Hubbard, Alfred · Solares, Edwin · Hemming-Schroeder, Elizabeth

88 rows · 18 KB · fasta

These are the files needed to run the Broad Institute's malaria amplicon pipeline for the PvGAP Plasmodium vivax panel, described in detail here . They consist of FASTA files containing the forward and reverse primers and another FASTA file containing reference sequences for each target, derived from the PvP01 reference genome.

Yuan, Guangyuan

72 rows × 13 cols · 6.0 KB · csv, fasta

11 numeric · 2 categorical

This dataset supports the findings of the manuscript "Root anatomical traits modulate the assembly and nitrogen transformation potential of root-associated microbiomes in a temperate steppe" (NPH-MS-2026-55667). It contains root traits data, bacterial 16S rRNA gene absolute abundances, functional genes relative abundances, DNA extraction metadata, and phylogenetic marker sequences for 37 plant species from a temperate steppe ecosystem. The dataset includes the following files: 1. root traits.csv - Root traits including average diameter (AD), specific root length (SRL), specific root area (SRA), root tissue density (RTD), root nitrogen content (RNC), root carbon content (RCC), carbon‑nitrogen ratio (RCN), cortex layer number (CLN), cortex thickness (CT), and the ratio of cortex thickness to root diameter (CTRD). The first column lists plant species names. 2. Absolute abundance of 16S rRNA gene.csv - Quantitative PCR (qPCR) derived absolute abundances of bacterial 16S rRNA gene copies (copies/ng DNA) across different root compartments (rhizosphere, rhizoplane, endosphere), host species, root orders, and cotyledon classes (monocot/dicot). 3. DNA extraction sample weight.csv - Fresh weight (grams) of root material used for DNA extraction for each sample, linked by SampleID to the abundance data. 4. DNA extraction concentration.csv - Qubit‑measured DNA concentrations (ng/μL) and the sample volume (μL) used for quality control, together with sample metadata. 5. 37species.fasta - DNA sequences of two chloroplast markers (matK and rbcL) for the 37 plant species included in the study. The sequences are in FASTA format with headers formatted as ">Species". These were used for host phylogeny construction and Pagel's λ analyses. 6. Quantitative PCR results of functional gene.csv - Quantitative PCR (qPCR) derived relative abundances of bacterial 16S rRNA gene and functional genes across different root compartments (rhizosphere, rhizoplane, endosphere), host species, root orders, and cotyledon classes (monocot/dicot). 7. README.md - A detailed description of each file, column headers, abbreviations, units, and any missing value codings (NA). All data are provided to ensure transparency and reproducibility of the analyses. For methodological details, please refer to the Materials and Methods section of the associated publication. These data are under embargo until the associated research article is published. After that date, they will be freely available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. During the embargo period, the metadata (title, authors, abstract) and the DOI remain publicly visible, but the data files are not accessible. For access requests before the embargo expires, please contact the corresponding author.

Altenhoff, Adrian

6 files · 100 MB · hdf5

OMAmer - tree-driven and alignment-free protein assignment to subfamilies OMAmer is an alignment-free protein family assignment method designed to avoid overly specific subfamily predictions and to scale efficiently to phylogenomic databases containing thousands of genomes. It relies on an innovative approach that uses evolutionarily informed k-mers for alignment-free mapping to ancestral protein subfamilies. This dataset provides precomputed OMAmer databases derived from the Hierarchical Orthologous Groups in the OMA Browser . We aim to update these databases with every new OMA Browser release. Each OMAmer database is built using the latest version of the OMAmer package available at the time of the corresponding OMA Browser release. The dataset includes databases for different subsets of the species taxonomy. In most cases, we recommend using the LUCA.h5 database, which contains information from all species in the OMA database. The subset-specific databases are mainly useful when disk space is limited. The release May2026 is based on the OMA Browser release May 2026 which comprises 2983 species. We used OMAmer version 2.1.0 to build these databases.

Requena Rolanía, Jose María · Greif, Gonzalo · ROBELLO, CARLOS

1 files · 8.0 MB · fasta

This dataset contains the genome sequence for Trypanosoma cruzi (strain Dm28c). This genome sequence was de novo assembled using PacBio Hi-Fi and Illumina sequencing platforms by Greif et al (2026. PMID: 41501640). The genome was assembled into 32 contigs, which represent complete chromosomes. The provided Fasta file also contains an additional contig corresponding to the maxicircle (mitochondrial genome) sequence. The Fasta files included in this dataset were downloaded from GenBank (assembly GCA_044048535.1; May 22, 2026). Additional information about the Dm28cT2T genome assembly and gene annotations may be accessed through the link: https://cruzi.pasteur.uy/

Burman, Nathaniel · Buyukyoruk, Murat · Wiegand, Tanner · et al.

4 files · 8.0 MB · fasta

This folder contains a multiple sequence alignment of Cas7 homologs in .fasta format, the domain-level annotations from PFAM and CasFinder, and an associated phylogenetic tree in .newick format.

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.

Kovaliov, Michael

1 files · 100 MB · parquet

Madhusudan, Gujral

6 files · 29 MB · parquetdeclared

Large language models (LLMs) are trained on massive, publicly available text datasets comprising trillions of tokens, enabling them to excel at general language tasks like next-token prediction. However, LLMs often struggle with domain-specific prompts, exhibiting reduced accuracy or generating inaccurate information (hallucinations). This is because they lack sufficient subject matter expertise. Two primary approaches exist to address this limitation for augmenting LLMs knowledge: Retrieval-Augmented Generation (RAG) and fine-tuning. This presentation focuses on fine-tuning smaller LLMs with domain-specific instruct datasets using the LoRA (Low-Rank Adaptation) technique on Gaudi hardware. We will leverage publicly available LLMs and datasets from the Hugging Face Hub for this demonstration. Though it is possible to fine tune LLMs with plain text data - sourced from documents, articles, and other materials.

Hackl, Jürgen

6 files · 132 MB · parquet, tiffdeclared

EuroFlood is an open, cloud-native index over the JRC/Copernicus CEMS-EFAS Satellite-Derived Flood Depth Maps for Europe (Betterle & Salamon, 2025; CC-BY-4.0) - ~3,280 satellite-derived observed flood-depth maps across Europe, 2015-2024. The bundle is a sparse Cloud-Optimized GeoTIFF encoding, per pixel, the set of flood events that inundated it, plus a combo_id -sorted GeoParquet dictionary and a small events table. Query by region and time via HTTP range reads (GDAL /vsicurl + DuckDB) to retrieve matching events, then fetch only the source depth rasters needed. Built with the open-source EuroFlood Python package ( pip install euroflood ).

Zhang, Yunwei

6 files · 40 GB · hdf5, zipdeclared

Files related to INVNET, a deep learning model for surface wave dispersion spectrum inversion in geophysics.

Tiskus, Edvinas · Tiškuvienė, Rūta · Bučas, Martynas · et al.

37 files · 1.6 GB · hdf5, tiff, torchdeclared

This record contains the labeled data, trained models, and analysis code supporting the article "Comparing a Vision Foundation Model (DINOv3) and a Task-Specific U-Net for Mapping Emergent Aquatic Vegetation from Fused UAV Multispectral and LiDAR Data" (Remote Sensing in Ecology and Conservation). Contents: - masks/ : georeferenced ground-truth segmentation masks (five classes: aquatic vegetation, water, sand, other objects, background), aligned to the fused UAV orthomosaics and spanning 13 sites across nine Lithuanian waterbodies surveyed between May and August 2024. - models/ : the two final trained segmentation models, a Keras/HDF5 U-Net and a PyTorch DINOv3 model. - code/ : Python scripts for training, evaluation, the label-efficiency experiment, and full-scene prediction. The fused 9-band orthomosaics (five-band multispectral, RGB, and a LiDAR canopy height model; approximately 62 GB) are archived separately because of their size and are available from the corresponding author on request. The DINOv3 SAT-493M pretrained backbone is distributed by Meta under its own license and is not redistributed here; obtain it from the official DINOv3 release.

Vines, Jose I.

1 files · 3.0 GB · hdf5declared

Pre-computed, resolution-broadened (R=1500) stellar atmosphere spectra cache for the astroARIADNE SED fitting package. Contains 7 model grids (Phoenix v2, BT-Settl, BT-NextGen, BT-Cond, Castelli & Kurucz 2004, Kurucz 1993, Coelho 2014) resampled to a common logarithmic wavelength grid (0.125-4.629 µm). This cache eliminates the need to download the full ~770 GB model libraries for SED plotting.

Njie, Adama · Torkayesh, Ali E · Venghaus, Prof. Dr. Sandra

10 files · 1.6 GB · csv, gzip, parquetdeclared

Structured, speaker-attributed corpus of all German Bundestag plenary session transcripts ( Plenarprotokolle ) from the first legislative period to the present (WP01-WP21, September 1949 - April 2026). Every attributed speech is extracted from the official PDFs published by the Deutscher Bundestag under open data policy and linked to the speaker's name, parliamentary role, party affiliation, and gender. Scale: 4,611 sessions · 1,033,723 speeches · 4,205 identified MdBs · 76 years of parliamentary debate Dataset files speeches.parquet - one row per attributed speech: speaker name, role, party, gender, stammdaten_id, full German text (~1 GB) persons.parquet - one row per MdB: cross-session identity linking all name variants via stammdaten_id; canonical name, birth date, career span, total speeches. Use this - not speakers.parquet - for person-level analysis sessions.parquet - one row per plenary session: date, city, Wahlperiode, source PDF hash, extraction engine speakers.parquet - name-string index: one row per unique name string as extracted from the transcripts. Useful for understanding extraction quality; not suitable for person-level aggregation (the same politician often appears under several name variants across sessions) parties.csv - reference table of 31 German parliamentary parties, 1949-present speeches.csv.gz - CSV fallback for Stata and Excel users (same columns as speeches.parquet) datapackage.json - Frictionless Data schema with column descriptions and foreign key constraints Cross-session identity The same politician often appears under different name strings across sessions (e.g. "Schmidt", "Dr. Schmidt", "Frau Dr. Schmidt"). Cross-session person linkage is provided via stammdaten_id , matched against the official Bundestag Stammdaten biographical XML. The persons.parquet table aggregates all name variants for the same MdB into one row with correctly summed speech counts, career span, and birth date. Coverage: ~98.5% of speeches are linked to a stammdaten_id; the remaining ~1.5% are ambiguous surname-only attributions or speakers not in the Stammdaten. Coverage and sources Source PDFs are the official Stenografische Berichte downloaded from the Bundestag open-data portal (bundestag.de). Party-share normalisation in the corpus statistics uses official seat counts per Wahlperiode sourced from the Federal Returning Officer (Bundeswahlleiter, bundeswahlleiter.de). Two PDF generations are covered: scanned and OCR'd documents (WP01-WP09, Bonn era, 1949-1987) and born-digital documents (WP10-WP21, 1987-present). The engine column in sessions.parquet flags whether pdftotext (born-digital) or pdfminer (OCR fallback) was used; this is the primary data-quality indicator for NLP use. Speaker attribution Each speech is attributed using four patterns extracted from the transcript format: presiding officers (Präsident/in, Vizepräsident/in), regular members (name + party), government officials (name + Bundeskanzler/in, Bundesminister/in, etc.), and procedural roles (Berichterstatter/in, etc.). The party field is null for ~60% of speeches - this is expected, as presiding officers and ministers are not identified by party in the transcript. Gender annotation & distribution Gender is derived by matching speaker names against the official Bundestag Stammdaten biographical XML (all MdBs since 1949), with fallbacks for role title, honorific prefix, manually researched overrides, and a gender_guesser first-name heuristic. The gender_source column distinguishes stammdaten (authoritative, 83%), role_title (gendered job title in attribution, 6.4%), title_prefix (Frau/Herr honorific, 0.5%), manual (historically researched, 2.9%), and inferred (name-based heuristic, 4.7%). Gender distribution: Female 26.6% · Male 73.4% · Unknown 0.0%. Data quality All speeches pass automated validation: zero null speaker names, zero sequence gaps, zero CID artefacts, zero party-misclassified-as-Bundesland errors. Eight sessions with conflicting source PDFs were deduplicated (first lexicographic occurrence retained). 252 non-person names incorrectly accepted by the parser (table headers, legislative terms, agenda fragments) are excluded at build time via a curated exclusion list. OCR sessions (WP01-WP09) may contain Unicode replacement characters (U+FFFD); the engine field identifies these sessions. Licence CC BY 4.0. The underlying Plenarprotokolle are official government documents of the Deutscher Bundestag and are in the public domain.

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.

abdulwahab, samaa · aduallah, mahmood z. · Sallomi, Adheed H.

34 files · 2.7 GB · csv, gzip, parquetdeclared

Intrusion-detection research on Internet Protocol version 6 (IPv6) remains bottlenecked by the scarcity of labelled, protocol-aware flow datasets. Existing machine-learning IDS benchmarks are overwhelmingly IPv4-centric, and the few IPv6 corpora that have been released target narrow attack families or rely on small academic testbeds that cannot be re-created by third parties. We present IPv6-CyberBench, a reproducible eight-phase pipeline that constructs a large, protocol-aware translated-flow corpus by harmonising CIC-IDS-2017, CIC-IDS-2018 and CIC-DDoS-2019, applying deterministic IPv4→IPv6 address translation (6to4, NAT64, Teredo, EUI-64), synthesising 27 IPv6-specific flow features grouped in six protocol families, enforcing nineteen RFC-derived constraint categories together with temporal address dynamics, and rebalancing the long-tailed class distribution with a feature-group-conditioned per-class Wasserstein-GAN-GP augmenter and a SMOTE-KDE fallback selected per class by a formal decision rule. We scope the contribution honestly: because the seed corpora are IPv4 captures, the resulting 2,285,774-record benchmark is a translated-flow corpus suitable for training and evaluating flow-level IPv6 IDS classifiers on flooding, brute-force, scan, web-attack and infiltration traffic under IPv6 protocol-header semantics, and for studying IPv6-specific feature engineering and address dynamics in a reproducible setting. It is not a substitute for protocol-native IPv6 attack capture, and we explicitly exclude ICMPv6 Neighbour-Discovery flooding, SEND flooding, NDP exhaustion and extension-header covert-tunnelling from the threat model. The benchmark is evaluated on four axes - fidelity (Kolmogorov-Smirnov, MMD, Fréchet feature distance), utility (stratified 5×5 nested cross-validation over six classifier families including CNN-LSTM and LightGBM), privacy (Shokri-style membership-inference advantage AUC), and external fidelity against a 24 h anonymised CAIDA IPv6 trace (equinix-chicago, US backbone) and a MAWI samplepoint-F trace (WIDE backbone, Tokyo, Japan). The full pipeline, the hyper-parameter manifest, the RFC-constraint manifest, the reproduction scripts, and the 2,285,774-record benchmark are released unconditionally on Zenodo under CC BY 4.0; the dataset and pipeline are openly available at https://doi.org/10.5281/zenodo.19503446 (CC BY 4.0).

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.

Barreto, Bruno · Eisencraft, Marcio

3 files · 2.6 GB · parquetdeclared

This dataset provides a fixed benchmark dataset for stellar atmospheric parameter estimation from Sloan Digital Sky Survey Data Release 12 (SDSS DR12) optical stellar spectra. The dataset is organized into three predefined Parquet splits: 30,000 spectra for training, 5,000 spectra for validation, and 15,000 spectra for testing. Each row corresponds to one SDSS stellar spectrum and includes raw spectral arrays, fixed-length processed spectral features, source identifiers, basic metadata, and catalog stellar-parameter labels with their associated uncertainties. The supervised regression targets are the adopted catalog stellar atmospheric parameters: effective temperature (Teff, in K), metallicity ([Fe/H], in dex), and surface gravity (log g, in dex). The dataset also includes relevant observational and catalog information such as SDSS plate, MJD, fiber identifier, sky coordinates, signal-to-noise ratio, adopted radial velocity, raw flux, logarithmic wavelength grid, inverse variance, pixel mask, and processed flux features. This release is intended to support machine-learning research on stellar spectroscopy, including regression models for atmospheric parameter estimation, benchmark comparisons, uncertainty-aware evaluation, and experiments using either processed fixed-length spectra or native observed-frame spectral arrays.

Saldanha, Raphael

8 files · 601 MB · parquet, zipdeclared

Description This deposit contains annual, municipality-level datasets derived from the Brazilian Primary Health Care Information System (SISAB). The files combine two complementary data sources: Public SISAB Saúde report downloads from the Atendimento/Visita production report. CID-10 and CIAP-2 attendance data obtained from SISAB through requests under the Brazilian Access to Information Law (Lei de Acesso à Informação, LAI). The datasets are organized as tidy annual files in CSV (Zipped) and Parquet format. They are intended to support reproducible analysis of primary care production, procedures, evaluated problems/conditions, and CID/CIAP-coded attendances across Brazilian municipalities. The public SISAB report datasets are stratified by competence month, state, municipality, DataSUS age group, SISAB sex category, and the selected report category. For each competence month and report type, the extraction combines 36 stratified SISAB downloads: 18 age groups by 2 sex values. Monthly files are merged into yearly files, completing missing combinations of observed competence, municipality, age group, sex, and category with valor = 0 . The LAI dataset contains yearly CID-10 and CIAP-2 attendance counts by competence month, municipality, code type, and code. When multiple valid LAI files cover the same competence, the processing pipeline selects the file with the largest number of data rows, using file size and request folder order as tie-breakers. Provenance columns identify the selected LAI request and source file. Variables SISAB Saúde Produção Columns: competencia : competence month in YYYYMM format. uf : Brazilian state abbreviation. ibge : municipality IBGE code. municipio : municipality name. faixa_etaria : Age group. sexo : SISAB sex category, Masculino or Feminino . tipo_producao : production type from the SISAB report. valor : count reported by SISAB. SISAB Saúde Procedimento Columns: competencia : competence month in YYYYMM format. uf : Brazilian state abbreviation. ibge : municipality IBGE code. municipio : municipality name. faixa_etaria : age group. sexo : SISAB sex category, Masculino or Feminino . procedimento : procedure from the SISAB report. valor : count reported by SISAB SISAB Saúde Condição Avaliada Columns: competencia : competence month in YYYYMM format. uf : Brazilian state abbreviation. ibge : municipality IBGE code. municipio : municipality name. faixa_etaria : age group. sexo : SISAB sex category, Masculino or Feminino . condicao_avaliada : evaluated problem or condition from the SISAB report. valor : count reported by SISAB. SISAB LAI CID/CIAP Columns: ano_competencia : competence year. competencia : competence month in YYYYMM format. competencia_date : first day of the competence month. co_municipio_ibge : municipality IBGE code. tp_codigo : code type, CID or CIAP . codigo : CID-10 or CIAP-2 code. qt_atendimentos : number of attendances. source_request : selected LAI request folder. source_file : selected source CSV file. Methods The public SISAB report files were generated with the sisab_scrapper processing pipeline. For each month, report type, age group, and sex value, the pipeline downloads the all-Brazil municipality report from SISAB, validates the returned CSV, preserves raw cache files for resumable runs, and writes a sorted monthly tidy dataset. The yearly merge validates required columns, expected age groups, expected sex values, category values, and month gaps unless explicitly allowed. The CID/CIAP files were generated with the sisab_lai processing pipeline. The pipeline imports CSV files received through LAI requests, detects the real CSV header after any SQL*Plus preamble, validates candidate files, resolves overlapping requests by competence, standardizes old and new schemas into one tidy table, and exports annual CSV and Parquet files together with audit reports. Sources - SISAB public reports, Ministry of Health, Brazil: https://sisab.saude.gov.br/ - SISAB LAI files obtained through Brazilian Access to Information Law requests. - Processing code for public SISAB report data: https://github.com/rfsaldanha/sisab_scrapper - Processing code for LAI CID/CIAP data: https://github.com/rfsaldanha/sisab_lai Notes - Counts are aggregated administrative records and should be interpreted in light of SISAB reporting practices, data quality, and changes in municipal reporting coverage. - Municipality boundaries, names, and coding practices may vary over time. - Public SISAB report datasets are completed with zero values only for combinations defined by observed municipalities, observed competencies, all expected age groups, both expected sex values, and observed report categories within the yearly merge. - LAI CID/CIAP data preserves selected source-file provenance through source_request and source_file . - This deposit corresponds to an individual year. Deposits for other years are published separately.

Bir, Joyanta · Cancio, Ibon · Diaz de cerio, Oihane · et al.

3 files · 100 KB · fasta, xlsxdeclared

This data file contains the data associated with the manuscript entitled "Duplication of the Genes Coding the Proteins That Regulate RNA Polymerase III Activity and Differential Transcription in Tissues of Teleost Fish."