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.

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.

Han, Bingbing · Li, Zhaolei

2 files · 429 KB · xlsdeclared

This dataset compiles published observational data of soil galactosamine across global terrestrial ecosystems. Relevant data were extracted from peer-reviewed literature via a systematic literature screening workflow, encompassing measured concentrations of soil amino galactose as well as matching covariates including soil properties, climatic conditions, microbial attributes, and ecosystem characteristics. All records in this dataset were harmonized through standardized unit conversion, rigorous quality control and cross-consistency verification to facilitate cross-study comparative analyses. This dataset is applicable to investigations into the global biogeographical distribution patterns of soil galactosamine.

Valencia Arias, Jhoany Alejandro · Rodríguez-Lora, Vanessa · Rua Hernandez, Juan Camilo · et al.

2 files · 2.0 MB · csv, xlsdeclared

This dataset contains the bibliographic records retrieved from the Web of Science Core Collection and Scopus databases for a bibliometric analysis of digital collaborative learning. The dataset includes the original export files from both databases in their native formats, preserving the complete bibliographic metadata required for bibliometric and science mapping analyses. The records were collected using a predefined search strategy designed to ensure transparency and reproducibility. These data can be used to replicate the bibliometric analysis, validate the study findings, or conduct complementary analyses using bibliometric software such as Bibliometrix, VOSviewer, CiteSpace, or similar tools. The dataset comprises the following files: Web of Science.xls: Original bibliographic records exported from the Web of Science Core Collection. Scopus.csv: Original bibliographic records exported from Scopus. The data are provided without modification to preserve the integrity of the original database exports. Researchers reusing these data should acknowledge the original data sources (Web of Science and Scopus) and cite this dataset accordingly.

Imanifard, Zahra · Penati, Francesca · Padoa, Sofia · et al.

6 files · 128 KB · xls, xlsxdeclared

This dataset contains the raw experimental data supporting the article "Moss-derived recombinant Factor H, CPV-104, effectively antagonizes alternative pathway C3/C5 convertases stabilization by NeFs from patients with primary C3 glomerulopathy", published in Frontiers in Immunology, 2026 . The dataset includes the following files: Western blot raw data (Figure 1, Supplementary Figure S1, and Supplementary Table S1). Western blot raw data (Figure 2, Supplementary Figure S2, and Supplementary Table S2). ELISA C3a raw data (Figures 3A, 4A, and 4B). ELISA C3a raw data (sCR1 experiments). ELISA Ba raw data (Figures 3B, 4C, and 4D). The files contain the original experimental data underlying the figures and supplementary material reported in the associated publication.

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.

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.

Han, Jin-fen · Wang, Xin · Yin, Bin · et al.

1 files · 63 KB · xlsdeclared

Pairwise distance (lower-left matrix) and number of nucleotide variance (upper-right matrix) of COI-5P sequence among the taxa in this study

Han, Jin-fen · Wang, Xin · Yin, Bin · et al.

1 files · 87 KB · xlsdeclared

Pairwise distance (lower-left matrix) and number of nucleotide variance (upper-right matrix) of rbcL sequence among the taxa in this study

BASUMATARY, BWSRANG

1 files · 18 KB · xlsdeclared

Anda dapat meminta bantuan Customer Service (CS) untuk membuka blokir melalui chat WhatsApp resmi Bank Woori Saudara di nomor +62 821-4444-012. Pastikan Anda sudah menyiapkan data diri seperti buku tabungan dan nomor rekening untuk proses verifikasi.

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.

Sieving, Kathryn

2 files · 697 KB · pdf, xlsdeclared

Two files in this archive associated with ms (to be submitted to Ecology or similar journal): " Changes in attitude with latitude: Leadership of winter bird mobs in the Eastern US ". Contents of this archive: A word file with a table explaining the columns in the data file and all model codes used to analyze the data set. An excel file with the data.

Patel, Maulik

2 files · 174 KB · hdf5declared

1. May24_CIRBE-GOES_flux.h5 contains the necessary flux data to recreate the flux plots. 2. Oct24_CIRBE-GOES_flux.h5 contains the necessary flux data to recreate the flux plots.

Hartig, Johannes

60 files · 11 GB · csv, hdf5, pdfdeclared

Keypoint-MoSeq model checkpoint and data from VNPD paper.

Tjuatja, Vincent · Keramat, Alireza · Duan, Huan-Feng

5 files · 123 KB · xlsdeclared

This dataset contains all the data for the article titled "Transient Resonant Peak Sequencing for Multiple-Leaks Localization: A Novel Graphical Framework". There has been a minor change in Figure ordering in the article. Figure 3a and Figure 3b refers to the FRF of the system with a single leak with xL/L = 0.1 and 0.14. Figure 12 a,b,c,d refers to the FRF of the system with two leaks denoted as validation case 1,2,3,4 with the leak ratio of 1.0. Figure 14 a,b,c,d refers to the FRF of the system with two leaks denoted as case 1,2,3,4 with the leak ratio of 0.8. Figure 16 a,b,c,d refers to the FRF of the system with two leaks denoted as case 1,2,3,4 with the leak ratio of 0.6. In the v.2 version, the following information are added: Validation where the leak ratio is 0.2 and 0.4 Combined order table with the ratio of 0.2 and 0.4 Distance ratio 0.2 and 0.4: The distance between the true leak locations with the closest bound of leak subdomain Sensitivity result summary: Shows the summary of method's performance when the noisy data is considered Sensitivity case 1 realization 0: Example of noisy data used for suggesting alternative to the method in the existence of noise Combined order table with ratio 1.0 sens: This is the combined order table assuming only four measurement points are considered Combined metrics noisy / noiseless classification: This is the summary of recall, precision, and F1 score of different class for CatBoost model based on noiseless and noisy data Confusion matrix noisy / noiseless classification: This is the confusion matrix of the CatBoost model based on noiseless and noisy data Regression data ML: This is the result of regression based on CatBoost model given the leak locations are directly added Comparison_ITA_instance: The pkl file for ITA training instance In the v.3 version, the following information is uploaded: Combined metrics noisy/noiseless classification_fix Confusion matrix noisy/noiseless classifcation_fix A labelling error was noticed in the original csv file (label 1-10-11-12-...) where the label is ordered based on string. In reality, the true label (label 1-2-3-...) is ordered based on integer. The numeric value remains unchanged, but just the label is changed. Comparison_ITA_instance_makefairer: The pkl file for additional ITA training instance given an assumed leak ratio to make a fairer comparison.

de Gonzalo Calvo, David · Perez-Pons, Manel

11 files · 236 KB · xlsdeclared

This repository contains the analysis code associated with the study "Integration of the circulating miRNome and clinical information to predict 90-day mortality in elderly COVID-19 subphenotypes." The archived source code reproduces the computational and statistical analyses reported in the manuscript, including: Differential expression analysis of circulating miRNAs. Identification of clinical subphenotypes using clustering approaches. Machine learning-based prognostic modeling using VSURF. Model interpretation and performance evaluation. Functional enrichment analysis of miRNA target genes. The repository includes the R scripts required to reproduce the analyses described in the manuscript, together with the input files necessary for the functional enrichment analyses. The corresponding miRNA expression dataset (Cq values) is available in Zenodo at https://doi.org/10.5281/zenodo.21261462 . The original development repository is publicly available on GitHub: https://github.com/mprz99/Machine-learning-and-miRNA-based-prediction-of-90-day-mortality-in-elderly-COVID-19-subphenotypes This archived version has been deposited to provide a permanent, citable record of the code used in the published study and to ensure computational reproducibility.

Plunkett, Cailin · Vitale, Salvatore · Zevin, Michael · et al.

4 files · 8.6 GB · hdf5declared

Posterior samples and posterior predictive distributions for the population analyses in Plunkett et al. 2026 .

Green, Alexander

3 files · 5.4 GB · gzip, hdf5declared

This includes the source code, background plasma conditions, and simulation results that produced the simulation data reported in Green et al., "Evaluating the Impact of Multiscale E-Region Turbulence on HF/VHF Scintillation."