sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
b03b38414f7c8704ae723053f9738bb32d47e6edc6c0721681e3811ec0a4f423 | Shell | 18,460 | 612 | #!/bin/bash
# The purpose of this script is to:
# 1. Extract the set of parameters to be used for a docker build based on the provided image name.
# 2. Run docker build with the parameters found in step 1.
# 3. Run the built image and print out the expected and actual versions of packages installed.
set -ex
image="$1... |
7d543cb703c692a5657d7c3c48ca303bffd0f5a778c91e7a7677a0cf4b5dc0f1 | Shell | 20,758 | 593 | #!/bin/bash
#$ -S /bin/bash
#######################################################################
#
# Program: ASHS (Automatic Segmentation of Hippocampal Subfields)
# Module: $Id$
# Language: BASH Shell Script
# Copyright (c) 2012 Paul A. Yushkevich, University of Pennsylvania
#
# This file is part of ... |
ee601d77d81a9f7f71fb162c91262c87a8c37f31565d4b6d687c956bccd2bf34 | Shell | 20,800 | 511 | #!/bin/bash
set -ex -o pipefail
# Required environment variable: $BUILD_ENVIRONMENT
# (This is set by default in the Docker images we build, so you don't
# need to set it yourself.
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# shellcheck source=./common-build.sh
source "$(dirnam... |
2c86095d8c6a7f158b38f4b0cabcd0fe4165cbcecded2cae14029301f44632f8 | Shell | 25,668 | 684 | #!/bin/bash
VERSION="0.0.7"
# Uncomment the line below in case you have not set the ANTSPATH variable in your environment.
if [ ${#ANTSPATH} -le 3 ] ; then
echo we guess at your ants path
export ANTSPATH=${ANTSPATH:="$HOME/bin/ants/"} # EDIT THIS
fi
if [ ! -s ${ANTSPATH}/ANTS ] ; then
echo we cant find the... |
05b2773628fae96ae29ddf3d324040d0fa1963568284eca917938ab5c7ff7d0f | Shell | 37,223 | 1,061 | #!/bin/bash
set -x
VERSION="0.0.13"
# trap keyboard interrupt (control-c)
trap control_c SIGINT
# Uncomment the line below in case you have not set the ANTSPATH variable in your environment.
if [ ${#ANTSPATH} -le 3 ] ; then
echo we guess at your ants path
export ANTSPATH=${ANTSPATH:="$HOME/bin/ants/"} # EDIT ... |
6be602af2fa16dced17aeec5c06aff2c27b51dcbda27d4944104df2abb3e9518 | Shell | 83,387 | 2,563 | #!/bin/bash -
#######################################################################
#
# Program: ASHS (Automatic Segmentation of Hippocampal Subfields)
# Module: $Id$
# Language: BASH Shell Script
# Copyright (c) 2012 Paul A. Yushkevich, University of Pennsylvania
#
# This file is part of ASHS
#
# ASH... |
ace2bbeb590f48a1202006bdf0b123911f0fee98d38b519f77eb85d6148ac012 | Shell | 116,217 | 2,802 | #!/bin/bash
# Required environment variable: $BUILD_ENVIRONMENT
# (This is set by default in the Docker images we build, so you don't
# need to set it yourself.
set -ex -o pipefail
# Suppress ANSI color escape sequences
export TERM=vt100
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.... |
f2d5029cfc672dbd630b5e776dce3459601266db9137874f772458c2c2169d65 | Stata | 9 | 2 | run
quit
|
c9d491843b41ef12f44e981e7d17956016b62e983d98593c76eb4ee3c6fa1e29 | Stata | 11 | 1 | add wave *
|
02b169d2bfd67aea65adb8592f560699afa8992e762ef732056a7f9a6b69e61e | Stata | 30 | 2 | add wave *
add wave /glbl/GSR
|
28df917a64d403ab2f543a3e14cdd9c8ea3ea9e8909f07ea9d55ccbe1c3c8517 | Stata | 179 | 16 | onbreak {quit -f}
onerror {quit -f}
vsim -t 1ps -lib xil_defaultlib fifo_mean_opt
do {wave.do}
view wave
view structure
view signals
do {fifo_mean.udo}
run -all
quit -force
|
85e8cea174cc2c504f8fa7bd0ccb970c5b99723274ce4ef71cbe595fe5fc5582 | Stata | 181 | 16 | onbreak {quit -f}
onerror {quit -f}
vsim -t 1ps -lib xil_defaultlib mult_gen_0_opt
do {wave.do}
view wave
view structure
view signals
do {mult_gen_0.udo}
run -all
quit -force
|
c9895e8b8ad5425eade3ade7604ed429b21923332c6a3546118c285463232fe3 | Stata | 208 | 1 | vopt -64 +acc -l elaborate.log -L xil_defaultlib -L xpm -L fifo_generator_v13_2_3 -L unisims_ver -L unimacro_ver -L secureip -work xil_defaultlib xil_defaultlib.fifo_mean xil_defaultlib.glbl -o fifo_mean_opt
|
e1b8f00ac9be4a3e50ff2483782027c6ab9708fddba42c7dbd8960b1a2c80463 | Stata | 211 | 1 | vopt -64 +acc -l elaborate.log -L xbip_utils_v3_0_9 -L xbip_pipe_v3_0_5 -L xbip_bram18k_v3_0_5 -L mult_gen_v12_0_14 -L xil_defaultlib -L secureip -work xil_defaultlib xil_defaultlib.mult_gen_0 -o mult_gen_0_opt
|
73438e17680103013b1773646ef909cfdcb719fe2fb13abf94a9d3392d1f1c25 | Stata | 315 | 17 | onbreak {quit -force}
onerror {quit -force}
asim -t 1ps +access +r +m+fifo_mean -L xil_defaultlib -L xpm -L fifo_generator_v13_2_3 -L unisims_ver -L unimacro_ver -L secureip -O5 xil_defaultlib.fifo_mean xil_defaultlib.glbl
do {wave.do}
view wave
view structure
do {fifo_mean.udo}
run -all
endsim
quit -force
|
3b85bf41bf0ff2b9bf742d9287704a08b45af5e565df3c907588e8caa318c31b | Stata | 319 | 17 | onbreak {quit -force}
onerror {quit -force}
asim -t 1ps +access +r +m+mult_gen_0 -L xbip_utils_v3_0_9 -L xbip_pipe_v3_0_5 -L xbip_bram18k_v3_0_5 -L mult_gen_v12_0_14 -L xil_defaultlib -L secureip -O5 xil_defaultlib.mult_gen_0
do {wave.do}
view wave
view structure
do {mult_gen_0.udo}
run -all
endsim
quit -force
|
b0b9119d7305b539195c205b43ecb0268f76c14dea161e81b5750a300fe72915 | Stata | 321 | 16 | onbreak {quit -f}
onerror {quit -f}
vsim -voptargs="+acc" -t 1ps -L xil_defaultlib -L xpm -L fifo_generator_v13_2_3 -L unisims_ver -L unimacro_ver -L secureip -lib xil_defaultlib xil_defaultlib.fifo_mean xil_defaultlib.glbl
do {wave.do}
view wave
view structure
view signals
do {fifo_mean.udo}
run -all
quit -force... |
6ba5e293934469ca1ee2b4a983b25bd37c3799fc57f3268bff42624aeaa70822 | Stata | 324 | 16 | onbreak {quit -f}
onerror {quit -f}
vsim -voptargs="+acc" -t 1ps -L xbip_utils_v3_0_9 -L xbip_pipe_v3_0_5 -L xbip_bram18k_v3_0_5 -L mult_gen_v12_0_14 -L xil_defaultlib -L secureip -lib xil_defaultlib xil_defaultlib.mult_gen_0
do {wave.do}
view wave
view structure
view signals
do {mult_gen_0.udo}
run -all
quit -fo... |
9871d18623727cb902b93e6b098debc110a4946ee1eb7c147fbde9d1e93278a1 | Stata | 883 | 31 | vlib work
vlib riviera
vlib riviera/xbip_utils_v3_0_9
vlib riviera/xbip_pipe_v3_0_5
vlib riviera/xbip_bram18k_v3_0_5
vlib riviera/mult_gen_v12_0_14
vlib riviera/xil_defaultlib
vmap xbip_utils_v3_0_9 riviera/xbip_utils_v3_0_9
vmap xbip_pipe_v3_0_5 riviera/xbip_pipe_v3_0_5
vmap xbip_bram18k_v3_0_5 riviera/xbip_bram18k_... |
17f690327bba81fd99ee7bbd24a4f39c9a0ec845cdd3c12bb849792b79d40858 | Stata | 905 | 31 | vlib work
vlib activehdl
vlib activehdl/xbip_utils_v3_0_9
vlib activehdl/xbip_pipe_v3_0_5
vlib activehdl/xbip_bram18k_v3_0_5
vlib activehdl/mult_gen_v12_0_14
vlib activehdl/xil_defaultlib
vmap xbip_utils_v3_0_9 activehdl/xbip_utils_v3_0_9
vmap xbip_pipe_v3_0_5 activehdl/xbip_pipe_v3_0_5
vmap xbip_bram18k_v3_0_5 activ... |
f9d7a23dc1cec5f7d776d9c874ef9a4f06676cf4b797d16340fd436f7a90b1e6 | Stata | 941 | 33 | vlib work
vlib riviera
vlib riviera/xil_defaultlib
vlib riviera/xpm
vlib riviera/fifo_generator_v13_2_3
vmap xil_defaultlib riviera/xil_defaultlib
vmap xpm riviera/xpm
vmap fifo_generator_v13_2_3 riviera/fifo_generator_v13_2_3
vlog -work xil_defaultlib -sv2k12 \
"D:/software/xilinx/Vivado/2018.3/data/ip/xpm/xpm_cdc... |
c21800825a0c621b561c34eb07bd7f1d4b6d4384294b13a851842bd71f1d3336 | Stata | 955 | 33 | vlib work
vlib activehdl
vlib activehdl/xil_defaultlib
vlib activehdl/xpm
vlib activehdl/fifo_generator_v13_2_3
vmap xil_defaultlib activehdl/xil_defaultlib
vmap xpm activehdl/xpm
vmap fifo_generator_v13_2_3 activehdl/fifo_generator_v13_2_3
vlog -work xil_defaultlib -sv2k12 \
"D:/software/xilinx/Vivado/2018.3/data/... |
0e8471015c27174e16103a01002af763ed24b966ab96743c1842ae9bce21d774 | Stata | 1,002 | 31 | vlib questa_lib/work
vlib questa_lib/msim
vlib questa_lib/msim/xbip_utils_v3_0_9
vlib questa_lib/msim/xbip_pipe_v3_0_5
vlib questa_lib/msim/xbip_bram18k_v3_0_5
vlib questa_lib/msim/mult_gen_v12_0_14
vlib questa_lib/msim/xil_defaultlib
vmap xbip_utils_v3_0_9 questa_lib/msim/xbip_utils_v3_0_9
vmap xbip_pipe_v3_0_5 ques... |
40e7ff85aed7e1e1e54b30d4fefc92c5aa6f150a6dfda80c11e0647f56babf23 | Stata | 1,006 | 33 | vlib questa_lib/work
vlib questa_lib/msim
vlib questa_lib/msim/xil_defaultlib
vlib questa_lib/msim/xpm
vlib questa_lib/msim/fifo_generator_v13_2_3
vmap xil_defaultlib questa_lib/msim/xil_defaultlib
vmap xpm questa_lib/msim/xpm
vmap fifo_generator_v13_2_3 questa_lib/msim/fifo_generator_v13_2_3
vlog -work xil_defaultl... |
8448bc9529ca2daf77467c5df6427e76bfd54d81c93ca683282ccc7921de8c10 | Stata | 1,026 | 31 | vlib modelsim_lib/work
vlib modelsim_lib/msim
vlib modelsim_lib/msim/xbip_utils_v3_0_9
vlib modelsim_lib/msim/xbip_pipe_v3_0_5
vlib modelsim_lib/msim/xbip_bram18k_v3_0_5
vlib modelsim_lib/msim/mult_gen_v12_0_14
vlib modelsim_lib/msim/xil_defaultlib
vmap xbip_utils_v3_0_9 modelsim_lib/msim/xbip_utils_v3_0_9
vmap xbip_... |
402780a1245186a4b8959ae1765710c081fd3b7640c3362463bfeac91bd87742 | Stata | 1,046 | 33 | vlib modelsim_lib/work
vlib modelsim_lib/msim
vlib modelsim_lib/msim/xil_defaultlib
vlib modelsim_lib/msim/xpm
vlib modelsim_lib/msim/fifo_generator_v13_2_3
vmap xil_defaultlib modelsim_lib/msim/xil_defaultlib
vmap xpm modelsim_lib/msim/xpm
vmap fifo_generator_v13_2_3 modelsim_lib/msim/fifo_generator_v13_2_3
vlog -w... |
b178fde8c7f982f1e8f1a2f93ed954fa4ba2b605d844899c02c62b90efcb8a38 | Stata | 8,146 | 225 |
clear
import delimited using "run-1682402668815-part-r-00000.csv", varnames(1) clear
gen variant_category_v2=resol+"_"+variant_cat
rename description variant_category_v1
keep variant_category_v2 variant_category_v1 predicted_effect
* old_variant is currently strL rather than str#. The merge won't work with strL, ... |
4d3fa61aec7bc63ed44551a01d99a3f3f86a78f087313c5de6ae3d821b45dc34 | Stata | 10,335 | 328 | ****************************
****************************
* Identify neutral mutations in a pre-algorithmic step:
****************************
****************************
clear
set more off, permanently
foreach y in complete noNICD {
forvalues a = 1(1)2 {
use "master_data_file_WHOa_`y'.dta", clear
gen byte set... |
b3763a0fb4429786be0a501194021162832ac5bb851c6faa3564606a7fa4a575 | Stata | 13,786 | 412 |
**************
** EPISTASIS
**************
* import catalogue
clear
import excel "List_of_graded_variants.xlsx", sheet("Sheet1") firstrow allstring
save "List_of_graded_variants.dta", replace
* import the final V2 graded catalogue and prep it:
use "Leonid_list_of_graded_variants_25Apr2023.dta", clear
keep if inlis... |
572f41d723aa22954463654194337400962d57d606702be9f67a6ee48dfa5804 | Stata | 17,117 | 567 |
******************
* Apply catalogue to source data to generate stats on predictive performance (sensitivity, specificity)
******************
****************************************************************************************************
***************************************************************************... |
80582c916dadcfdf54a5f2d4f5c304e0b6f7f6f6f68fe64801efe48b6cf46c5f | Stata | 25,688 | 865 |
******************
* Apply catalogue to source data to generate stats on predictive performance (sensitivity, specificity)
******************
****************************************************************************************************
***************************************************************************... |
e72f578f9f683fb7e5d2c6418883161ed1ed5b4d0452c42d2022b4b49a8ce38e | Stata | 70,802 | 1,679 | *0* Start by running the conversion script to prepare the relevant files (LC)
********************************************************************************
run STATA_code_to_convert_old_to_new_nomenclature.do
********************************************************************************
cd FILE_CONTAINING_INPUT_D... |
931e942c518f94cfeed1e3c641e413d8d2e616867804dbf87e6e480c17eeb324 | Text | 11 | 1 | # T1D-NEURO |
77c8e2642b2006aec74fcbb0d4c65c32466c36e59f3de79fc5367ea4a0f633b6 | Text | 20 | 1 | # BehavioralPlatform |
80bf0206d8eba3ca410f4f4ff7cf5d0278c33258da76476e3412c4e0bf6c7251 | Text | 20 | 1 | # Discrimination-CA1 |
77fea422c0a3fd18cf24b286243e964cdf50b0fbb45d57ece4d1be40883eb6f1 | Text | 29 | 1 | DOI: 10.5281/zenodo.18234431
|
5e64538bc9ba77bb3c747845f2c5134d450e230bca70e9347930860a540107d8 | Text | 39 | 1 | # TMS-EEG-Machine-Learning-PLOS-CompBio |
48e3d538b5ec870a9bc150442e0787a4b13d883f48b674b4700ec7af2af214d2 | Text | 53 | 2 | # TyrRu
Code and data used to create images in TyrRu
|
fcae9017e08027c5dca9caaf3d4e70c248710c26e4409208f81620ec93e00d50 | Text | 71 | 2 | # MAND
Mean absolute of n-th difference (MAND) neural feature for BCIs
|
f1b4b629845dfaac5e8432ef3e95bba00fb8f447b20fcb022ad5799d86e47622 | Text | 113 | 2 | # radiomics-mia-vs-iac-4mm
Code and resources for the study: Distinguishing MIA from IAC in GGNs using radiomics
|
f6c519975d642bd9710370a6f159fb791701c91f828ff635b15d12a248a905d6 | Text | 118 | 3 | # PRECOG
Codes from the manuscript: Decoding Neural Signatures of Semantic Evaluation in Depression and Suicidality.
|
5b2c9a47cd94962db2b0b452794d09b6f6cb6acc553f2561c700a3abd84ea564 | Text | 122 | 1 | Code for "Social isolation and loneliness are associated 11 neurological and psychiatric disorders in UK Biobank cohort".
|
27b6a08b7f6a2a1907156f1de66223142517ce22d3301039477e51654f88a50d | Text | 148 | 2 | # MECP2_E2KO_RNAseq
We performed RNA-seq to evaluate the rescue effect of a novel isoform switching strategy to upregulate MeCP2 in human iNeurons.
|
6519b47bdca3fd4c07bf6040399a96b069c0909f9fb411f5b6affa62915cb2fb | Text | 176 | 4 | # bergmann-et-al
Code for Bergmann et al., 2026 J Physiol https://doi.org/10.1113/JP290394
Bergmann et al. also uses the code in https://github.com/aclinlab/calcium-imaging/
|
b75ea453a71d6612804c9eb6f8e2fbe89a3cb56e1e7d55c292c2bd085e150f81 | Text | 178 | 2 | Open source code for the study 'Dissociable dynamic effects of expectation during statistical learning.', published in eLife.
https://elifesciences.org/reviewed-preprints/103689
|
d7bd1d1fe6391a61a0d1fc5274c42a27341e2111c9e2708df0744a3f31878010 | Text | 179 | 2 | # PLSGTEx
MATLAB code, Python code and results for Sex-dependent transcription of cardiac electrophysiology and links to histone acetylation modifiers based on the GTEx database
|
13e742d9b3dd2dfc427fd909d0beaff4678ecab1f7ed75d3693df710ee3d8900 | Text | 205 | 4 | # ASHS
ASHS is a pipeline for Automatic Segmentation of Hippocampal Subfields (and other Medial Temporal Lobe Subregions)
Please see main ASHS documentation at https://sites.google.com/view/ashs-dox/home
|
cb493c451224bc17a897a5f049be7dbdee226ad52e1977499bb0508a2ec8c2d5 | Text | 209 | 5 | # iSTTC
This repository relates to **iSTTC: a novel method for robust and accurate estimation of intrinsic neural timescales** (hyperlink to the paper).
It includes synthetic datasets generated in the paper. |
0e093c79a0aacc34e40e68e4fa80889bf06883c96b5f28062fb596d96a4adddf | Text | 216 | 4 | # Lesser_eLife_2025
Analyses for (eLife, 2025) Peripheral anatomy and central connectivity of proprioceptive sensory neurons in the Drosophila wing
reviewed version of record: https://doi.org/10.7554/eLife.107867.2
|
cd331e8916d5f1f3cbcfa870b948fe806e93b17ba997536aedf82848ffe8de31 | Text | 223 | 4 | # mginoPD
Analysis data for article Macroscale Gradient-Informed Neural Oscillation in Parkinson’s Disease
This repository contains the gradient 1 value for healthy controls in the study which can be used as reference.
|
1b671ee56f5de3775243f29cb58532679495de6df2bd9440a50f2482853bd3cc | Text | 226 | 3 | Data and Code for "Eye Movements Reveal Memory-Related Theta Activity in the Human Brain"
Ensure that Matlab program files and datasets are in the same folder. Scripts ending in "_PlotCode.m" can be run to generate figures. |
1cbd06f8d4ee57e8dec2a1cc257b995cdfb7bd69ac9c9549b81e3cf37dcd61dc | Text | 230 | 7 | **fMRI studies**
=
This folder contains the codes used in my studies.
1. NERS - Common and distinct neurofunctional signatures of dynamic naturalistic emotion regulation strategies (https://doi.org/10.1038/s41467-026-70708-5).
|
591b4efb1b10cef73f74213374d5f22039a732ce00f0f16695e8ea51f4e57ba6 | Text | 231 | 9 | # ARTR-seq
## Dependency
- **cutadapt**, tested with v4.2
- **bowtie2**, tested with v2.4.4
- **STAR**, tested with v2.7.9a
- **UMI-tools**, tested with v1.1.2
- **bedtools**, tested with v2.30.0
- **macs3**, tested with v3.0.0b2
|
1c1f96b9e4a662aa2e99d3a89cc5e8d5d60657c640d0ac8b5312373feda87899 | Text | 270 | 2 | # calcium-imaging
Scripts for analyzing GCaMP imaging data used in [Bielopolski et al., 2019](https://doi.org/10.7554/eLife.48264), [Apostolopoulou and Lin, 2020](https://www.pnas.org/content/117/28/16606), [Amin et al., 2020](https://elifesciences.org/articles/56954)
|
4c0decf086284973b58e4fb3cc226bfbf026596c6a05d157d01733b211eff3e9 | Text | 279 | 10 | # GrimACE manuscript software
## GrimaceRecorder
The GrimACE software application. See [GrimaceRecorder/README.md](GrimaceRecorder/README.md) for installation instructions.
## GrimaceModelTraining
Scripts used for training the ML models that underlie the GrimACE application |
615a8df9b9a057f9b1dc7bbf3e9ef17bea977095f7dfd1281c90af88cb481860 | Text | 283 | 7 | **fMRI studies**
=
This folder contains the codes used in my stuies.
1. NERS - Common and distinct neurofunctional signatures of emotion regulation strategies and their clinical translation in dynamic naturalistic contexts (preprint: https://doi.org/10.1101/2025.05.29.25328539).
|
d5dc38b356f8fc08aa7ee466fda46f457e9cfa229fe9340d0f38a3f26c54812b | Text | 300 | 10 | # Repository structure
- `R/`
Core R functions to run **scTWAS**, **ANTWAS**, and **NATWAS**.
- `toy_example/`
A toy example demonstrating how to run **scTWAS**.
- `realdata_code/`
R code and scripts for Stage 1 and Stage 2 analyses of scTWAS, ANTWAS, and NATWAS in OneK1K and ROSMAP.
|
186e267315971d66e77e2d6698098e64bfe77841c03c0435054e3e77b9e93338 | Text | 331 | 6 | Single-cell spatial map of cis-regulatory elements for disease-related genes in the macaque cortex
For cell-cell pairing of snATAC-seq and spatial transcriptome data, the code is available at https://github.com/sunyk740/... |
b723c0d6b4428bfe4edeed8dd1f86efb74caa9fdaa858505345b5505cb9b3a7b | Text | 355 | 2 | # Learning covariate relations in disease progression models using symbolic neural networks
This repository contain code and simulated data to replicate the method in the paper "Learning covariate relations in disease progression models using symbolic neural networks". For simplicity, each row of the transition probabi... |
220ec983beff5e821e35aaebca9d5894be7c18db9b592a855baec244095215b2 | Text | 388 | 5 | # _Lingula_ genome project - R script
This repository contains an R script that was used to generate figures for our _Lingula anatina_ genome paper.
The preprint is currently available on BioRxiv: Lewin et al. 2024. "Brachiopod genome unveils the evolution of the BMP–Chordin network in bilaterian body patterning" Bio... |
74e103ab4cc984c655fec85f280cd873339613dfb50ba1278b5cb50826e18d39 | Text | 392 | 5 | # TREM2-Metabolomics
Repository for the paper titled: "The TREM2 R47H variant is associated with liver-plasma-brain axis dyshomeostasis in the 5xFAD mouse model of Alzheimer’s disease"
Contains all of the raw data files and R code needed for creating most of the figures in the paper. Pathway analysis figures were gen... |
e7decb7d7af335fb5c470954ef0cc912fb080cf46372803c5ea09735ef14fb77 | Text | 400 | 5 | # Manuscript: Fast and accessible morphology-free functional fluorescence imaging analysis
Authors: Alejandro Estrada Berlanga, Gabrielle Kang, Amanda Kwok, Thomas Broggini, \\Jennifer Lawlor, Kishor Kuchibhotla, David Kleinfeld, Gal Mishne*, and Adam Charles*
Code for reproducibility of LASSO and compression optimiz... |
af4884d3529fe22d05ec132c2a40112ad0bfd82925386e609095b563851ed62a | Text | 410 | 21 | # AggreProt Predictor
- Web page: https://loschmidt.chemi.muni.cz/aggreprot/
- Paper: https://academic.oup.com/nar/article/52/W1/W159/7683054
## Run predictor
Use Python 3.8.
Install the predictor:
```bash
pip install https://github.com/loschmidt/aggreprot-predictor/archive/refs/heads/main.zip
```
Run the predict... |
74dd0562d6c7f5f36076b3154e256c06355d9df7ac777896164153d46198196e | Text | 411 | 18 |
# compress VCF
for vcf in ./s_BCPD-*.noChr.vep.vcf;do \
name=$(basename $vcf .noChr.vep.vcf );
echo $name;
bgzip -c $vcf > $name.noChr.vep.vcf.gz;
done
# index
for vcf in ./s_BCPD-*.noChr.vep.vcf;do
name=$(basename $vcf .noChr.vep.vcf );
echo $name;
bcftools index $name.noChr.vep.vcf.gz;
done
# merge
bcftools m... |
58d9514860dfb8dddb477111e18e4add89ac8679654807d7850979a2f1f669f0 | Text | 412 | 13 | # Introduction
Scripts to reproduce figures and analysis in Yang JC et al., under review.
## Raw data
Can be accessed on NCBI with accession code PRJNA1005265.
## Structure of the repository
- `data` : contains the input files used for the analysis
- `results` : contains the results of statistical analysis
- `src` ... |
519e861d5b41c1df21d5ef275312b970a3efdbc93fbf55bc22d96e0232b769e2 | Text | 422 | 8 | This is the project for the paper:
On-Demand Seizures Facilitate Rapid Screening of Therapeutics for Epilepsy
[https://elifesciences.org/reviewed-preprints/101859v1](https://doi.org/10.7554/eLife.101859)
1) Download the source code from the following location:
2) Set the directory in the MATLAB MAIN file and ALL 4 R f... |
520ff65f994862cd9ef7c1a815ef0177814db4e9f2f63f0c6871a2818d944701 | Text | 432 | 13 | # Reza Filter
**PyPI name:** `reza-filter`
**Python import:** `import reza`
Reza Filter is a **zero-phase, frequency-domain** filter that shapes the spectrum using an exponential-window gain curve. It is designed for clean, practical band/low/high filtering in signals such as **EEG** and **IMU** time series, with ... |
1c50a58054cad9d4ec9efdaf6a119b2ab522fd78902c410d53d6219b21886be7 | Text | 451 | 12 | # paper_historyBias
This repository contains scripts and resources to reproduce Figures 4 and 6 from the paper.
Contents
env_file.txt — specifies the dependencies to create the required Conda environment.
figXyy.py — scripts to reproduce the panels yy of figure X.
figures/ — folder containing the plotted figures ge... |
2f22062692bf0c21fd6943c36c27dba589f341dedf91778326830e796a18db85 | Text | 455 | 14 | "clinical_data.txt" is a .txt table with the following variables:
gender (0 = male, 1 = female)
age (years)
body mass index (Kg/m2)
basal glycaemia (mg/dL)
HbA1c (%)
follow-up (days)
final diagnosis of type 2 diabetes mellitus
Files from "case 1.csv" to "case 208.csv" are the CGMS record ... |
75f11312b64fa83794d9c1078a3c95163d6a7fe2adba680ddc75d4aec738ee37 | Text | 470 | 30 | PointTree_software.zip: the presented software.
dataset_for_training.zip : training data for segmentation network.
MIFT_data.zip: statistical data for Figure 1c.
data_of_difficult_structure.zip: data for Figure 2.
patch_data.zip: data for Figure 3.
data_for_different_SNR.zip: data for Figure 4.
merg... |
a54c5d3d437790cb08a1c948c6e976ae935d300ebe16cb4bbadc3d45d1226e15 | Text | 498 | 21 | # Rolon_Martinez_2024
Python scripts for data analysis of Rolon Martinez et al. 2025 data
# Installation
This code uses [uv](https://docs.astral.sh/uv/) and [marimo notebooks](https://marimo.io) to modularize analysis scripts and handle python version and dependencies.
To get started:
- Install [uv](https://docs.a... |
0d5519fc7c4123681b65548932f134e3dda0993e10467f49cda90adb38a496a5 | Text | 505 | 13 | # VistoSeg <img src="images/logo.png" align="right" width="150px"/>
<!-- badges: start -->
[](https://zenodo.org/badge/latestdoi/333403047)
<!-- badges: end -->
Welcome to `VistoSeg`!
This repository describes steps to run Image processing on Visium histology images for... |
7ff3fac86dbff9ed1eca45c5f403719f8e6c49e6a112fa1a6d9d8bb9ec558a80 | Text | 512 | 5 | # Zebrafish pharmaco-behavioral database
This resource is a database generated by the Hoffman and Wang labs at Yale that catalogs the effect of **774 U.S. FDA-approved drugs** on basic behaviors in wild-type zebrafish. This website provides an **interactive pharmaco-behavioral profiling platform** for researchers to a... |
4b9e881eb9e40f6d7b1924a2adf302f1578ba66449a966bf4347cd969c8e29b3 | Text | 519 | 14 | README
Install the necessary libraries first before running the code. To download all the necessary libraries, please run the following command
`pip install -r requirements.txt`
The "Data" folder contains all the sentence pair datasets
First, run the encoder experimental code Double encoder.py
Then the Cla... |
1feab94d0211c3387bcc1991c57439e21e397d55d42f32a4bc0cb355b80608b5 | Text | 529 | 6 | # inharmonicity_modulation
This is a code repository for the paper 'Non-linear relationships between auditory mismatch responses and the inharmonicity of complex sounds'.
To replicate the results, download the raw data and run scripts in the indicated order. Scripts 00-03 require a parameter (participant ID) to work.S... |
67ccb3a2ec7e422e06ea09deead0fffaa8534e10f83122b9998efba9798ef986 | Text | 541 | 9 | ## LPS-induced inflammation differentially affects endogenous Ca2⁺ activity in mouse and human iPSC-derived astrocytes
### Franziska E. Müller, Flavian Ivanov, Anne-Catharine Studt, Ida Nitzsche, Frauke S. Bahr, Anna-Lena Krüger, Josephine Labus, Ghanendra Singh, Evgeni G. Ponimaskin, Kerstin Lenk* & Andre Zeug*
\* aut... |
3fb4b1ed5c5be22708866b471c287494976a713e967b87e9fa864dbf231ca95d | Text | 546 | 8 | # Organization of neuropeptide systems in the human brain
This is the supporting code for the above publication, now published on [Nature Neuroscience](https://doi.org/10.1038/s41593-026-02236-w).
## `code`
We provide code to replicate all analyses in the manuscript. The scripts are ordered according to their figures,... |
85e26a226119430dde9aca15a2f50f57799b6d77e5f365b9f5c2b6b77a469eac | Text | 550 | 13 | [](https://doi.org/10.5281/zenodo.18373350)
Steps:
- Put the dataset in a GDrive, put the link to the appropriate lines in the code
- Run all of the preparations and utilities cells
- Run DCHE cell
- Run all cells under Genetic Algorithm
- Run GADCHE, which will produce a... |
6ea1f62186dc9ddc799c6c94d83b5673d119336346c94db88795bce78c36e90a | Text | 560 | 15 | # Archived pipeline for Rezaei et al. 2026 (PLOS Biology)
This repository contains the code (and pointers to data) needed to reproduce the analyses and figures in:
### Rezaei et al., 2026. “The retrieval of previously learned motor memories is facilitated by the reinstatement of default mode network manifold structur... |
49da9c5b454c317ca451790b0c600c8022bbbb4e1ad1beca70758516bffd8059 | Text | 642 | 3 | The two scripts recreate the data and figures in the mansucript. There are two files: one (ScriptsPlos_sustained_final.m) is for sustained stimulus and recreates Figures 1-5 and the other is for transient stimuli (ScriptsPlos_Transient_final.m) and recreates figure 6
The codes are written in MATLAB. The number of ... |
94d4a39f52a8d1728ca23861dd87fde00dc86b108289794d1227a5dadfe1c1fc | Text | 699 | 17 | # Blood Glucose Prediction
This repository is still actively under construction!
This is the official implementation of:
Deep learning-based clinical glucose forecasting and hypoglycemia forewarning in type 1 and type 2 diabetes: a multicenter cohort study
## Environment Setup
1. Please create a virtual environmen... |
8e873567137383627e4c167236d3ad086b1cb1259e03d840373d2e959c78e737 | Text | 739 | 5 | # AR-based-Navigation-for-Stereotactic-Brain-Biopsy
Official repository for the AR-based navigation system in stereotactic brain biopsy. Features a multi-objective optimization model for path planning and hybrid registration.
The system consists of two main components:
1. Path Planning Module (Python): Implements a co... |
8cf3176f10ba6f8ceb0df20f660a5d6db4b414cb673c6104116a36e08c11ea2a | Text | 878 | 13 | # musicnf-novelinterface
**Music as a real-time fMRI neurofeedback interface for modulating interhemispheric connectivity: effects on mood and recruitment of the putamen and insula**
Here, we present and validate a musical interface for real-time fMRI neurofeedback, applicable in various experimental protocols. The ... |
fec4bbe5c38d872c8d1a59d90dc001eaa347f9d16f7414335843d82354ccec17 | Text | 879 | 21 | psignifit
=========
Toolbox for Bayesian psychometric function estimation
(c) Heiko Schütt, AG NIP, University of Tübingen
www.wichmann-lab.org
with help from Stefan Harmeling, Jakob Macke and Felix Wichmann
This program is free software: you can redistribute it and/or modify
it under the ter... |
1ab494c8804f5cb54ee9116f5afb652c95da045c6b65d430535cdbacfc07a59c | Text | 882 | 37 | # About
- Related Publication: Cloud et al. (under review). Cardiorespiratory fitness is differentially associated with motor cortex laterality in middle-aged and older adults.
## 01 - Imaging Analysis
Goal: Analyze preprocessed VISMOTOR fMRI data, generate left and right hemisphere motor ROIs, and extra beta coeff... |
8e6b1f025a6dac1d7fdfac27cc00930eebd12ea419fc65ca6dd5fb7ba99a5587 | Text | 893 | 27 | # SPMLMI
**SPMLMI: Predicting lncRNA–miRNA interactions in humans using a structural perturbation method**
**If you use this tool, please consider citing the following publication: https://doi.org/10.7717/peerj.11426**
# Data：
- ML_matrix: Known interaction pairs between miRNAs and lncRNAs.
- LS: The lncRNA similar... |
28cc4439be474dcef5d10a122d7a92c56b4d7261674f6107dd77d4f81ad6fc62 | Text | 940 | 16 | **Segmentation and characterization of retinal hyperreflective foci on OCT using deep learning**
This repository provides a deep learning–based framework for automatic segmentation of retinal HRF from OCT images. The framework includes model architecture, training, and evaluation pipelines designed for reproducible re... |
5f547f1aac93a7b31a2ad63d678f7a5fc830a03a7b61af4355f783d6d8063798 | Text | 954 | 16 | # craniofacial_snrna
# Code related to processing and analyzing snRNA-seq data from human and mouse craniofacial development.
<img src="overview.jpg" alt="Graphical Abstract">
Scripts for clustering, removal of neuronal cell types, and annotation of cell types in both human and mouse are found in the clustering direct... |
c858b86fa96ba0b23d504fc27e30a50143eaddfc95b800b167b993c5550220af | Text | 985 | 11 | Data repository to the paper "qsGW quasiparticle and GW-BSE excitation energies of 133885 molecules". The zip files correspond to the following properties:
e_qp.zip --> qsGW quasiparticle energies (in eV)
e_exc_ss.zip --> Lowest 5 GW-BSE singlet-singlet energies (in eV)
e_exc_st.zip --> Lowest 5 GW-BSE singlet-triplet... |
8c24d0924445e4de49f1da6823e47cdbeb53b8c24d104bdcf7deb1026f892e22 | Text | 987 | 22 | # 2026_multib_paper_AlfaPLUS
MATLAB scripts used in the analyses for the manuscript:
Kassinopoulos et al. (2026). Intracellular fluid accumulation underlies brain volume increases in early Alzheimer’s disease. Brain Communications.
The full manuscript, including methodological details, is available through Brain Comm... |
994132190cecf499e36ecfe50dddd52f3163765341fb88476e2f946c0486d072 | Text | 995 | 18 | # Learning the bistable cortical dynamics of the sleep-onset period
This repository contains code to reproduce analyses and selected figures for the preprint **“Learning the bistable cortical dynamics of the sleep-onset period.”** The paper introduces a minimally parameterized stochastic dynamical model in which a slo... |
2e3294e449ec0967e58a9211503a3b16cdd657aa353962e03e2cc954fc8945c4 | Text | 1,005 | 22 | # Linelength-spike-detector
Detects abnormal events in brain wave data (namely, interictal spikes in EEG data) using a linelength transform algorithm.
Transforms data into linelength then detects events (spikes) surpassing
the designated percentile threshold. Note that this function assumes any
detections in any chan... |
16358f6d75ae0c04cd593c14fd03ddc3313c4e81ad67004d207f6fcb4ee88acf | Text | 1,021 | 27 | Sinto: single-cell analysis tools
=================================
.. image:: https://github.com/timoast/sinto/workflows/pytest/badge.svg
:target: https://github.com/timoast/sinto/actions
.. image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat
:target: http://bioconda.github.... |
166afd46716872fe4911ee38fc73e19217589bcc5624ada1217404bc7b2e5e18 | Text | 1,038 | 18 | # mesh-sig-detect
Time to signal analysis for spontaneous report data on pelvic mesh medical device
# Data source
The data is thanks to [curtis-murray](https://github.com/curtis-murray) at hi... |
c680ed9026af57acba541f539c1139b4df3ddccb1112129167cb2008d061e7b0 | Text | 1,050 | 24 | # 🧠 BRAIN AGE MODELS BENCHMARK
A comprehensive framework to benchmark, analyze, and develop brain age prediction models using neuroimaging data.
Overview
Brain Age Benchmark is an open-source repository dedicated to:
🧪 Evaluating the performance and bias of existing models for brain age prediction
🧠 Developing no... |
6dfd1b80900a6259b9f79f03bdde185cf3e0da6491b7a126d1d4d0669d8fc287 | Text | 1,083 | 23 | # Electrophysiology Analysis and Figure Generation — Bertelsen et al. (Dec 2025)
This repository contains all the code required for the analysis and generation of figures presented in the paper:
**Bertelsen et al., New Version, December 2025**.
## Folder Overview
- **Ephys-Analysis-main**
Code for processing an... |
773f061802a012a56df116923ec1ba0d51bbb40292fa71da45a4bd9bed8f1531 | Text | 1,097 | 23 | RELION 5.0.1
============
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... |
667c602298183fe9613f4b9b1794db2e89923f421b3cd4d1af32d8d311a6e591 | Text | 1,182 | 23 | ## Dataset
This repository contains numerical data used to plot figures in the manuscript entitled:
"Time-Resolved EEG Decoding Reveals Altered Neural Dynamics of Affective Semantic Evaluation in Depression and Suicidality."
## File Descriptions
`Latency_measure.mat`: Latency values for "agree", "disagree", "Type ... |
b09b3fcb392b5670f5683840273f19fc1ef46ee5e2f915542952eaa50d6980df | Text | 1,198 | 26 | # Dataset SHTE_V1
This dataset is built based on the Sposobin's Harmony Textbook Exercises(SHTE). This is the Version 1.0.
## Description
This dataset is derived from the exercise answers provided at the end of Chapters 1–19 of Sposobin. Each entry has been proofread by professional musicians. We manually entered eac... |
e90c5d9fd24e0742c67a9d228a167e49849b1a95a5f02d8807cd3e2be1697d28 | Text | 1,202 | 43 |
# TRN_MGB_celltypespecific
Models to accompany Rolon-Martinez et al.
---
# Paper link
[doi](url)
---
# Model usage
follow matlab setup -> [Here](docs/Matlab%20setup.md)
make a new directory for simulation run.
Copy src model files to new simulation directory.
edit the Run_dsim.m template script.
Visualize v... |
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