cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13293704
title: Appraise the immunogenicity of designed antibody using deep learning

description: Appraise the immunogencity of designed antibody using deep learning

Link to deep learning model: Yusuf Hamied Department of Chemistry / Sormanni Lab / AbNatiV · GitLab (cam.ac.uk)

Python code: run_abnativ_humanness_score.py

Dataset: antibody_affinity_protein_sabdab_vhvl_immunebuilder_outfiles_nomissing_h.fasta

Example output: *res_scores.csv and *seq_scores.csv
DOI: 10.5281/zenodo.13293705
title: Appraise the immunogenicity of designed antibody using deep learning

description: Appraise the immunogencity of designed antibody using deep learning

Link to deep learning model: Yusuf Hamied Department of Chemistry / Sormanni Lab / AbNatiV · GitLab (cam.ac.uk)

Python code: run_abnativ_humanness_score.py

Dataset: antibody_affinity_protein_sabdab_vhvl_immunebuilder_outfiles_nomissing_h.fasta

Example output: *res_scores.csv and *seq_scores.csv
DOI: 10.15468/dl.vsknsb
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhododendron baconii Argent, A.Lamb & Phillipps"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061121-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yvd4qv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((147.817035 -34.738551, 147.817035 -34.743042, 147.821527 -34.743042, 147.821527 -34.738551, 147.817035 -34.738551))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061122-240626123714530/datasets/export for details.
DOI: 10.15468/dl.4gfcae
title: Occurrence Download

description: A dataset containing 552074 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aquila chrysaetos (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 552074 records from 447 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061118-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.64wkp3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((147.837247 -34.738551, 147.837247 -34.745288, 147.839493 -34.745288, 147.839493 -34.738551, 147.837247 -34.738551))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061123-240626123714530/datasets/export for details.
DOI: 10.15468/dl.79kdas
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhododendron baenitzianum Lauterb."
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061124-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3esf6f
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((147.951783 -34.738551, 147.951783 -34.745288, 147.954029 -34.745288, 147.954029 -34.738551, 147.951783 -34.738551))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061126-240626123714530/datasets/export for details.
DOI: 10.15468/dl.ajdv6h
title: Occurrence Download

description: A dataset containing 62021 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-3.558356 50.69444, -3.464068 50.69444, -3.464068 50.74246, -3.558356 50.74246, -3.558356 50.69444))",
 "Year is greater than or equal to 2000",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 62021 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061125-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zuttga
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((147.983224 -34.738551, 147.992208 -34.738551, 147.992208 -34.736305, 147.983224 -34.736305, 147.983224 -34.738551)), ((147.983224 -34.738551, 147.978733 -34.738551, 147.978733 -34.743042, 147.983224 -34.743042, 147.983224 -34.738551)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061127-240626123714530/datasets/export for details.
DOI: 10.15468/dl.zchkhc
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.070811 -34.711601, 148.070811 -34.72283, 148.075302 -34.72283, 148.075302 -34.727322, 148.070811 -34.727322, 148.070811 -34.729568, 148.075302 -34.729568, 148.075302 -34.731813, 148.077548 -34.731813, 148.077548 -34.72283, 148.08204 -34.72283, 148.08204 -34.720584, 148.077548 -34.720584, 148.077548 -34.716093, 148.075302 -34.716093, 148.075302 -34.711601, 148.070811 -34.711601)), ((148.077548 -34.731813, 148.077548 -34.736305, 148.084285 -34.736305, 148.084285 -34.738551, 148.091023 -34.738551, 148.091023 -34.736305, 148.093269 -34.736305, 148.093269 -34.729568, 148.091023 -34.729568, 148.091023 -34.731813, 148.077548 -34.731813)), ((148.084285 -34.738551, 148.075302 -34.738551, 148.075302 -34.743042, 148.077548 -34.743042, 148.077548 -34.745288, 148.08204 -34.745288, 148.08204 -34.743042, 148.084285 -34.743042, 148.084285 -34.738551)), ((148.091023 -34.729568, 148.091023 -34.727322, 148.088777 -34.727322, 148.088777 -34.729568, 148.091023 -34.729568)))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061128-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fycnza
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.450351 -34.738551, 148.450351 -34.745288, 148.452596 -34.745288, 148.452596 -34.738551, 148.450351 -34.738551))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061129-240626123714530/datasets/export for details.
DOI: 10.15468/dl.9auq6m
title: Occurrence Download

description: A dataset containing 22412 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Larus melanocephalus Temminck, 1820",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 22412 records from 243 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061130-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qyna7j
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.564886 -34.738551, 148.564886 -34.743042, 148.56264 -34.743042, 148.56264 -34.745288, 148.560395 -34.745288, 148.560395 -34.74978, 148.564886 -34.74978, 148.564886 -34.745288, 148.573869 -34.745288, 148.573869 -34.743042, 148.569378 -34.743042, 148.569378 -34.738551, 148.564886 -34.738551)), ((148.573869 -34.745288, 148.573869 -34.74978, 148.576115 -34.74978, 148.576115 -34.745288, 148.573869 -34.745288)))"
 ]
}

 The dataset includes 40 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061131-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10637171
title: [DATASET] Supporting data for Melt inclusions control seismic anisotropy in deforming partially molten ice

description: Data used for paper "Melt inclusions control seismic anisotropy in deforming partially molten ice ." 

File contains a zipped folder with all data. When unzipped, this contains a subfolder for each test shown in manuscript, labeled by degree of melt and DRX steps used per deformation interval (labeled GBM).  Each subfolder contains



EBSD outputs from ELLE named as 'extract_xy_euler3-ZZZ', where ZZZ represents the strain percentage at each step (such that extract_xy_euler3-100 is a strain of 1, extract_xy_euler3-120 is a strain of 1.2, etc). The structure of each file is as follows:  x - y - euler 1 - euler 2 - euler 3 - VMS stress (not used in the paper) - phase (1 ice, 2 melt), with one entry for each point. 

A subfolder labeled 'png,' containing images of the melt at each deformation step. In the case of 0 melt fraction (MF0GBMXX), this is not present. Some images are blank or completely dark due to computation issues.
DOI: 10.5281/zenodo.10851981
title: Programs and data used for Extracting latent variables from forecast ensembles and advancements in similarity metric utilizing optimal transport

description: This is compiled from the program and output data using in Nishizawa (2024).

 

Nishizawa, 2024: Extracting latent variables from forecast ensembles and advancements in similarity metric utilizing optimal transport. submitted to JGR: Machine Learning and Computation.
DOI: 10.5281/zenodo.4250532
title: Deforestation risk embodied in production and consumption of agricultural and forestry commodities 2005-2017

description: This dataset contains estimates of tropical deforestation embodied in the production, exports, imports and consumption of agricultural and forestry commodities by country, year, and commodity, in the time period 2005-2017. The data is an update on the results presented in Pendrill et al. (2019a, b), using a land-balance model to attribute deforestation across 135 countries in the tropics to expansion of cropland, pastures and forest plantation and the commodities produced on this land, and tracing these commodities to consumption using a physical trade model.
description: {"references": ["Pendrill, F., Persson, U. M., Godar, J. and Kastner, T. (2019a) 'Deforestation displaced: trade in forest-risk commodities and the prospects for a global forest transition', Environmental Research Letters, 14(5). https://doi.org/10.1088/1748-9326/ab0d41", "Pendrill, F., Persson, U. M., Godar, J., Kastner, T., Moran, D., Schmidt, S., & Wood, R. (2019b). Agricultural and forestry trade drives large share of tropical deforestation emissions. Global environmental change, 56, 1-10. https://doi.org/10.1016/j.gloenvcha.2019.03.002"]}
DOI: 10.6073/pasta/840d70788bde4692a7d6d45f8d04376f
title: University of Michigan Biological Station cumulative food web data for terrestrial habitats

description: Here, we present species and interaction lists for a food web of the aboveground terrestrial habitats at the University of Michigan Biological Station (UMBS). The site is composed predominantly of dry-mesic, northern hardwood forests with patches of wooded wetlands (hardwood conifer swamp). Taxa were sourced from lists provided by UMBS, from resident biologists’ personal observations, museum specimens, online databases, historical censuses, and BioBlitz events. Only those that could be resolved to species-level or were genera with &lt; 20 species in the Nearctic were included. We also excluded species that do not have a significant lifestage or feeding behavior in aboveground terrestrial habitats. Our focal taxonomic groups include vascular plants, arthropods, birds, mammals, reptiles, amphibians. The majority of arthropods are insects; non-insect arthropods were highly underrepresented in our lists. Interactions were sourced from online databases, naturalist observations, and field guides and accumulated into a “metaweb” of all potential interactions between local species. Interactions were checked by experts to plausibly occur in the aboveground terrestrial environments at UMBS, given species’ phenology, traits, and habitat usage. Interactions at any taxonomic level were included, so long as they were approved to potentially occur between all species by our experts. To study the effect of taxonomic resolution on food web structure, in this dataset, we retained records at coarser taxonomic groupings even if more highly resolved records were also approved. We included all direct interactions among species in our system with a bioenergetic flow (i.e., one species consuming another), differentiated by their focal resource. We broadly categorized the resources as (1) animal tissues (live and scavenged), and (2-5) plant tissues, grouped into (2) leaves and stems, including grasses, exudates, etc., (3) flowers, nectar, pollen, etc., (4) seeds, fruits, elaiosomes, etc., and (5) wood and bark. In our dataset, these are referred to simply as “animals,” “leaves,” “flowers,” “seeds,” and “wood.” We included all consumption interactions in our system that use these resource types, regardless of their potential ecological effects. This includes carnivory, scavenging, parasitoidism, and parasitism of animals (resource type 1), grazing, browsing, and specialized strategies like leaf mining that are sometimes called parasitism (resource type 2), florivory including by animal pollinators (resource type 3), feeding on fruits, seeds, etc. including by seed dispersers and scatterhoarders (resource type 4), and feeding on woody plant tissues including strategies that are sometimes called parasitism (resource type 5). We did not include interactions which may have an effect – e.g., killing (competitively) or pollinating – without a feeding component.
DOI: 10.5281/zenodo.7556459
title: Surrogate Downscaling of Mesoscale Wind Fields Using Ensemble Super-Resolution Convolutional Neural Networks

description: Datasets and source codes for the manuscript "Surrogate Downscaling of Mesoscale Wind Fields Using Ensemble Super-Resolution Convolutional Neural Networks" submitted to the journal "Artificial Intelligence for the Earth Systems" of the American Meteorological Society.
DOI: 10.1285/i20705948v14n2p373
title: The extended Farlie-Gumbel-Morgenstern bivariate Lindley distribution: Concomitants of order statistics and estimation

description: In this study, we proposed the variable scale kernel estimator for analyzing the degradation data. The properties of the proposed method are investigated and compared with the classical method such as; maximum likelihood and ordinary least square methods via simulation technique. The criteria bias and MSE are used for comparison. Simulation results showed that the performance of the variable scale kernel estimator is acceptable as a general estimator. It is nearly the best estimator when the assumption of the distribution is invalid. Application to real data set is also given.
DOI: 10.15468/dl.bdqb0y
title: Occurrence Download

description: A dataset containing 2524 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is Spain",
 "Country is Türkiye"
 ]
 },
 "HasCoordinate is true",
 "TaxonKey is Secale L.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2524 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004519-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gruu9h
title: Occurrence Download

description: A dataset containing 39148 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is Iran (Islamic Republic of)",
 "Country is Türkiye",
 "Country is Pakistan",
 "Country is Tunisia",
 "Country is Spain",
 "Country is Algeria"
 ]
 },
 "HasCoordinate is true",
 "TaxonKey is Triticum L.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 39148 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004520-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24432/c5gp6d
title: REALDISP Activity Recognition Dataset
DOI: 10.5281/zenodo.10587230
title: Data for multi-radionuclide in the Haizhou Bay
DOI: 10.5281/zenodo.1297304
title: Kiwifruit Genome Assembly Red5 Version Ps1.68.5

description: Draft assembly pseudomolecules plus repeat and gene model  annotation files for kiwifruit <em>Actinidia chinensis</em> var. <em>chinensis</em> 'Red5'.
description: Pre-publication working draft of assembly published in BMC Genomics 2018 19:257 . Chromosome 30 includes scaffolds not placed on genetic maps
description: {"references": ["Pilkington, S. M., Crowhurst, R., Hilario, E., Nardozza, S., Fraser, L., Peng, Y., ... & Templeton, K. (2018). A manually annotated Actinidia chinensis var. chinensis (kiwifruit) genome highlights the challenges associated with draft genomes and gene prediction in plants. BMC genomics, 19(1), 257.. DOI https://doi.org/10.1186/s12864-018-4656-3", "Crowhurst, R., Liu, Y., & Scaglione, D. (2016). The Kiwifruit Genome. In The Kiwifruit Genome (pp. 101-114). Springer, Cham. DOI https://doi.org/10.1007/978-3-319-32274-2_8"]}
DOI: 10.5281/zenodo.8286633
title: Data for Internal Variability Increased Arctic Amplification from 1980-2022

description: This data holds the historical and spliced data required to run the convolutional neural network document in Sweeney et al., 2023 submitted to GRL. Data is stored in two folders (historical and spliced), and individual models are put into each category and separated by ensemble number, time period of trend, variable type (surface air temp or sea level pressure), latitude and longitude.
DOI: 10.5281/zenodo.8383359
title: Package for An Observational Study of ChatGPT Usage in Software Engineering Practice

description: The package includes CSV files, and the exit form used by participants in our paper titled: "Beyond Code Generation: An Observational Study of ChatGPT Usage in Software Engineering Practice".

This package has been accepted for the FSE 2024 research track: https://2024.esec-fse.org/details/fse-2024-research-papers/43/Beyond-Code-Generation-An-Observational-Study-of-ChatGPT-Usage-in-Software-Engineeri
DOI: 10.6084/m9.figshare.26014747
title: Supplementary Material for: ATF4 as a Prognostic Marker and Modulator of Glutamine Metabolism in Estrogen Receptor Positive Breast Cancer

description: Purpose: ATF4, a stress-responsive transcription factor that upregulates adaptive genes, is a potential prognostic marker and modulator of glutamine metabolism in breast cancer. However, its exact role remains to be elucidated.

Methods: ATF4 expression was evaluated at genomic and transcriptomic levels using METABRIC (n=1980), GeneMiner (n=4712) and KM-Plotter datasets. Proteomic expression was assessed via immunohistochemistry (n=2225) in the Nottingham Primary Breast Carcinoma Series. ATF4 genomic copy number (CN) variation and mRNA/protein in association with clinicopathological parameters, amino acid transporters (AATs), and patient outcome was investigated.
 
Results: 
Genomic, transcriptomic, and proteomic overexpression of ATF4 was associated with more aggressive ER-negative tumours. ATF4 mRNA and protein expression were significantly associated with increased expression of glutamine related AATs including SLC1A5 (p&lt;0.01) and SLC7A11 (p&lt;0.02). High ATF4 and SLC1A5 protein expression was significantly associated with shorter breast cancer-specific survival (p&lt;0.01), especially in ER+ tumours (p&lt;0.01), while high ATF4 and SLC7A11 protein expression was associated with shorter survival (p&lt;0.01).

Conclusion: These findings suggest a complex interplay between ATF4 and AATs in breast cancer biology and underscore the potential role for ATF4 as a prognostic marker in ER+ breast cancer, offering a unique opportunity for risk stratification and personalised treatment strategies.
DOI: 10.12751/g-node.tvzqc5
title: A multi-center, multi-parametric MRI dataset of primary and secondary brain tumors

description: We introduce a multi-center, multi-origin brain tumor MRI (MOTUM) imaging dataset obtained from 67 patients: 29 with high-grade gliomas, 20 with lung metastases, 10 with breast metastases, 2 with gastric metastasis, 4 with ovarian metastasis, and 2 with melanoma metastasis. This dataset includes anonymized digital imaging and communications in medicine (DICOM) files alongside processed FLAIR, T1-weighted, contrast-enhanced T1-weighted, T2-weighted sequences images, segmentation masks of two tumor regions, and clinical data. Our data-sharing initiative is to support the benchmarking of automated tumor segmentation, multi-modal machine learning, and disease differentiation of multi-origin brain tumors in a multi-center setting.
description: IsDescribedBy: Zhenyu Gong, Tao Xu, Nan Peng, Xing Cheng, Chen Niu, Benedikt Wiestler, Fan Hong A, and Hongwei Bran Li (2024), A Multi-Center, Multi-Parametric MRI Dataset of Primary and Secondary Brain Tumors. Scientific Data, under review.
DOI: 10.15159/eds.dt.20.02
title: Consumption and wind production time series data

description: Consumption data are measured in the real household for two weeks and then multiplied to the whole year. This is an average family with 4 members. Consumption behavior is quite similar whole the year. Production graph is measured in real wind generator as described in the paper and when scaled to certain annual production.
DOI: 10.15468/dl.vh5u7n
title: Occurrence Download

description: A dataset containing 111271 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is Türkiye",
 "Country is Italy",
 "Country is Israel",
 "Country is France",
 "Country is Spain"
 ]
 },
 "HasCoordinate is true",
 "TaxonKey is Avena L.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 111271 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004514-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.