Bar, Ido

9 files · 8.0 MB · gff, gzip

These files are downsampled WGS fastq files (250k paired-end reads each) of a fungal pathogen ( Ascochyta rabiei ), generated on MGI DNSeq-T7. The files are intended to be used directly as test datasets in PopFun - a Nextflow pipeline for variant calling in fungal genomes.

Yang, Qingliu

6 files · 8.0 MB · bzip2

Dataset Description This dataset contains 3D lightning location results, DALMA and FALMA waveform for two Energetic Compact Stroke (ECS) events. location results are included: HF3D_1732785151.dat - 3D lightning locations for the ECS leader A flash. HF3D_1734785454.dat - 3D lightning locations for the ECS leader B flash. The timestamp 1734785454 and 1732785151 corresponds to the occurrence time of the lightning flash in Japan Standard Time. File format and parameters The first row contains the lightning occurrence time. Column descriptions: Time (ms) - time relative to the lightning source. X, Y, Z (m) - 3D spatial coordinates relative to ground level. The origin (0, 0, 0) corresponds to latitude 36.76°N and longitude 136.76°E. FALMA and DALMA waveform ECSLeaderA_DALMA_waveform.bz2 is DALMA waveform of Leader A. ECSLeaderA_FALMA_waveform.bz2 is FALMA waveform of Leader A. ECSLeaderB_DALMA_waveform.bz2 is DALMA waveform of Leader B. ECSLeaderB_FALMA_waveform.bz2 is FALMA waveform of Leader B. This dataset allows analysis of the spatial and temporal development of these two ECS flashes.

Cai

12 files · 8.0 MB · npy

Lopez Dubon, Sergio · Sgarabotto, Alessandro · Lanzoni, Stefano

11 files · 38 MB · hdf5, npydeclared

This record contains the trained autoencoder, extracted encoder, and processed world/real-river latent-space reference cloud associated with the manuscript *A data-driven approach to discern the curvature spectral complexity of compound meander bends*. The full autoencoder is provided to support reconstruction-based validation and reproducibility of the learned representation. The extracted encoder is provided for inference and future software tools. It maps preprocessed 64 × 64 single-channel curvature-spectrum images to the two-dimensional latent space used to analyse meander shape complexity and skewness. The file `world_latent_cloud.npy` contains the two-dimensional latent coordinates of the world/real-river meander dataset used as the reference background cloud in the manuscript latent-space figures. This file is a processed latent-coordinate dataset only; it does not contain raw satellite imagery, raw centreline geometries, or training images. The release includes model weights, architecture files, model summaries, export metadata, the world/real-river latent cloud, example inference scripts, a validation script, environment files, and a minimal example input. The models should only be applied to curvature-spectrum images generated consistently with the preprocessing workflow described in the associated manuscript. Main files included in this release are: - trained_autoencoder.h5: full trained autoencoder. - encoder_only.h5: extracted encoder in HDF5/Keras format. - encoder_only.keras: extracted encoder in native Keras format. - model_architecture.json: full autoencoder architecture. - encoder_architecture.json: encoder architecture. - model_summary.tx and encoder_summary.txt: layer summaries. - world_latent_cloud.npy: world/real-river reference latent-space cloud. - world_latent_cloud_metadata.json: metadata for the world/real-river latent-space cloud. - model_card.md: intended use, inputs, outputs, limitations, and citation guidance.

Ou, Te-Yu · Gu, Rong-Yu · Jang, Yi-Shin · et al.

26 files · 2.2 GB · csv, netcdf, npydeclared

Version history Version 2: This version updates Figure1.py and MainFigure.ipynb to match the revised manuscript submitted to Geophysical Research Letters. Specifically, a scale bar was added to Figure 1. No changes were made to the input datasets, analysis workflow, or scientific results. Code All results were analyzed and visualized by Python version 3.9.18. Filename Description MainFigures.ipynb Jupyter Notebook for reproduce all figures in the article. Figure*.py Python file for reproduce each figure in the article. Data Ground Station Observation Filename Description 467530_hr_19800101_20230101.csv Alishan station data managed by Central Weather Administration (CWA) of Taiwan, which is generated from Atmospheric Science Research and Application Databank . Solar Radiation Reduction Ratio (RR SR ) Results Filename Description ReductionRatio_20151001_20220930_31_daily.nc RR SR of Taiwan (119.9°E-122.1°E, 21.8°N-25.4°N, 0.01° x 0.01°) from 2015-10-01 to 2022-09-30, which is generated from TCCIP Grid-point Surface Insolation Derived from Geostationary Satellite Dataset . *_hr_20151001_20220930_seasonal.csv Seasonal mean RR SR for 6 CWA stations (Alishan, Anbu, Yushan, Sun Moon Lake, Chiayi, and Keelung). *_hr_20151001_20220930_DJF_NE_means.csv Winter (December-February) event-mean RR SR for 6 CWA stations (Alishan, Anbu, Yushan, Sun Moon Lake, Chiayi, and Keelung). Land and Non-rainy Mask Filename Description LandNonRainyMask_2015_2022.nc Mask for land area and non-rainy data, which is generated from TCCIP Gridded Historical Daily Dataset for Taiwan . Land-type Classification Generated from Schulz et al. (2017) . Filename Description MCF2017.zip Shapefile of montane cloud forests (MCFs) region in Taiwan. nonMCF2017.zip Shapefile of forest region other than montane cloud forest in Taiwan. MCFfraction_TCCIP.npy Forest classification in Taiwan regrid to TCCIP dataset. North-easterlies events classification Adopted from Taiwan Atmospheric Event Database . Filename Description TAD_NE.csv North-easterlies events classification based on the criteria of Taiwan Atmospheric Event Database (TAD). Others Generated from Open Data in Taiwan . Filename Description Taiwan_WGS84.zip Shapefile of coastlines of Taiwan. dem20_TCCIPInsolation.nc Digital Elevation Model of Taiwan regrid to TCCIP dataset. Note Please unzip .zip first to get shapfile before reproduce the figures in the article.

Meekes, Lisa · Tabaro, Francesco · Bexkens, Michiel · et al.

41 files · 8.2 GB · csv, fasta, pdfdeclared

This record contains the Python software for PEPTiGEN, a tool for generating tryptic peptides from prokaryotic gene sequences and their variants, and the associated antimicrobial resistance (AMR) peptide database. The database is provided as an SQL file and a CSV file containing all genes and predicted peptides. The README file contains explanation of the PEPTiGEN tool. The SQL database schema files contains both the database schema of the SQL database used in the PEPTiGEN analysis as the database schema of the AMR peptide datbase.

Flowerdew, Jake

6 files · 1.3 GB · csv, npydeclared

Voltage calibration data taken on 10/06/2026 of all ten 10 MHz PS cavities (exluding the spare C11). Measurements were taken, pulsing each cavity individually at harmonics h7 - h21 and voltages of 10 kV, 12.5 kV, 15 kV, 17.5 kV and 20 kV. Note, due to cavity trips, no useful data was collected for C10-46 and C10-86.

Liu, Yixuan · Meyer, Renate · Christensen, Nelson · et al.

10 files · 2.0 GB · gzip, npydeclared

LISA Data data.npy (original data) true_matrix.npy (true PSD) true_freq.npy (frequencies for the true PSD) ET data caseA_original.RData (original data) caseA_nlized.RData (normalized data) caseA_true_psd.RData (true PSD) caseA_freq_psd.RData (frequencies for the true PSD) caseA_mpg_orig.RData (periodogram of the full data) caseA_freq_mpg.RData (frequencies for the periodogram of the full data) vnpc.avg_0.1.0.tar.gz (source file for the R-package vnpc.avg used in the main paper)

Kim, Kyurhi

10 files · 9.6 GB · bzip2, zipdeclared

This repository contains cis-xQTL mapping results, colocalization analysis results, and transcriptome-wide association study (xTWAS) weights and association test statistics for six transcriptomic modalities generated from bulk RNA-seq data of dorsolateral prefrontal cortex (DLPFC) tissue from the ROS/MAP cohorts (n = 1,035). The RNA trait tables (BED format) used for cis-xQTL mapping and xTWAS model training were generated using the Pantry pipeline but are not included in this repository. Colocalization and xTWAS analyses were performed using the publicly available Alzheimer's disease (AD) dementia GWAS summary statistics from Bellenguez et al. ( Nature Genetics , 2022).

Fairlie Reese

9 files · 16 GB · gff, tsvdeclared

master_table_pcg_lnc.tsv: Metadata / information about each transcript isoform (filtered for protein coding and lncRNAs only) merged.gtf: GTF of transcript isoforms transcript_tpm_summary.tsv: TPMs of each transcript isoform PFAM-Filtered-Merged.txt: PFAM domains called in each predicted ORF sequence from each transcript. Filtered for quality and confidence. fetal_dhs_info.tsv - genomic locations of all DHSs, distance from nearest TSS, gene associated with nearest TSS fetal_matrix_binary.tsv - binary matrix with samples (rows) x DHSs (columns) with 1 indicating the presence of a peak in that DHS in that sample at an FDR of 1% fetal_matrix_density.tsv - matrix of read depth normalized counts fetal_matrix_vst.tsv - matrix of vst normalized counts (like deseq) fetal_meta.tsv - metadata of fetal samples, should include the ln_number for DNase, which wil match the rows of the matricies, and the per sample matching ln_number and other identifiers for short read and long read RNA seq, as indicated by the column titles

Allendorf, Daniel · Bläsius, Thomas · Leonhardt, Alexander · et al.

2 files · 12 GB · bzip2, zipdeclared

About this Repository This repository contains the software, datasets, and experimental data to reproduce the experiments in the above mentioned article. Please refer to the README file for more details and instructions. Article Abstract We consider a maximum entropy edge weight model that allows for negative weights. Given a graph Gand possible weights W typically consisting of positive and negative values, the model selects edge weights w ∈ W^m uniformly at random from all weights that do not introduce a negative cycle. We propose an MCMC process and show that it converges to the required distribution. We then engineer an implementation of the process using a dynamic version of Johnson's algorithm in connection with a bidirectional Dijkstra search as well as an innovative resampling method. We empirically study the performance characteristics of these novel sampling algorithms as well as the output produced by the model. Dataset Most of the input data (graph data) is generated dynamically via random graph models. In addition to the result data from the experiments, unew.data.tar.bz2 also contains trimmed US road networks used for the ROAD dataset in the paper. Code The code is developed at https://codeberg.org/lukasgeis/unew --- you may want to check there for updates.

OpenFF, YDS

18 files · 334 MB · bzip2, csv, pngdeclared

Generated by yammbs-dataset-submission: https://github.com/openforcefield/yammbs-dataset-submission

Formaggioni, Alessandro

6 files · 3.4 GB · fasta, gff, zipdeclared

Genome assembly of Cardita leana (Bivalvia: Archiheterodonta) and the associated gene models predicted with AUGUSTUS. The 'Tree' folder contains species trees inferred using different tree reconstruction programs. The MCMC_analysis folder contains inputs and ouputs for every MCMCTree analysis

Pastor Durántez, Eduardo · Diez Casero, Julio Javier

2 files · 15 MB · gffdeclared

Curated, high-confidence structural gene annotation of Phytophthora plurivora (strain TJ71), provided in GFF3 format (15,415 gene models; gene, mRNA, exon, and CDS features). The annotation was generated with a BRAKER3-based structural prediction pipeline, followed by a custom curation workflow combining transcript deduplication, repeat- and expression-aware filtering, a heuristic homology-and-topology scoring scheme, and directed manual curation. This dataset was produced as part of the associated manuscript describing the genome annotation and two-speed genome architecture of P. plurivora . This annotation is built on the previously published genome assembly available at NCBI GenBank under accession ASM3002794v1. The genome FASTA itself is not included in this deposit. See the accompanying README.txt for full file description, methods summary, and locus tag conventions.

Jensen, Anders

60 files · 7.4 GB · netcdf, npydeclared

See the readme

Ji, Junyi

5 files · 14 MB · npydeclared

Yang, Xin · Wang, Yifei · Yang, Shengyong

8 files · 95 GB · gzip, npydeclared

Tekpinar, Mustafa

1 files · 85 MB · bzip2declared