/10S3Zzk8f39zIHAX6b5nfQA_xuI-vXpZo?usp=share_link
Instructions on... |
bfc6183eee7308e79b02c8b330820afb982a50560ccaed8feb382abc6dcf1c53 | Text | 384 | 7 | # Neuralparacet R Scripts
051222: added RNA-seq, DNAm and integration scripts. <br />
ArchR(Corces et al,2020) Pipeline script for analyzing Single Cell RNAseq analysis.<br />
P2Glinks for D20 Ctrl , D20.P100 and D20.P200 for single cell ATAC seq analysis. <br />
Single Cell RNAseq analysis for HESC Neuronal differe... |
b75c78645962a65defe1a14305c16e61f3b54f84d980c9fdf71ac173569dd168 | Text | 414 | 3 | # Pyramidal
Whole hippocampi were obtained surgically as from individual mice treated with EPO and Placebo controls. We did stick to the standard parameters of sample preparation for single nuclei sequencing.
Single nuclei libraries were constructed using the Chromium Single Cell 3’Reagent Kits (v6) according to manufa... |
1530c2df9d7493945f38595664736cb71844038be892de22dc50ade28f03f031 | Text | 425 | 7 | # Rehabilitation_of_auditory_cortex
Reproduces the modeling figures (Fig 3, Fig 7 and SFig 5) for Kumar et al., 2023: "Cell-type-specific roles of inhibitory interneurons in the rehabilitation of auditory cortex after peripheral damage"
bioRxiv link: https://www.biorxiv.org/content/10.1101/2022.09.15.508128v1
simAn... |
9d241a283d0ca7b91ff792e10eb9a4739ac50906b0bf0f4302ff6dee4fbd6abb | Text | 433 | 5 | # Source code: Usefulness of Heatmap Explanations for ECG Analysis
This repository provides the source code for replicating the experiments described in "Usefulness of Heatmap Explanations for Deep Learning-Based Electrocardiogram (ECG) Analysis"
The ECG dataset is available on Physionet.
For the pretrained weights of... |
852233815306a810a39bc6c723b326ebb06532b8b73205f6dbc7bf6f7ddb8fbc | Text | 435 | 10 | visual_coding_2p_analysis
===============================
https://github.com/AllenInstitute/visual_coding_2p_analysis
Visual Coding 2P analysis code
Level of Support
===============================
We are not currently supporting this code, but simply releasing it to the community AS IS but are not able to provide a... |
32226e73b0ad139325a17c00c174801120405bbb7ad2f41b93d59d1891ea7245 | Text | 437 | 8 | # sensimetrics_filter
code for filtering WAV files using filters supplied by Sensimetrics.
`load.py` contains the function `load_filter()`, which reproduces exactly the output from the `load_filter` MATLAB function supplied by Sensimetrics.
`apply_filter.py` contains the function `filter_wavfile()`, which applies fil... |
2ffdf97d9153c5470684bcedc61af4c72fe091ddf19a5e3ef799689a85c358e8 | Text | 449 | 14 | # Interpretable-NN-for-IBD-diagnosis
This is a repository for Interpretable NN for IBD diagnosis project, torch captum is employed to interpret attributions of various level of diagnosis factors
## Training classification model
- run.sh
1. train CNN model
2. finetune pretrained language model
- train.py: train CNN mo... |
1692009bea4e38e5d25a6dfa0abec52556b94be2541fb773ddce43fec5fbbc8b | Text | 465 | 4 | # Automatic-MSI-Spectra-Extraction
MSI-Parser is a program produced by the Lingjun Li Lab at the University of Wisconsin-Madison for defining regions of interest (ROI) for single cell mass spectrometry analysis, followed by average spectra extraction. A quick start manual is included in the repository. Please forward ... |
f40fc3738131cccf20bac7948b5c3c94fbfeb18c6bc1bfdc4c223de8c54dbb22 | Text | 498 | 11 | VideoCapture App
================
The VideoCapture app is a Mac app that is meant to interface with the existing
[FinchScope](https://github.com/WALIII/FinchScope/) project in order to
do realtime recording and processing of video and audio from the orthophysiology rig.
The project interfaces with the Finchscope in ... |
52b754600587185a8fa3d5d0cbd42ef6f668e7244d78f08de5a10739f367bc7e | Text | 522 | 10 | # Rehabilitation_of_auditory_cortex
Reproduces the modeling figures (Fig 3, Fig 7 and SFig 5) for Kumar et al., 2023: "Cell-type-specific roles of inhibitory interneurons in the rehabilitation of auditory cortex after peripheral damage"
bioRxiv link: https://www.biorxiv.org/content/10.1101/2022.09.15.508128v1
simAn... |
ce74dd051cf0e4e018617324e102790dcc272ba70d391183b73c07c28030d9b5 | Text | 566 | 7 | Scripts to run simulations with the model described in "An in silico and in vitro human neuronal network model reveal cellular mechanisms beyond NaV1.1 underlying Dravet Syndrome."
Consists of:
- Analysis_MATLAB: contains the scripts used for the analysis of both simulated and experimental data to compute network bu... |
4b8d74248123cb5c657f91f9af3e56eea0ca8f2cb23d6e578ffcb726a0ddb8c6 | Text | 571 | 10 | # BTSP-Based-Learning
Code repository of the article: Rapid memory encoding in a recurrent network model with behavioral time scale synaptic plasticity
BioRxiv link: https://www.biorxiv.org/content/10.1101/2023.05.02.539020v1
Folders:
- Figure_code: codes to generate figures in the article.
- Figure: contains... |
9926cad48d7f0508640612a5a1613fbc91eabbccea72f73dab063ed02a44f8b4 | Text | 637 | 8 | [](https://doi.org/10.5281/zenodo.18774578)
This repository contains the code for the analysis of RNA-sequencing data from [Duncan et al. - "Sex differences in pituitary corticotroph excitability" - Front. Physiol., 2023](https://www.frontiersin.org/journals/physiology/art... |
42163791b4c3caea3e8a8e4a3e676c31ce91f65beb0512bac709b2002d108653 | Text | 678 | 12 | # expressionML
### Expression_Matrix.RData
* rawdata
* bc_rpkm_tmm_log2_data: normalized expression matrix after batch correction
* metainfo: metadata corresponding to batch correction
* exclude: excluded samples in this study
**Thank you for your interest in our work**
**If you use data, please cite:**
Liu, W., Zh... |
bc7ee04c446d6ec7d2e3813ecbfba28edbe6b47f474c0a4130c33242d6686a41 | Text | 679 | 5 | ### Unsupervised Anomaly Detection in Neonates
This repository contains code associated with out publication entitled "Unsupervised Abnormality Detection in Neonatal MRI Brain Scans Using Deep Learning" - Jad Dino Raad, Ratna Babu Chinnam, Suzan Arslanturk, Sidhartha Tan, Jeong-Won Jeong, and Swati Mody (currently und... |
7196e7b6f9053939bcead47c3913ab633cf4d0c7746daf6034b69d3a1c429bc4 | Text | 680 | 7 | # Anterograde_heatmap
Code snippet written in R allows to perform hierarchical clustering of the attached dataset and built the heatmap.
Code reproduces Figure 1 from the article "Somatostatin-expressing neurons in the ventral tegmental area innervate specific forebrain regions and are involved in the stress response" ... |
89da75cb29ce596a39a7d266612b6d79069006dbadfb45e59d1dd1f9cb884c4b | Text | 731 | 16 | # Learning the local landscape of protein structures with convolutional neural networks
## This repository contains trained CNN models, code, analysis and processed data.
output/ - processed alignment data
analysis/figures/ - contains all plots and figures
src/ - R and python scripts for data processing
neural_net... |
0f0fe30d4c17272f9c3f982130fe4d6f129e1375563c0c8aaa86c0ce17bf33a2 | Text | 743 | 15 | # MIBI analysis
Scripts for MIBI analysis
## Description of the scripts: <br>
* Script# 1: Converts single-channel TIFs to pixel x marker matrices
* Script# 2: Performs pixel clustering using FlowSOM and makes cluster heatmaps
* Script# 3: Saves pseudocolored overlays of MIBI images colored by pixel cluster number
* ... |
5c44c3278b2364e4572aa690384893447d8102adcb38dd2be432613b23fdce7b | Text | 772 | 12 | # Variance Component Analysis
Code for and examples of partitioning variance in aesthetic ratings using
Variance Component Analysis (VCA).
## 01_VCA
It contains functions and example scripts to calculate the amount of variance ia a given trait of interest (e.g., beauty) that is shared across and/or unique to individ... |
bbd6175e2c0b2e6896a31937b56b06a270549142b5a35b7cd8f17b2f630e4a24 | Text | 782 | 20 | Local Cell-Specific Network (locCSN)
=============================================
`locCSN` is a package for estimating gene co-expression networks for each cell from single-cell datasets.
How to cite `locCSN`
-------------------
This work has been published in [PNAS](h... |
1248326a53ff39b18526c8a9d0a3122eed0d1fcb8e879533d33113b3db3ac711 | Text | 795 | 23 | # M-Current-modulation-of-cortical-slow-oscillations
This repository is part of the paper: M-current modulation of cortical slow oscillations: network dynamics and computational modelling, by Leonardo Dalla Porta, Almudena Barbero-Castillo, Jose Manuel Sanchez-Sanchez, and Maria V. Sanchez-Vives.
Plos Computational B... |
cc1cba0e06b2504e8297af91c068b87285fb9968f91e7f20a6818605eab204a4 | Text | 797 | 22 | # 3D printed pacifier-shaped mouthpiece for fMRI-compatible gustometers
The repository contains all scripts needed to reproduce the results reported in the above study.
# Code
The code is split in three main folders
* ./mouth_piece -3D printing files (stl) including seven versions with a diameter of 2.5 mm ± 0.3 ... |
679a02118dd95fd1d49f0fd213e13f65886412150924c8380e600a3f0a00bf23 | Text | 801 | 20 | Code for the paper [A probabilistic digital twin for leak localization in water distribution networks using generative deep learning](https://www.mdpi.com/1424-8220/23/13/6179)
.
Reference for citing the work:
*Mücke, Nikolaj T., et al. "A probabilistic digital twin for leak localization in water distribution network... |
06d07151dcb9d2ed921c5d6d1879b521f33e329e5c3962f3b83f9fb07c2112d4 | Text | 805 | 15 | # PD_one_over_f
This repository contains scripts for the estimation of MEG 1/f-exponent's dynamics in Parkinson's disease patients and healthy controls presented in the manuscript:
Helson, P., Lundqvist, D., Svenningsson, P., Vinding, M. C. & Kumar, A. (2022). Cortex-wide topography of 1/f-exponent in Parkinson’s dise... |
41c6d489b86b8088d0c6169e5302bbde8c1d91e42c34efbb9eb869dae81502e4 | Text | 812 | 13 | # Mitochondrial morphology governs ATP production rate
[DOI:/10.1085/ jgp.202213263](https://doi:/10.1085/jgp.202213263)
Welcome to the repository of the manuscript "Mitochondrial morphology governs ATP production rate". This repository contains all the code generated for this publication, for the analysis and figures... |
acd2ce816b2a5ab0a6ad0f24c2c117229fa73556a27652616262c4aa346c46db | Text | 831 | 16 | This code is assembled from different toolkits. We just provide a code in our pratical use.
Please reference to orginal code.
read_surf.m is from DPABI_V7.0_230110 (http://rfmri.org/dpabi)
read_annotation.m is from ENIGMA Toolbox (https://enigma-toolbox.readthedocs.io/en/latest/pages/01.install/index.html)
rotate_... |
1374c1bd35a58d40d6a431b5d95afaf218b75b27365711d28a970c6394813df8 | Text | 891 | 18 | # RNAForecaster.jl - Estimating Future Expression States on Short Time Scales
RNAForecaster is based on a neural network that is trained using ordinary differential equations solvers (neural ODEs). See https://arxiv.org/abs/1806.07366
for details on neural ODEs. The goal of this method is to forecast future expression... |
5c0eb599f1d9705ab39bb6e7e3b4ca066c9bfb9c5cf3132164aca28834148458 | Text | 894 | 8 | # MT_Angle2Ablation_Workflow
Set of ImageJ and python scripts for the analysis of cortical microtubules timelapse reorientation relative to an ablation site.
To get started, see the [installation procedure](https://github.com/VergerLab/MT_Angle2Ablation_Workflow/blob/master/Installation_procedure.md), [user guide](htt... |
7dd59829b3d55d451c09c5c797c453e227fdb08649223719bd66e2e02dbf203a | Text | 921 | 24 | # Articulatory Settings in Electrocorticography
Code for electrocorticography (ECoG) data pre-processing and signal analysis written for Easthope et al. [_"Cortical control of posture in fine motor skills: evidence from inter-utterance rest position"_](https://doi.org/10.3389/fnhum.2023.1139569) (2023).
 Download (clone) repository
2) Generate tiled XML:
Use MibiWriteTilingXmlCenterRect.m
The script generates a tiled XML file from the default MIBI 1 point setup XML (input XML file). Provide desired number of
rows, col... |
1679a12f087d609277fdae4df2cefc05ecc07429b536abd6d64e0bf9436b7659 | Text | 946 | 13 | # abcd_protocols
Documentation of the scan protocols used to collect the ABCD data.
This files were provided by Joshua Kuperman on December 18th 2018. We provide them here for the community's reference, but NIH FMRIF is not accociated with the ABCD study. With regard to future imaging studies, it should be noted that... |
691bdf6a5af8a489cb9f58b0f955bc55def151ba1fb5a2cb9403d5291befae49 | Text | 962 | 19 | # CS-CORE_python
Python package for `CS-CORE`, a statistical method for cell-type-specific co-expression inference from single cell RNA-sequencing data
## Installation
`CS-CORE` is available on GitHub. You can install it using
```
pip install git+https://github.com/ChangSuBiostats/CS-CORE_python.git
```
## Vignette
... |
fcb68b48e50819689520cdb578ed0bc82c1f5ccbd6dc234c3f1526aa543eb550 | Text | 977 | 22 | # ECG-ASD
AI model to detect ASD from ECG
# Environment
- tensorflow 2.4.1
- numpy 1.19.2
- pandas 1.4.3
# Requirements
Put the input file in the same directory as EFcode_0622.py as numpy array.
The input should be formated as a 3d numpy array with shape 2500,12,1 (time,induction,1).
The ECG should be in 250 Hz reco... |
0415d4ea476b0f146be8488637945acb33884166b8b4b0a7b70beec6c0380c3b | Text | 981 | 23 | ## About
PyTorch code for our paper: **Fooling Examples: Another Intriguing Property of Neural Networks**.
<br> Ming Zhang, Yongkang Chen, Cheng Qian.
### Requirements
torch>=1.7.0; torchvision>=0.8.1; tqdm>=4.31.1; pillow>=7.0.0; matplotlib>=3.2.2; numpy>=1.18.1;
### Dataset
The 1000 images from the NIPS 2017 Ima... |
8d65ff8eefa3d7b125f0f5a9fb6f1818cedbffac066ae6cf074215d67b99be9c | Text | 1,014 | 20 | # RNAForecaster.jl - Estimating Future Expression States on Short Time Scales
RNAForecaster is based on a neural network that is trained using ordinary differential equations solvers (neural ODEs). See https://arxiv.org/abs/1806.07366
for details on neural ODEs. The goal of this method is to forecast future expression... |
48edb24b30fa0cafc2b1f03fa749a39fe98c557495abc5eaf1b81b7afd180be0 | Text | 1,020 | 24 | # Anchoring_analysis
Anchoring analysis code and sample data accompanying the ExPRESSO paper
### 1. System requirements
The MATLAB info is as follows: R2020a Update 5 (9.8.0.1451342) Platform: 64-bit (win64) August 6, 2020, running under Windows 10 Home version 21H1
This "Anchoring_Analysis_cellRatio.m" MATLAB scri... |
bb9ac492ca76fb2b3188f30145b62e78db9e98ef476db345e3f09867eaf6d6da | Text | 1,053 | 16 | # OPMEGfeedback
Analysis scripts to reproduce the figures from *Real-time, model-based magnetic field correction for moving, wearable MEG*.
## Dependencies
- OPM: https://github.com/tierneytim/OPM (although need version of spm_opm_epoch_trigger from https://github.com/stephaniemellor/OPM). Version must be from before... |
95815e8630f63bf9300606bf9cf5b351c5518f76ef23a998806a2445059ac081 | Text | 1,069 | 12 | # LeleNet
This repo was set up to share code for semantic segmentation in the LELE project as described in "Testing the suitability of consumer-grade UAV imagery for semantic segmentation of savanna vegetation"<sup>1</sup>.
Requirements are—amongst others—installation of:
* [TensorFlow](https://www.tensorflow.org/) (CN... |
81d435bf83adb33ad6f2df2bc88679297bee86185669daf31160a3cec26e14e4 | Text | 1,083 | 13 | Artificial intelligence to detect coronary artery tortuosity through
coronary angiography
=========================================
**Author:** [Miriam Cobo](https://github.com/MiriamCobo) (CSIC)
**Description:** This work provides a tool to detect coronary artery tortuosity in coronary angiography.
**Acknowledgemen... |
2e985f3095a8abb753683b13c5ea7d35953eba9919d021f034c428cdb67c92b9 | Text | 1,096 | 22 | # Deep quantum neural networks equipped with backpropagation on a superconducting processor
In our work [Deep quantum neural networks equipped with backpropagation on a superconducting processor](https://arxiv.org/abs/2212.02521), we experimentally demonstrate the training of deep quantum neural networks for several ... |
c6c29eb846197641314befb727946dc0303c69e3c7b698fe706b9e6ba0b0e618 | Text | 1,097 | 23 | RELION 5.1.1
============
RELION (for REgularised LIkelihood OptimisatioN) is a stand-alone computer
program for Maximum A Posteriori refinement of (multiple) 3D reconstructions
or 2D class averages in cryo-electron microscopy. It is developed in the
research group of Sjors Scheres at the MRC Laboratory of Molecular B... |
d87d22ad31a653c578bccd4a97f3fc9cc17779d1e302e571ce96f068c5393b51 | Text | 1,102 | 25 | # VisualFlickerVoltageImaging
This repository contains scripts that plot the figure 1B and 1C for manuscript ""Brain rhythms control microglial response and cytokine expression via NFκB signaling".
## General information:
### animals
6 EMX1-Cre mice were used for the experiments. These mice expressed JEDI-1P-Kv and m... |
2cb8a8d3108f39cb9d810b80d84877ede0e58bfe9a899e5fbe43a4370fc7942a | Text | 1,114 | 28 | # Cardiac T1 and T2 Mapping Segmentation
Source code for our paper "*Automated T1 and T2 mapping segmentation on cardiovascular magnetic resonance imaging using deep learning*".
### Setup Docker Container
For accessing the container by directly connecting to it via ssh:
1. Create a keypair, copy the public key to the... |
f0ab4af28dffe8124351c3a8a7b63467b579711bfc59cb86a886b45a4aed7ada | Text | 1,131 | 16 | # BMTK-Loihi Datasets
This dataset lists the different parameter sets and stimulus sets used in the validation of Loihi implementations of LIF models based on BMTK (Brain Modeling ToolKit) simulations, including :
- LIF model parameters for excitatory and inhibitory neurons based on the data from Allen Brain Atlas (htt... |
220f2ca244a11fd6f6bbe8f16bec72046a9d04c69420b9f56d88e931e81a864b | Text | 1,134 | 52 | # GO_NN
## Description
* Gene Ontology informed neural network model formicrobe functionality discovery in human diseases.
## Environments
* python 2.7, check environments.yml for needed packages
## Installation
1. Clone the repository
```sh
git clone https://github.com/YunjieLiu-HGC/GO_NN.git
```
2. Creat... |
9822a70c442917f6635de13971945a5dbaa532d8b0e086dad7eb61bc6b919d80 | Text | 1,163 | 32 | ## APDB: a database on air pollutants characterization and similarity prediction
**APDB** is a publicly available online database which improves our knowledge of the existing pollutant molecules, providing an in-depth insight into their physicochemical, structural and quantum properties. The collection of pollutant m... |
911d51465c7030fc6144a32d2c817597c47f44c1f33687c18bc6cc30330a5c5a | Text | 1,172 | 35 | # Evaluating the Use of GNNs and Transfer Learning for Oral Bioavailability Prediction
> 
This repository consists of 2 folders and 4 python scripts:
1. data folder
1. graph_data: csv files of solubility... |
b1b64352a2739b32fb576406253d83644a6ad8b56bd48db2576002e566c5b4b3 | Text | 1,184 | 25 | # CEEMDAN
A MATLAB package for CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise).
The current is an improved version, introduced in:
[1] Colominas MA, Schlotthauer G, Torres ME. "Improve complete ensemble EMD: A suitable tool for biomedical signal processing"
Biomedical Signal Proce... |
6e4cac5ff850210181c338ee625182c978d057809f6f20028cfc874e83a08df0 | Text | 1,203 | 21 |
# Mini-BacRefSeq dataset
The Mini-BacRefSeq is comprised of 1,506 complete genomes (Supplementary Table 2), including 707 pathogenic bacterial strains (540 species, including animal, human, and plant pathogens) and 799 nonpathogenic bacterial strains (687 species).
The file name of the frequency features extracte... |
388e32087ab1df6d90f468e795e4bc27773fd742cc2d2665831c9bfe698eed35 | Text | 1,239 | 16 | # Functional and microstructural plasticity following social and interoceptive mental training
Hello, please find here the code and some meta-analytical maps used for the study currently in biorxiv:
https://www.biorxiv.org/content/10.1101/2020.11.11.377895v7
All code of analyses is included.
We made gradients using... |
7f3b51a9c2fdb73c2adff95cb2d3c9c622d64aaa12260b774b30b0684002afe9 | Text | 1,286 | 15 | COCO API - http://cocodataset.org/
COCO is a large image dataset designed for object detection, segmentation, person keypoints detection, stuff segmentation, and caption generation. This package provides Matlab, Python, and Lua APIs that assists in loading, parsing, and visualizing the annotations in COCO. Please visi... |
18ea7f6e19ce91bae9085c87ab5ac6e7ef7033ba56743c04d5cc2c640052854f | Text | 1,288 | 14 | # Intrinsic-Signal-Imaging
Code & Apps for Running and analyzing intrinsic signal imaging experiments
* * This repository is under construction. More coming soon! * *
*For users setting up IOSI, start with the 'IOSI_RingLED_IlluminationBuild.docx' document to get your illumination set up. This can then be control... |
781dbcb9a7b767279193628b370802648f8dac8508ca0ea4390fa67298042201 | Text | 1,372 | 4 | # spinDrop
This is the repository for the publication: De Jonghe, Kaminski et al. spinDrop: a modular droplet microfluidic platform to maximise single-cell RNA sequencing information content (2022)
Droplet microfluidic methods have massively increased the throughput of single-cell RNA sequencing campaigns. The benefit... |
09ebe10429e9cedb4c6e2f415b31548add679524565592656084eb8be8725e72 | Text | 1,377 | 25 | # Causal evidence for frontal cortex organization for perceptual decision making
Data and code for paper titled "Causal evidence for frontal cortex organization for perceptual decision making", accepted for publication at PNAS.
Most of the analyses are written in MATLAB. Here is a guideline to the files:
MAIN TMS AN... |
9b7b1d461284069ce30c0790aae03b5a077d317d657fb43ba61e0e415ac13312 | Text | 1,377 | 28 | # GattacaNet2
Predictive Genomics leveraging Multi-Task learning and LINA
## Requirements
* Python 3.6
* Tensoflow v2.6.2
* pandas_plink v2.2.9
* pandas v1.4.2
* numpy v1.19.5
* scikit-learn v1.1.0
## How to use it
This github contains the base code to run our experimentations. Each modu... |
f920c00f106027512f8453dcb9aa83e474653d1f8c2bdbf369029c13c7736f5d | Text | 1,378 | 24 | # Neuropixels Platform Paper
<img src="icon.png" width="400">
This repository contains code for generating the figures in the pre-print describing the scientific findings from the Allen Institute's [Neuropixels data collection platform](https://portal.brain-map.org/explore/circuits/visual-coding-neuropixels).
Most o... |
5e6cbde3f442b11e44cf875af9e8054c657076b8c564d060ecb64b637a10851a | Text | 1,384 | 35 | # Train CIFAR10 with PyTorch
I'm playing with [PyTorch](http://pytorch.org/) on the CIFAR10 dataset.
## Prerequisites
- Python 3.6+
- PyTorch 1.0+
## Training
```
# Start training with:
python main.py
# You can manually resume the training with:
python main.py --resume --lr=0.01
```
## Accuracy
| Model ... |
ad675e8a19642c2ca98d3ebec515b7221021c56777f87b597c89d653714963be | Text | 1,393 | 22 | # Multi-Graph Convolutional Neural Networks
The code contained in this repository represents a TensorFlow implementation of the Recurrent Muli-Graph Convolutional Neural Network depicted in:
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks (in Proc. NIPS, 2017)<br>
Federico Monti, Michael M. Bron... |
3124a91ad218c030d54020fcf80b03e2b6f0f1eee47ffdac7916c94a2eea44da | Text | 1,397 | 49 | # Similarity based pairing for Siamese Neural Network
This repository corresponds to the article'Siamese Neural Networks for Regression: Similarity-Based Pairing and Uncertainty Quantification'. The project consists of 4 models: Multilayer p... |
58d5fdb3cd9d6b510414d40b3e78c35402702b9d4e02897a183a29a89fd13587 | Text | 1,424 | 44 | # TraBS - Transformer Breast Segmentation
Segmentation of fibroglandular tissue in breast MRI with neural networks
Paper
=======
ArXiv: [**Fibroglandular Tissue Segmentation in Breast MRI using Vision Transformers - A multi-institutional evaluation**](https://doi.org/10.48550/arXiv.2304.08972)
![](data/figures/Fig_2... |
eb8ea54117d1e920a9f1eb0753ac7d77833cca8b1db303b0bb0dd8598d8362fe | Text | 1,438 | 14 | # Cholinergic biasing of claustral networks
Investigating the effects of opposing cholinergic gain control in a network model of the claustrum
### Aditya Nair, Martin Graf, Yue Yang Teo, George Augustine<sup><a href="#fn1" id="ref1">1</a></sup>
Cholinergic modulation has long been thought to alter the signal-to-nois... |
01674e5ef04a95919e547dc663e538e8450d4a6976cd4f0f5b08c03a6fa22d1a | Text | 1,521 | 26 | # NeuriteNet
NeuriteNet is a machine learning platform developed to identify differences in control and experimental groups of cultured neurons based on morphological criteria
This repository has the python code for training and running the NeuriteNet model as well as additional tools for deep learning interpretabilit... |
00cebd2b40d017ebc3167c2c3a24030e9c3fc9740c5e2af7a929238c19eaa2c4 | Text | 1,522 | 15 | NeuroDevSim
----------------
**NeuroDevSim** is a Neural Development Simulator for Linux of MacOS environments. It is a parallel and phenomenological computational framework to grow large numbers of neuronal morphologies (and resultant microcircuits) simultaneously according to growth-rules expressed in terms of ... |
a293c675c0d4b3ffb550dd0ba430234e184e4591ff96939ab22c42200a443c79 | Text | 1,568 | 30 | # Framework for predictive modelling on tabular datasets with xAI
This repository contains the implementation and evaluation of traditional (GLM, Lasso and Elastic Net) and non-traditional (Tree Boosting, SVM, Naive Bayes and Multilayer Perceptron) machine learning algorithms for classification.
Additionally, for eac... |
9ee7d0cb3d360673569256ddd4944f2f3b48172c0a9f8af13879f7ceccec59c3 | Text | 1,570 | 27 | # KISN-pancortical-kinematics
### Data analyses for e-phys and 3D tracking experiments
---------------------------------------------------------------------------------
Code used to generate findings presented in "Behavioral decomposition reveals rich encoding structure employed across neocortex" ([bioRxiv](https://www... |
6720455d5abee5a13dcf17beb58362ed095acddca38869575055a859969936b4 | Text | 1,601 | 37 | # ANIMA
> [!WARNING]
> This repo was moved to Github at <https://github.com/rpcarvs/anima>
ANIMA (AdvaNced artificial Intelligence for Materials reseArch) is a machine learning code developed to work with Quantum Mechanics and Materials Science. For now, the main goal is related to energy materials and organic elec... |
3c998ca400c0ae40ed4e611aae38230cd25d27d78058f195690a2b8b67c4a766 | Text | 1,659 | 46 | # imctools
# Reproschema Python library and Command Line Interface (CLI)
The `reproschema-py` library provides a Python interface and a command-line tool to work with ReproSchema, a YAML-based framework for creating and managin... |
ef0da2b0a89a8a82e9451f637e483f6cbf52c3765de752e07ad58d854588065f | Text | 1,693 | 57 | # etspredict
Using edge time series to estimate FC at different levels of co-fluctuation for individual-level predictions
# Set up environment
This project uses julearn for machine-learning and cross-validation. It is a
library built on top of scikit-learn, and built with specific neuroscientific
challenges such as ... |
6a1dd14d26edd5b9c883c0acd26c217508563c60fb259995c6fd472f3b683ff1 | Text | 1,711 | 38 | # rfspec-db
Synthetic Radio Frequency Spectrum Snapshots Database for RFML
This database contains 391 {**Y**, **W**} pairs of images, where Y is radio spectrogram containing signals and W is noise distribution.
Database was created with randomly selected:
* FFT sizes from set `{1024, 2048, 4096, 8192}`
* Time resolut... |
ebd633d6c7191614b3a0d5207d664ab0b100e0e3757018aae8c6f0fcf6444322 | Text | 1,716 | 28 | # Lifespan_MEG
Analysis of age effects on MEG-derived markers and cortical thickness in an adult lifespan sample
Reference: Stier, C., Braun, C., & Focke, N. K. (2023). Adult lifespan trajectories of neuromagnetic signals and interrelations with cortical thickness. NeuroImage, 278, 120275.
https://doi.org/10.1016/j.... |
59e0f675ee2d88bd0dbb6206e9b92d414a880b93108875b036620305afa32a4d | Text | 1,784 | 42 | # Intervene #
**An interactive Shiny App for UpSet plots, Venn diagrams and Pairwise heatmaps**
Intervene Shiny App provides an interactive interface for intersection and effective visualization of gene or genomic region sets. Currently, Shiny app does not acccept genomic regions as input, but the text files generate... |
30c372ecd80e2aa597ecd6d111e8ce3d1381c996f698022216068ab57e3dada5 | Text | 1,813 | 36 | # solubility
An implementation of Delaney's ESOL method using the RDKit
```
ESOL: Estimating Aqueous Solubility Directly from Molecular Structure
John S. Delaney, J. Chem. Inf. Comput. Sci., 2004, 44, 1000 - 1005
https://pubs.acs.org/doi/abs/10.1021/ci034243x
```
There are 4 scripts in this repo.
* esol.py - has ... |
e8de35ea316da1a2937296a7c29d6fbcc888f924749500aaca436c5568011eac | Text | 1,832 | 28 | # scover
This GitHub repository contains the neural network tool **scover** associated with a publication: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-03021-9.
<img src="https://github.com/jacobhepkema/scover/raw/master/scover_logo.png" width=300 align=right>
__Q__: What is this?
__A__: __... |
c8704c311d43e52560660f1103676067d2ce6fd02766e06318468aac3034b8e5 | Text | 1,841 | 37 | # A-tradeoff-between-acoustic-and-linguistic-feature-encoding-
Codes used in the paper "A tradeoff between acoustic and linguistic feature encoding in spoken language comprehension"
eLife2023;12:e82386 DOI: https://doi.org/10.7554/eLife.82386
- Generate .csv files that contains word and phoneme onsets of stories
1) Ru... |
cd7f89683bf834cc472899ec671a1cd3e38c2232c0946a9494515987d9860e34 | Text | 1,856 | 20 | # PiecewiseDeterministicMarkovProcesses.jl
| **Documentation** | **Build Status** |
|:-------------------------------------------------------------------------------:|:---------... |
3b64973daf344222a821b1f1815986a468154e5e0ac1db1e5c48f69185594428 | Text | 1,885 | 32 | # Conv-ViT-A-Convolution-and-Vision-Transformer-Based-Hybrid-Feature-Extraction-Method
This project implements Conv-ViT, a hybrid deep learning architecture combining convolutional neural networks (CNNs) and Vision Transformers (ViTs) for effective retinal disease classification using Optical Coherence Tomography (OCT... |
9604009e628901621027989f285808b1a18646c1ede04387d53eb489be9f7e2c | Text | 1,896 | 4 | # AI-Driven Respiratory Distress Syndrome Prediction for Very Low Birth Weight Infants: Korean Multicenter Prospective Cohort
***Abstract***
Respiratory distress syndrome (RDS) is a disease that commonly affects premature infants whose lungs are not fully developed. It results from a lack of surfactant in the lungs... |
a525ded67c8abe37bbbde4a97c0024213ff7c52bc72db40e96149563a6a83b24 | Text | 1,904 | 20 | # Deciphering protein secretion from the brain to cerebrospinal fluid for biomarker discovery
### Katharina Waury, Renske de Wit, Inge M.W. Verberk, Charlotte E. Teunissen and Sanne Abeln
We have collected discovery proteomics studies based on untargeted mass spectrometry of healthy cerebrospinal fluid (CSF). The cura... |
ee32e09a0513c1bcc5df56da040193b8f9ad4c4e2527e34c9f87577071d5c41b | Text | 1,949 | 37 | <img src=https://user-images.githubusercontent.com/35853195/42889397-52f9c75e-8a78-11e8-9da8-86ccc3a30a80.png align="right" hight=120 width=120/>
MMVT-Lite is a lite version of our multimodal analysis and visualization platform (MMVT) that implements a small section of MMVT related to labeling invasive electrodes.
Plea... |
b2b50071a869fe604afa545ebc3e852cdc65f8f57d3bc43be06274688e70f868 | Text | 1,965 | 3 | # NACA
Synaptic connections in the brain are known to be locally modulated by neural activity via many forms of synaptic plasticity, including long-term synaptic potentiation and depression associated with spike timing-dependent plasticity1 (STDP). Neuromodulators in the brain also act globally at many synapses to m... |
6efa85619630975e3e39d20e72a191d06a7dd05860b29cb3a55cf51488842aa4 | Text | 1,978 | 39 | # KISN-pancortical-kinematics
### Data analyses for e-phys and 3D tracking experiments
---------------------------------------------------------------------------------
Code used to generate findings presented in "Behavioral decomposition reveals rich encoding structure employed across neocortex" ([bioRxiv](https://www... |
7262ddb0945cf455e75af8894085f3287d7edd97e379acc80a03c87a889b72a1 | Text | 1,985 | 40 | # CS-CORE
[](https://github.com/ChangSuBiostats/CS-CORE/actions/workflows/R-CMD-check.yaml)
[ equivariant graph neural networks for robust and accurate protein–protein interaction site prediction
by Rahmatullah Roche, Bernard Moussad, Md Hossain Shuvo, Debswapna Bhattacharya
published in [PLOS Computational Biology](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011435)
Codeba... |
4e1aac587588da4284facd7ea9086a545c863e65dc14f406bf8122500abaed5a | Text | 2,052 | 36 | ====================================================
Data files
====================================================
(1) 'rr.mat'
It contains neural activity data around ME (megazine entry) and MX (Megazine exit) from all mice that underwent RR training. The middle latter '0' or 'z' refers to normalization by div... |
dfd1739f607d3eefb69da2f674b70d29e09af87727429bb7d16d394d49663407 | Text | 2,076 | 53 | # fwhm_on_spots
## Full-width-half-maximum of 2D spots
This jython-fiji macro computes the FWHM on bright spots on dark background by,
first, finding all maxima in an image (using fiji `Find Maxima`) and second, iterating
over all 2D peak locations. For each peak the horizontal, vertical and two diagonal line intensi... |
4d1ab9257fbe064fe3cb6ce577efdf945a76c25fda8053caa8070797902d0fff | Text | 2,093 | 70 | ### PathFrame is a flexible and scalable deep-learning framework to build segmentation model on large scale pathological images.
****
### Environment
python2.7
pip install -r requirements.txt
### Configuration
NetFame uses a configuration file of yaml to set up all the parameters.
|Argument |Comment |Example|
|... |
d631dcbd8889fbce9bfd0859f64868eda1c51c0d068ec45b65ae1b1a07969ef7 | Text | 2,107 | 21 | # A Comprehensive Analysis of Mathematical Models and Applications
This repository discusses Spiking Neural Networks (SNNs) and their mathematical models, which simulate the behavior of neurons through the generation of spikes. These models are used to improve the accuracy of the network's outputs and have potential ... |
bfe20b118006fc4a915e809d33a9af2ad79707935fb88a17042030926858d233 | Text | 2,128 | 48 | # neuroCNVscore
The neuroCNVscore is developed to quantitatively prioritize the deleterious, functional and pathogenic CNVs in neurodevelopmental diseases at a genome wide basis. The core algorithm of neuroCNVscore is XGBoost. NeuroCNVscore outperformed a state-of-art tool in independent datasets. If you find neuroCNVs... |
3110234526d2462254a3b411d85767c9f02bab32c616d15ac9d14e3c50167219 | Text | 2,134 | 35 | # Pelvic PET/MR attenuation correction in the image space using deep learning
A novel approach of adding bone information to the 4-class PET/MR attenuation correction method commonly used in clinical practice. The metod directly predicts the error in the PET image of bones not being included in the 4-class attenuation... |
0f7e10af164f40f7b96d8c800883c823dd87086dff5440a5466a0eb2945f99c5 | Text | 2,199 | 79 | # BCI-walls
These scripts calculate SNR and the SNR-walls of EEG
[](https://zenodo.org/badge/latestdoi/146623395)
## Dataset
Download the dataset from https://researchdata.gla.ac.uk/1258/
and unpack the zip outwidth of this repository so that the directory
structure loo... |
c1b01274f18c6d3016af4b3e7d361f363249c3025808894f6aa55550b2c2af31 | Text | 2,272 | 46 | # FTIR Spectral and Test Strip Data
This repository contains the data utilized in our project. It includes FTIR spectral data and a dataset with test strip data. The purpose of sharing this data is to facilitate transparency, and to allow for others to replicate and validate our analysis. All data is anonymized and do... |
8e27f69b33359aaa13c523825e9c132de79853358f4fbcd8ed69c98682efe320 | Text | 2,287 | 22 | # Design of synthetic promoters for cyanobacteria with generative deep-learning model
In our study, 'Design of synthetic promoters for cyanobacteria with generative deep-learning model', we provide a deep-learning based generic framework to generate synthetic promoter sequences for cyanobacteria and predict their stren... |
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