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56ec145b1bad15d777b6dd8c9a110179bd2156a99f239a4c5b2527833b69c5cc | Text | 1,049 | 14 | Please cite the following references if you use these data:
S. Schwab, M. Mouthon, L.B. Jost, J. Salvadori, I. Yakoub, E. Ferreira da Silva, N. Giroud, B. Perriard and J.M. Annoni, Neural correlates of lexical stress processing in a foreign free-stress language; Brain and Behavior (2023)
L. Rogenmoser, M. Mouthon,... |
3ae84c070977908dc7a124ac057dbd394e35d02e40917767f076ca9fbb58de7c | Text | 1,055 | 23 | # pyNeurite
A computer vision package that traces and analyzes neurites fully automated. Optimized for time-lapse videos.
Used in Schelski and Bradke, 2022, Science Advances (https://www.science.org/doi/10.1126/sciadv.abo2336)
# Installation
The package was developed and tested on Windows.
<br/>
1. If you don't alre... |
08c21b814e2fc1c653cdcc4b7ed65323108cd1faa8c336c949c60fcb092334b4 | Text | 1,058 | 31 | <h1 align="center">
Laplace.jl
</h1>
<p align="center">Numerical procedures to perform inverse Laplace transforms
<div align="center">
[](https://heltonmc.github.io/Laplace.jl/stable)
[](https://helto... |
df8320a761b50e0fae16ff2a081d0153fcdee444aee93c6d659f088b13930380 | Text | 1,067 | 24 | # CSOptim
Gradient-based optimization of core-shell particles with distinct material classes. For detailed information please check the [article](https://www.nature.com/articles/s41598-022-21802-3)
## Requirements
Setup a suitable [conda](https://docs.conda.io/en/lates... |
973a40cdc20346d80ba856316ac1133a3c22e437e01e46277dfb68bdfa310627 | Text | 1,097 | 51 | # Deep Neuronal Filter (DNF) -- libtorch version
A realtime noise reduction filter using deep networks in autoencoder configuration.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0277974
## Prerequisites Libraries and packages
1) Make sure you have `cmake` and a c++ ... |
44cd2435597c4ec22d960b4ba7db750f5b5799d8389d97e38fd1f2078fed69ab | Text | 1,099 | 39 | **Deprecated.** <br/>
Use KDE EBM instead: [ucl-pond:kde_ebm](https://github.com/ucl-pond/kde_ebm)
<hr/>
<hr/>
<hr/>
Event-Based Model
=================
The Event-Based Model (EBM) is a simple, robust model for the estimation of the most likely order of events in a degenerative disease.
Important Links
========... |
12cd971b8d2003547b28b36a27b43fe24a46bc6d6812faa1f32f78d9bcc1c523 | Text | 1,100 | 24 | # Pipeline_for_anatomical_connectivity_along_the_anterior-posterior_axis_of_the_human_hippocampus
This repository contains code for the following preprint paper:
Marshall A Dalton, Arkiev D'Souza, Jinglei Lv and Fernando Calamante. "Anatomical connectivity along the anterior-posterior axis of the human hippocampus: n... |
8e0557ba25d87e4f458e39ff5aef0901f7a45c36dd7116c0b0c691ed911f85cb | Text | 1,102 | 17 | # [Urban Nature Recommender](https://unarec.azurewebsites.net/)
The Urban Nature Recommender (UNR) is an expert system that facilitates knowledge acquisition from an NBS case repository. The UNR is a hybrid system integrating a black-box Artificial Neural Network (ANN) with a white-box Case-Based Reasoning model. UNR ... |
c1c2f9e15932ef8b9f9dfdc5ab08a1481b65301cf79de90596edec51ee69f9ae | Text | 1,133 | 15 | # Copolymer Machine Learning
Code and data for the paper [Machine learning strategies for the structure-property relationship of copolymers](https://www.cell.com/iscience/fulltext/S2589-0042(22)00857-4).<a href="https://zenodo.org/badge/latestdoi/488046493"><img src="https://zenodo.org/badge/488046493.svg" alt="DOI"></... |
6d54a0dcc13a2804c0c5cc03e5076522d7de85c16228ca969320d0baca8696f9 | Text | 1,134 | 46 | ======
SMILE
======
-----------------------------------------------
State Machine Interface Library for Experiments
-----------------------------------------------
Overview
========
Writing experiments should be simple, the library should be small, and
it should make you happy.
Prepare to SMILE...
Dependencies
===... |
b1971f86546c828719fff0ea4009e6d2dce9712599ffd5c9e06d3745a051eb9b | Text | 1,135 | 13 | # HAC
Hierarchical Clustering is a visualization technique used widely in neuroscience to group together similar neural responses to stimuli.
## System requirements
To run this code, you must have MATLAB installed, and have the Statistics and Machine Learning Toolbox.
This code was tested using MATLAB version 9.14.... |
ff23711dd667672df70a974c83ff9e4acef31c391892a09db60d8bf6d7e8a7bd | Text | 1,137 | 19 | # gradient_boosting_CLF
Repository for reproducing the results presented in the paper "Tuning gradient boosting for imbalanced bioassay modelling".
## Overview
- [losses... |
b24bda2a5cb726589e0971f8f1f51e83475acf94574100c03f4f275725f8a282 | Text | 1,152 | 12 | # scNTImpute:single-cell Neural Topic Imputation Model
scNTImpute is a model for imputation of scRNA-seq data, helping to improve downstream analysis of single-cell RNA sequencing data and more.
Without any installation, researchers can download and use the source generation to pre-process scRNA-seq data to accurate... |
d33c69f01be4da5a1602bd01d1c042232e97d27a914f3e10aabe36a82bd4d7fe | Text | 1,170 | 16 | # sumo
This package contains various functions related to statistics, data visualisation, data organisation and image analysis.
Make_project() creates an environment with classical folder structures (Data, Figures, Docs, References, Sources, Gist) and a R script at its root.
If IHC = TRUE, it will create "czi" folder... |
dcc298b1cdd0aa50033d37f351d74f559df3eef75f75747d73d64fb57d1f2142 | Text | 1,186 | 21 | # Domain Adversarial Neural Network (shallow implementation)
This python code has been used to conduct the experiments
presented in Section 5.1 of the following JMLR paper.
> Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle,
> François Laviolette, Mario Marchand, Victor Lempitsky.
> ... |
4cea5cbb058de02341daf4bc4ddc3daa5ad0857cc75677026e8df4482c686177 | Text | 1,189 | 53 | # Deep Neuronal Filter (DNF) -- libtorch version
[](https://doi.org/10.5281/zenodo.17827627)
A realtime noise reduction filter using deep networks in autoencoder configuration.
https://journals.plos.org/plosone/article?id=10.1371/journal.pon... |
d358db7c285318999bc905e31e08080985336ae79ec3d05ba66dd0cba983341f | Text | 1,193 | 14 | # livecellreg
Correlation-based registration of 2D & 3D live cell imaging movies using translation of images. It also works quite well for cells with signals that change localization over time within the structure that should be registered - e.g. a signal that is moving within the cell.
Only works with timelapse re... |
2ffb6d4b34cacbe9aaa2960d596c825bbb263caa0a34e6ea40b4fe0815719d7e | Text | 1,210 | 13 | The zip archive contains all the images and raw data generated for: Katrina M Longhini & Michael Glotzer, “Aurora A and cortical flows promote polarization and cytokinesis by inducing asymmetric ECT-2 accumulation”
In the archive, the data is organized by figure then per experiment. Each embryo folder contains format... |
a144ab9ad32312e679b7775648f59858d467b39edd429157043f1ea8d3e8776a | Text | 1,220 | 27 | # rmf 2.28.2022, last modified 3.2.2022
Code required to replicate analyses in:
Sebastian B, Fey RM, Morar P, Lasher B, Giebultowicz JM, Hendrix DA. Discovery and Visualization of Age-Dependent Patterns in the Diurnal Transcriptome of Drosophila. Journal of Circadian Rhythms. 2022;20.
https://doi.org/10.5334/jcr.2... |
eb300c73fa9b1d9ff7d677d6d68c2e7d180d09053cdc0997215f09792237d318 | Text | 1,225 | 14 | # livecellreg
Correlation-based registration of 2D & 3D live cell imaging movies using translation of images. It also works quite well for cells with signals that change localization over time within the structure that should be registered - e.g. a signal that is moving within the cell.
Only works with timelapse ... |
1f61ab9295d8659757f8b774e8537a7567dbf880811e2a1d3d4880e5282e9ee8 | Text | 1,230 | 13 | # Transparency and open science standards in the policies of medical and health science journals
This repository contains the data and code used to analyse TOP scores (using OSF's Transparency and Openness Promotion Guidelines) for 20 high-ranking journals in health and medical sciences. More details are available on ... |
b149405dc62e9da844829d6f08c8fe29ffb927a341ebe319374491edb8ccf274 | Text | 1,232 | 18 | # Glands detection in prostate biopsies
A deep learning algorithm based on convolutional neural networks to detect glandular cells in digitalized biopsies of the prostate. Performed as final degree work for the degree in computer engineering.
## Abstract
Cancer is constituted as the second cause of global death and s... |
3f507a58b348a1577add0c4e5a5066ca60d890e5d27ba01b0a564e8feaa40fb8 | Text | 1,235 | 22 | # OCELOTML 2D
This repository contains the code to download the OCELOT chromophore dataset and use the pretrained models to make predictions. You can find the online implementation at [here](https://oscar.as.uky.edu/ocelotml_2d)
More details on model in our paper [Electronic, Redox, and Optical Property Prediction of ... |
0537aa376db2908f8f8c1e0a854e72d5320f54a3bd74634aa5d1ceade174520b | Text | 1,240 | 36 | # Smartshopping project repository for our PLOS One paper.
###Important note : make sure to download the data.zip file available through this link :
https://drive.google.com/file/d/1q-LkWMx5ar-OGlPPLFwSDi-IbLe7ZaIo/view?usp=sharing
###Extract the content of data.zip at the root of the project.
The 'ml_algorithms.p... |
4e391a44f3e5923d7543a5548415e43ec8abc5b0a2499bf2259658e061c7cfc0 | Text | 1,257 | 30 | # E2E_ASD_DETECTION
ASD Detection based on feature extractors(Auto-encoder or wav2vec2.0) and BLSTM classifier
# Information
The model training and evaluation scripts for BLSTM, AE-BLSTM-FT, AE-BLSTM-JT, W2V-BLSTM-FT, and W2V-BLSTM-JT. <br />
# Arguments
For AE-BLSTM-FT, it consists of two stages. You should train t... |
a45fcbccebfb628c43ab2e0943cead445b520bde1b4869301c1ca7c175e3684e | Text | 1,266 | 28 | # BitDepth_NucSeg
This repository contains a fully annotated nuclei segmentation dataset of 8-bit and 16-bits fluorescence Dapi stained microscopic images from 5 human organs at a fixed size of 512x512 pixels.
## Citation
A pape... |
8a05ed070732a527ab4564260616091caa9e996ec76a9ccbcb6b79849af5bb11 | Text | 1,281 | 6 | # cascadia-behavioral-healthcare
Code and datasets for a study in collaboration with Cascadia-Behavioral-Healthcare
## Mechanistic Modeling as an Explanatory Tool for Clinical Treatment of Chronic Catatonia
Mathematical modeling of neural systems is an effective means to integrate complex information about the brain ... |
ddef847a719100725c046d0e797d4d3d52f7dce746ce87ec49e84e91fd3e653b | Text | 1,281 | 7 | # sample_efficient_pop_codes
Code for the paper [Population Codes Enable Learning from Few Examples By Shaping Inductive Bias](https://www.biorxiv.org/content/10.1101/2021.03.30.437743v1).
The analysis of Mouse V1 responses can be reproduced with code in the [KPCA_EXPT](KPCA_EXPT) directory. Responses of V1 cells to ... |
d9f4c307d7e8266f7b64da04e8e1acbc39f3f60ae5b5082b1c18f7091b78148a | Text | 1,303 | 54 | ## Overview
magicBatch is a modified version of the MAGIC algorithm that allows for batch-corrected imputation of multi-batch datasets.
## Installation
1) install the magicBatch python package using one of two methods:
From within R (preferred):
```
python_path <- system("which python3", intern = TRUE)
system... |
cadc883971035d6c630c7d4b93b0102058d38c439b5e9347be5ff798b9689877 | Text | 1,308 | 16 | # Gene-Gene Interaction Detection with Deep Learning
Code for "Gene-Gene Interaction Detection with Deep Learning". We design a NN based approach to recover the interactions between genes, which we defined as sets of SNPs.
---
#### Toy example on simulated data:
On the simulated dataset, we simulate 20 SNPs ("/data/ge... |
470e920460b153467aaf7b0703a9eaf57060c12062f785791eb4d1b3799caec6 | Text | 1,335 | 63 | # Deep Neuronal Filter (DNF)
[](https://doi.org/10.5281/zenodo.7100537)
[See also the libtorch version of the DNF](https://github.com/berndporr/dnf_torch)
## Prerequisites Libraries and packages
1) Install the IIR and FIR filter libraries
Installation ... |
909aff24864a39888f16a33eb8d106ad11ebd0984b22ef20962dbe5a2693379e | Text | 1,336 | 38 | # Detecting temperature targets
***
Neural networks are trained on CMIP6 data to detect the remaining number of years until specific temperature targets are reached.
## Tensorflow Code
***
This code was written in python 3.9.7, tensorflow 2.7.0, tensorflow-probability 0.15.0 and numpy 1.22.2.
### Python Envi... |
1f3fdc07caf93d561e11906beeba1dc098a54b5e6ca795852eb257b18ef25ee0 | Text | 1,370 | 41 | # Language Model Representations for Sentiment Analysis in English Tweets
Official implementation of [Sentiment analysis in tweets: an assessment study from classical to modern text representation models](https://arxiv.org/abs/2105.14373).
# How to use :
## Available models
<!-- Com link -->
| Model ... |
54910215ab4b44f4c8a7a6cf5d69b73df18c363966f6559352a1421f91229325 | Text | 1,373 | 13 | # lfp-juxta
This repository contains codes and data used in the following paper:
"Spread of pathological human Tau from neurons to oligodendrocytes and loss of high-firing pyramidal neurons in ageing mice" by Tim J. Viney, Barbara Sarkany, A. Tugrul Ozdemir, Katja Hartwich, Judith Schweimer, David Bannerman, Peter So... |
e437c9e16c4f40a03392edf1a5811ca52bfa1b49a1286c014e6700e851d8ac7a | Text | 1,378 | 42 | # GILoop
GILoop is a deep learning model for detecting CTCF-mediated loops on Hi-C contact maps.
**New:** *GILoop now supports `.cool` input*
#### Installation:
```
conda create -n GIL python=3.8
conda activate GIL
pip install -r requirements.txt
```
After runn... |
b126c8e5197a0ec9b336e172b0d173a3f000dc6260828a52890ed3b8e0cbe67f | Text | 1,406 | 30 | # FAN-C: Framework for the ANalysis of C-like data
FAN-C provides a pipeline for analysing Hi-C data starting at mapped paired-end sequencing reads.
Please check out the documentation at https://fan-c.readthedocs.io/en/latest/ for... |
db516c56b456ac789e87a93611358eed23d67722a0948a407d5791ac79fc7729 | Text | 1,441 | 31 | # Retinal Organoid Bulk RNAseq, Scientific Data 2022
This repository contains code used for quality control and data analysis presented in:
> Agarwal, D.; Kuhns, R.; Dimitriou, C.N.; Barlow, E.; Wahlin, K.J.; Enke, R.A. Bulk RNA Sequencing Analysis of Developing Human Induced Pluripotent Cell-Derived Retinal Organoi... |
d24e7f1c274314d24789c58c3f92ae06835474d24dcc902bad280ac7b428001f | Text | 1,474 | 41 | # ProBioSim
ProBioSim is a simulator for mass-action chemical reaction networks.
## Description
- ProBioSim includes both deterministic (ODE-based) and stochastic simulation engines.
- Most notably, ProBioSim provides powerful features for modifying the state of the simulation at specified timepoints, by specifying ... |
28e23eecb4d7cc482c246148c4e745a4fb1ad3aae99e178ba09c77e6c1ba361e | Text | 1,491 | 21 | The dataset contains the NEURON simulations and python codes for ANN fitting and evaluation.
The first folder contains the ANN benchmarking code, and the necessary ANNs in .h5 file format.
All NEURON models were created with the same logic, the most detailed documentation in in the single compartmental model folder.
... |
6ca0a93ab5c7fea133c4eb67cca4f2a9390d5dda1d2e78cd1ca29e623bb7d056 | Text | 1,515 | 17 | # This Repository contains the code to locally run the **Injured Sciatic Nerve Atlas (iSNAT) described in this [eLife publication](https://doi.org/10.7554/eLife.80881 "The Injured Sciatic Nerve Atlas (iSNAT), insights into the cellular and molecular basis of neural tissue degeneration and regeneration")**
](https://zenodo.org/badge/latestdoi/165096390)
Python pipeline for neuroimaging data. Documentation at https://clpipe.readthedocs.io/en/latest/index.html
If you run into issues, find bugs, or have feature requests, please create an issue in this repository.
I... |
2642d15d97009f72adc96e6a12579ff4185c529e8e80ee98f7807867ee62530d | Text | 1,585 | 26 | # NCI-DOE-Collab-Pilot1-Normal-Tumor-Pair-Classifier
### Description
The Normal/Tumor classifier capability (NT3) shows how to train and use a neural network model to classify molecular features (such as RNA-Seq expressions) as either normal or tumor. The RNA-Seq expressions are provided in Genomic Data Commons (GDC).... |
861f25b0d2f9b32c0a8f03002711c5c4bc5d72e2e3716ddf6f2c86b793df0634 | Text | 1,609 | 29 | # NCI-DOE-Collab-Pilot1-Tumor-Classifier
### Description:
The Tumor Classifier capability (TC1) shows how to train and use a neural network model to classify tumor types from molecular features (such as RNA-Seq expressions) provided in Genomics Data Commons (GDC).
### User Community:
Researchers interested in cancer... |
6a31925d5c5a6c4ffbfe4280c6999a9e78ea3406fa92fac4737fc41fb33b3744 | Text | 1,642 | 34 | # GuanidinoaceticAcid
[](https://github.com/ScreenNeuroPharm/GuanidinoaceticAcid/blob/master/LICENSE)
> The repository contains the data and the functions needed to reproduce the analysis reported in the article "Lack of epileptogenic effects of the creatin... |
d525f79e855574d0e30d76aa3a17baa42bc3409ab7b465c195f5bb6a0f29596e | Text | 1,659 | 42 | Shield: [![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa]
This work is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].
[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]
[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-s... |
a7055c09a8a9406fb8854a4a9dcf8e0584d3b4cb091c70382433f489a5fcbaed | Text | 1,673 | 25 | # Sparse RNNs can support high-capacity classification
The BPTT Python + Pytorch simulations, Hebbian Learning Matlab simulations and Directed Graph Empirical Study results can be found in their respective folders.
## BPTT
The "Regular" code works via sparsity and EI architecture Mask, while the "SpeedUp" code works ... |
9a93f0fd1cbb39770e3844b7ad8aef0e8f5ecd86786c9518e12912a1eb1f61f0 | Text | 1,679 | 32 | # singleCellTools
Tools for analysis of single-cell sequencing data, by Alex Smith in the lab of Paul Kenny @ Mount Sinai.
[](https://zenodo.org/badge/latestdoi/273064116)
#Overview:
* ACWS_scanPy_MASTER.py - contains a full workflow for analysis of single-cell sequencin... |
29772cfa7a4c5502b7ef0c2c3906cdc25283ffbef4636db09f1629a49af536df | Text | 1,722 | 24 | # nct_hierarchy
The goal of this project was to examine whether the topology of the structural connectome—which we index using an
undirected description of connectivty—confers asymmetries in signal propagation across the cortical hierarchy of
cytoarchitecture. We use Network Control Theory to model state transitions ... |
913723c728a02e2ba1dd8ed756590c6f654ed1a52e7127643227245a0cf48f69 | Text | 1,726 | 33 | The main objective of this project is to convert existing whole-cell patch clamp recordings in ABF format into the open NWB standard and publish these openly on the DANDI archive. This repository will be used to raise issues, track progress and ensure the process is reproducible.
Datasets were published to DANDI here:... |
fa2b746b88f0147d3b41af407b12f0ecfe774bb97c964f6d28d4baa71f170d30 | Text | 1,739 | 55 | # rl_materials
## About
A library for general-purpose material optimization using AlphaZero-style reinforcement learning.
This repo is a snapshot of the code used for the paper "Upper-Bound Energy Minimization to Search for Stable
Functional Materials with Graph Neural Networks" in 2022.
The code to optimize crys... |
22d28a0a57be3510b53c8ec0cdd3480d821111343dc89bed59ca83b4bb7e7364 | Text | 1,740 | 11 | # CilOCT: A software for semi-automatic segmentation and analysis of the ciliary muscle in OCT images
Presbyopia and myopia research show a growing interest in ciliary muscle (CM) biometry using optical coherence tomography (OCT). Until now, segmentation of the CM is often performed manually using either custom-develo... |
3bb84541b918f8ef4918c4c5b220a8f9d636241b5ff21547a256d21e4459d42a | Text | 1,747 | 35 | # `GAGome-MCED`
## 🔬 Description
This repository contains code and example data sets for the publication "Noninvasive detection of any-stage cancer using free glycosaminoglycans".
Both a synthetic data set with standardized GAGome values and the code for the development of free GAGome MCED scores are available in th... |
317cc676872ac9f87c26588a64940b05c02e120656fdaf4174a585dc6a188444 | Text | 1,763 | 45 | # Computational and neural mechanisms of statistical pain learning
Suyi Zhang, Ben Seymour, Flavia Mancini
In press in Nature Communications
An older version of the paper: doi: https://doi.org/10.1101/2021.10.21.465270
## Usage
The code in folder exp_code is used to generate the sequence of stimuli.
The experimen... |
b23be3abcffeac76c733186348cb173727682e4844ad253ac9f820784d81c695 | Text | 1,790 | 30 | # A connectomics-based taxonomy of mammals
## "What's in this repository?"
This repository contains code for the analysis presented in "[A connectomics-based taxonomy of mammals](https://elifesciences.org/articles/78635)" by Laura E. Suarez, Yossi Yovel, Martijn P. van den Heuvel, Olaf Sporns, Yaniv Assaf, Guilla... |
6d254741389b2c08c465fef0cae2ed521d6d495fa865d225bf0e6031c8352fb6 | Text | 1,807 | 26 | # SPIJN
## Description
Code for the Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm as used for Multi-component Magnetic Resonance Fingerprinting using a joint sparsity constraint.
The algorithm is described in
Nagtegaal, Martijn, Peter Koken, Thomas Amthor, and Mariya Doneva. “Fast Multi-Component Analysi... |
ee0f651eb1a3bb1c82eb2702a9c604ebe7df8d8c69cdfa6c49e15758414f245e | Text | 1,814 | 44 | # Flexible integration of continuous sensory evidence in perceptual estimation tasks
Code of the computational models and psychophysical data of the paper "Flexible integration of continuous sensory evidence in perceptual estimation tasks"
## Requirements
The scripts have been tested in Python 3.9 running on Ubuntu 2... |
a30d07a4099ff4567acc55c2d2c154268851c213316682276fa944138103f13e | Text | 1,817 | 25 | # nct_hierarchy
[](https://zenodo.org/badge/latestdoi/333524327)
The goal of this project was to examine whether the topology of the structural connectome—which we index using an
undirected description of connectivty—confers asymmetries in signal propagation across the cor... |
5c9393267f09194b12b074cb03260f45a596995a36d51b2976a91c8ba3ca1d79 | Text | 1,823 | 45 | README.md
**About the prototype**
The final goal of this MATLAB/LeadDBS addon is to reduce the time patients and clinicians spend tediously testing various DBS parameter values, as well as to improve patient outcomes through finding as optimal parameter values as possible on a patient-specific basis. This GUI and alg... |
5312fec3c27f8f91234fb665bf849c5a5f4963ee477356989993a2c45b426ce1 | Text | 1,903 | 45 | # Computational and neural mechanisms of statistical pain learning
Suyi Zhang, Ben Seymour, Flavia Mancini
Mancini, F., Zhang, S. & Seymour, B. Computational and neural mechanisms of statistical pain learning. Nat Commun 13, 6613 (2022). https://doi.org/10.1038/s41467-022-34283-9
An older version of the paper: doi: ... |
469a2953cf2b246fa06e6bcb560c974b958a84d63447ec16f00f4620ea0bef39 | Text | 1,905 | 5 | # Mouse-synaptome-Pax6-disease
Code used for the manuscript 'Laura Tomas-Roca, Zhen Qiu, Erik Fransén, Ragini Gokhale, Edita Bulovaite, David J. Price, Noboru H. Komiyama, Seth G.N. Grant (2022) Developmental disruption and restoration of brain synaptome architecture in the murine Pax6 neurodevelopmental disease model... |
ae6b8ff501f8b1509c9f7b23c18daa99e6c531e7be2c4af0747c90e218880486 | Text | 1,913 | 23 | # DDTBOX
Decision Decoding Toolbox
Copyright (c) 2013--2018 Stefan Bode and contributors.
Unless otherwise specified, code is distributed under the GNU Public License (GPL) version 2, and documentation under a Creative Commons Attribution-Share-Alike 4.0 International license.
<a rel="license" href="http://creativec... |
bc1ea192f0bfd182ff2b3bfc6867d12803a2569bcfe0e93ae99b8a97c5e08d50 | Text | 1,965 | 51 | # Building Cell Ranger ATAC 1.2.0
## Build dependencies
This package has been built internally using:
- Python 2.7.13
- clang 7.0 (gcc/g++ should also work)
- go 1.12
## Setting up the environment and build dependencies
- Environment dependencies can be found in the Ranger ATAC 1.2.0 package (https://support.10xgeno... |
c511e9fe312f1195bf4b9286a04a5a89c9c5c60567dc5042c784356da9603991 | Text | 1,967 | 8 | # DL-on-PD-oscillaroy-topographic-pattern
Deep convolutional neural network (DCNN) provides a multivariate framework to detect relevant spatio-oscillatory patterns in the data beyond common mass-univariate statistics. Yet, its practical application is limited due to the low interpretability of the results beyond accura... |
5a89a334a85603f17e700fc1373e5ebdf47d97155bb94cd0fd59a9b0f50b3f0d | Text | 1,991 | 34 | Requirements:
* R (version 4.0.3 was used for analyses in the paper)
* Deriv package (version 4.1 was used for analyses in the paper)
(to install this, open R and execute the command: install.packages("Deriv") )
Instructions for running the ODE-GP code on the ADNI data:
* Edit file paths in `ODE_GP_v6_public.R` so t... |
c164f38381c0300324799f3551e95d73e18e2541e373cc19bb7f677bc6e93da5 | Text | 1,997 | 43 | # findPeaks
A repo for a function I posted as part of my answer to a [quesiton about peak detection](http://stats.stackexchange.com/questions/22974/how-to-find-local-peaks-valleys-in-a-series-of-data/164830#164830) on StackExchange.
The function takes an ordered sequence (vector) of values `x` and a number `m` and re... |
bd613d3e68e3d2b682d3379580c30e263e3cfbc0eeb31a5364ff9013db8c90e2 | Text | 2,011 | 18 | ### Artificial Intelligence Convolutional Neural Networks maps giant kelp forests from satellite imagery
Marquez, L.; Fragkopoulou, E.; Serrão, E.A.; Cavanaugh, K.; Houskeeper, H.; E.; Assis, J.
<hr style="border: 0.5px">
### Rationale
Ongoing climate change is producing shifts in the distribution and abundance of n... |
bd5bee78a57b218b36b4c293cf4a424223026b845f033a6952d1c0144a8d4929 | Text | 2,032 | 39 | ## Fashion200K dataset
Fashion200K dataset used in ICCV'17 paper "Automatic Spatially-aware Fashion Concept Discovery." [[paper]](https://arxiv.org/pdf/1708.01311.pdf)
### Contact
Author: Xintong Han
Contact: xintong@umd.edu
### Dataset
This dataset is crawled from [Lyst.com](http://lyst.com) in September 2016.
... |
724e15311ede5474963cba9c4d0dfccc5ec5871b4deaf8f236a53c35b0841d02 | Text | 2,059 | 21 | # flexible_cpm
Modified connectome-based predictive model. See preprint of book chapter outlining this method: https://osf.io/ay95f/
1) Enables inclusion of covariates at feature selection or model-building stage or both stages
2) Provides ability to threshold edges based on p-values (e.g. only select edges with p-va... |
1875de0298ab10da38ea76495f0d283045f42ffe34d57475ae8ce28785e00914 | Text | 2,095 | 37 | # rG4detector
We present rG4detector, a convolutional neural network for predicting rG4 folding of any given sequence based on rG4-seq data. rG4-seq experimental protocol was employed to generate transcriptome-wide rG4 maps of human HeLa cells (accession code GSE77282). In this study, we used the experimental raw data... |
d20fe652bd8c67eba9617ea072df5c4fdc2f20e878978fc2d91e3462e0ee4a66 | Text | 2,120 | 28 | # Jadhav Lab Codes
Code repositories from Jadhav Lab
This repository has all my code from the jadhav lab. Right now there are three projects
1. BetaOdorProject: olfactory guided T maze task, this was published under DOI: https://doi.org/10.7554/eLife.79545
This repository also contains an archived version o... |
059f10ca2c5f06996bfa91916f0a7310bbe5328bd1c7688e9f8b729436b6bd81 | Text | 2,192 | 32 | ## Last updated 24/04/2022
## All original code is copyright of Graham King, Trinity College Institute of Neuroscience.
This repository is divided into three folders: HEADCOIL, REGRESSOR, and FINGER.
HEADCOIL folder contains code relating to:
- participant groups (csv files)
- Calculating the SNRCoil of the ... |
5ba15576d9d735c5ebe4e1a56817e4007b5a75c83ca7287ea7f97bd7e6fde89e | Text | 2,195 | 54 | # Deep Learning Utilities for Pathology: PyTorch-lightning implementation of multiple instance learning models
==== WORK IN PROGRESS ====
- Add bash scripts to run compilation of features from VISSL
- Add bash scripts to run training of all classifiers
- Add config files
- Improve documentation
=====================... |
cad1e58fd4d0c63a715157f791ebf44ec795eaec8505eeb878c0325af8915de0 | Text | 2,234 | 60 | # tension
The `tension` package is a Python package for building and FORCE training chaotic recurrent neural networks. `tension` is built to integrate seamlessly with TensorFlow/Keras, a widely used software package for training artificial neural networks.
## Code and documentation
Installation guide, contributing gu... |
fc5fb593dbe956015d2a78d84b9341292eddf64041aab4e149b11c7b0163ed59 | Text | 2,241 | 36 | # Smart-Upload
Script for uploading dicom files to xnat. This script will clean and decompress the images before uploading them to the ctp. Then, the ctp anonymizes and uploads the files to the xnat platform.
## Previous steps
Before launching the script there are some points to take in account. First, you will need... |
8a676e64b5cedeb37fb448b860c97683b218de767005e61a35c0725323a5f9c0 | Text | 2,261 | 30 | # scNTImpute:single-cell Neural Topic Imputation Model
scNTImpute is a model for imputation of scRNA-seq data, helping to improve downstream analysis of single-cell RNA sequencing data and more. Without any installation, researchers can download and use the source code to pre-process scRNA-seq data to accurately and ef... |
b485fd19cf7dbc3dbee6c0258e86340f5e333dc12ba1efcd094f2ddc7396d103 | Text | 2,266 | 18 | This is the code that accompanies the paper - Estimating bone marrow adiposity from head MRI and identifying its genetic architecture, Kaufmann et al, eLife 2026 (https://doi.org/10.7554/eLife.101499.1)
A description of how to use this code can be found in 000_README.pdf file (https://github.com/comgen/boneMarrowLocal... |
73eae29803bd432e810027928f267b09f49d71f5c31a5620a2e6647c06f5a0da | Text | 2,273 | 36 | # BindSiteS-CNN
**This is a repository for BindSiteS-CNN under preparation. Not yet completed and may contain mistakes / non-optimal code**
This is a demo of the official PyTorch implementation of our paper in submission: *Classification of Protein Binding Sites using a Spherical Convolutional Neural Network*
## Dep... |
4e12d792273b90b12e9e9aa4c63807150bc05f441d1dcb118893698642d0ce08 | Text | 2,287 | 42 | MEXPRESS
========
### About
MEXPRESS is a data visualization tool designed for the easy visualization of [TCGA](https://tcga-data.nci.nih.gov/tcga/) expression, DNA methylation and clinical data, as well as the relationships between them. The first version of MEXPRESS was published in BMC Genomics: https://www.biomed... |
f7221bb8e1e787aaae2eb79ea5c43763304ea24fad4021281cea2f6d2219df39 | Text | 2,328 | 46 | ### Demo codes for
### "Invariance of object detection in untrained deep neural networks" </br>
Jeonghwan Cheon, Seungdae Baek, and Se-Bum Paik*
*Contact: sbpaik@kaist.ac.kr
### 1. System requirements
- MATLAB 2021b or later version
- Installation of the Deep Learning Toolbox (https://www.mathworks.com/products/deep... |
4db0507878b34641d832313a12627db57f40ec5b76f3288657c4a811463272b0 | Text | 2,349 | 41 | twitter-sentiment-training
==========================
Training set of 5513 hand-classified tweets for sentiment classifiers
----
This is an upgrade to the original script by Niek J. Sanders available [here] (http://www.sananalytics.com/lab/twitter-sentiment/).
Twitter's [REST API v1.1] (https://dev.twitter.com/docs... |
ea709839149368e44c3d4793e12e9107b13b65f2c68cf77cee392f2f19384b0e | Text | 2,353 | 32 | # Review on "Precise Spiking Motifs in Neurobiological and Neuromorphic Data"
- Antoine Grimaldi, Amélie Gruel, Camille Besnainou, Jean-Nicolas Jérémie, Jean Martinet, Laurent U Perrinet
* read the paper [online](https://arxiv.org/html/2404.07866v1) or in [PDF](https://arxiv.org/pdf/2404.07866v1.pdf)
* [Video Abstr... |
a35fc781fd816ffe092037751199864de271cc3025261dc5b117aa8ac1b062f0 | Text | 2,385 | 43 | # lcni_motion_scripts
Scripts for dealing with subject motion in fmri
## censor_volumes.py
This script takes a functional series in nifti format and a text file containing motion metrics and removes volumes exceeding a given value. There is also an option to specify a minimum duration for retained segments, and an o... |
1a03d44a7f801e752d39bdd8945e08774327e6e3b7f1c1c89ab9318e3777692f | Text | 2,414 | 26 | # punctaDensity
Puncta density estimation code for Gesuita et al., 2022, Cell Reports.
%%%%%
For synaptic boutons counting, the mSyp::GFP channel was filtered using the Wiener filtering followed by bilateral filtering for denoising (the Wiener filter performs adaptive noise removal through low-pass filtering of the i... |
c9bcd20bd7abb0cb702f7dd8a933df8e230c4191294f2cd40b6404d6ce13da04 | Text | 2,424 | 27 | # What have single-cell transcriptomics taught us about long noncoding RNAs in the ventricular-subventricular zone?
Jemima Becker <sup>1</sup>, Bin Sun <sup>1</sup>, Farah Alammari <sup>2</sup>, Wilfried Haerty <sup>3</sup>, Keith W. Vance <sup>4</sup>, and Francis Szele <sup>1</sup>
<sup>1</sup> Department of ... |
4277a184a6e4df9e0f5f9fa99674ab7b32f3767d9bfb8e27ecf9471b09cd722b | Text | 2,446 | 66 | [](https://github.com/neuroquery/neuroquery/actions/workflows/testing.yml)[](https://codecov.io/gh/neuroquery/neuroquery)
# NeuroQuery
NeuroQuer... |
d68e862464d0bdb74cc7d72d49540afdefc460e316c783815041707e78ee7c6a | Text | 2,466 | 37 | <div style="text-align: justify">
# SynthEye
Inherited Retinal Diseases (IRDs) represent a diverse group of rare monogenic diseases resulting in visual impairment and blindness. Over 200 different types of IRDs are known, which affect 1 in 3000 people in the UK. Genetic diagnosis is particularly relevant in IRD care,... |
3765fb69af94c5210bd9ca990c57110f52301fe88561ccada3f706801d473662 | Text | 2,472 | 45 | 
# APARENT2
This repository contains the code for training and running APARENT2, a deep residual neural network that can predict human 3' UTR Alternative Polyadenylation (APA) and cleavage magnitude at base-pair resol... |
4adf936d5c581a521e8997bcca7410345ecdd365570c9e52e1ac66604fdb5155 | Text | 2,491 | 33 | <div align="left"><img src="https://raw.githubusercontent.com/grimmlab/easyPheno/main/docs/image/Logo_easyPheno_Text.png" height="80"/></div>
# easyPheno: A state-of-the-art and easy-to-use Python framework for plant phenotype prediction
[](https://www.pyth... |
9f7737dc7c9949c4d67c6b14d19c3623afc01a21776b6251c1f3ebf543ac0e36 | Text | 2,495 | 98 | [](https://coveralls.io/github/alvarouc/polyssifier)
Polyssifier
===========
Polyssifier runs a multitude of machine learning... |
82c8ceac8c28ca889cbff81646d18d11d03ff4138eb28646fbe1a95d8ce33d78 | Text | 2,506 | 23 | # *C. elegans* Lifespan Prediction
Analysis of a *C. elegans* lifespan prediction method based on a multimodal neural network and uncertainty estimation
## *C. elegans* lifespan demo
Run the demo in [google colab]... |
4052da308a9a25821e35b2f650a4ccc5d63f3d102d13c42cb14997b7ae845681 | Text | 2,554 | 47 | # DeepPROTACs
This model is to predict degradation of the target given PROTACs complex. This repository can help reproduce the experiments of:
Li, F., Hu, Q., Zhang, X. et al. DeepPROTACs is a deep learning-based targeted degradation predictor for PROTACs. Nat Commun 13, 7133 (2022). https://doi.org/10.1038/s41467-02... |
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