cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19334180.v3
title: Data for "Quantifying the Missing Half of Daily NOx Emissions over South, Southeast and East Asia"

description: Fig_1_Mask_ROI.mat is the area mask and the standard deviation of OMI NO2 over the ROI. <br> Fig_2_PC_EOF.mat is the EOF map and PC time series of the first 4 mode of OMI NO2 dataset.<br> Fig_3_EOF_PC_4_Typical_Urban_And_BB.mat s the 2 typical EOF map and extreme time series extracted for Urban areas and BB areas, respectively.<br> Fig_4_typical_daily_NOx_estimation.mat is 4 typical daily NOx emission in this paper. <br> Fig_5_NOx_Mean_Ratio_4_Estimation_EI.mat is the mean and ratio of Mean to standard deviation of NOx estimation and the existing emission inventories(FINN+EDGAR, both in EOF and Mask regions). <br> Fig_6_Timeseries_of_NOx_Est_EOF_Mask_4_Urban_BB.mat is the time series of NOx estimation, NOx emission inventory over EOF region and NOx emission inventory over mask region in Fig.1 for Urban and BB areas.<br> Fig_7_NOx_Estimation_PDF_Geolocation_4_LCT_types.mat is the NOx estimation and geolocation distribution of 3 land cover types. <br> Fig_8_NOx_Estimation_Comparison_4_Sensitivity_Runs.mat is the differences between Base+40%/Base-40% and Base, plus the time series comparisons of the three runs (Base+40%, Base-40% and Base) in both Urban and BB areas.<br> Sup_Fig_1_NO2_mean_ROI.mat is the mean of OMI NO2 over the ROI.<br> Sup_Fig_2_Lai_ROI.mat is the land cover types of MODIS over the ROI.<br> Sup_Fig_3_EOF_PC_4_SouthernCSA.mat s 3 typical EOF map and extreme time series extracted for Southern Continental Southeast Asia.<br> noxEst_year_2016.mat is the estimated NOx dataset for 2016 within this work. <br> estimateGridCoefEmission.m is the core MATLAB code used to fit the coefficients with Least Square Method and estimate the emission with bootstrap method. <br> Demo.zip is one example to help test the core code of this work.
DOI: 10.6084/m9.figshare.22304050
title: Data sets used in the empirical comparison study presented in "Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study"

description: These data sets are a subset of the pre-processed versions of the multi-omics datasets originally used in the empirical comparison study presented in Hornung & Wright (2019). In the latter paper, survival was considered as the outcome variable, given by the data.frame "targetvar" (first column "status": status indicator, second column "time": survival times). The remaining objects in each Rda file are "clin", "cnv", "mirna", "mutation", and "rna", which contain clinical data, copy number variation data, miRNA data, mutation data, and RNA data, respectively. Hornung et al. (2023) used the subset of the data sets presented here, where the outcome variable was the presence vs. absence of the TP53 mutation ("1" vs. "0"). This information is provided by the "TP53" column of the mutation data. Note that while predicting this outcome is not contextually meaningful, TP53 mutations have been found to be associated with poor clinical outcomes in cancer patients (Wang & Sun, 2017). In this context, TP53 can be used as a surrogate for a phenotypic outcome. These data sets are intended to test machine learning or statistical methods and may not be useful for biological analysis. <br> References: <br> R. Hornung, F. Ludwigs, J. Hagenberg, and A.-L. Boulesteix. Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study. arXiv, arXiv:2302.03991, 2023. <br> R. Hornung, and M. N. Wright. Block Forests: random forests for blocks of clinical and omics covariate data. BMC Bioinformatics, 20:358, 2019. <br> X. Wang, and Q. Sun. TP53 mutations, expression and interaction networks in human cancers. Oncotarget, 8(1):624-643, 2017. <br>
DOI: 10.6084/m9.figshare.22304050.v2
title: Data sets used in the empirical comparison study presented in "Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study"

description: These data sets are a subset of the pre-processed versions of the multi-omics datasets originally used in the empirical comparison study presented in Hornung & Wright (2019). In the latter paper, survival was considered as the outcome variable, given by the data.frame "targetvar" (first column "status": status indicator, second column "time": survival times). The remaining objects in each Rda file are "clin", "cnv", "mirna", "mutation", and "rna", which contain clinical data, copy number variation data, miRNA data, mutation data, and RNA data, respectively. Hornung et al. (2023) used the subset of the data sets presented here, where the outcome variable was the presence vs. absence of the TP53 mutation ("1" vs. "0"). This information is provided by the "TP53" column of the mutation data. Note that while predicting this outcome is not contextually meaningful, TP53 mutations have been found to be associated with poor clinical outcomes in cancer patients (Wang & Sun, 2017). In this context, TP53 can be used as a surrogate for a phenotypic outcome. These data sets are intended to test machine learning or statistical methods and may not be useful for biological analysis. <br> References: <br> R. Hornung, F. Ludwigs, J. Hagenberg, and A.-L. Boulesteix. Prediction approaches for partly missing multi-omics covariate data: A literature review and an empirical comparison study. arXiv, arXiv:2302.03991, 2023. <br> R. Hornung, and M. N. Wright. Block Forests: random forests for blocks of clinical and omics covariate data. BMC Bioinformatics, 20:358, 2019. <br> X. Wang, and Q. Sun. TP53 mutations, expression and interaction networks in human cancers. Oncotarget, 8(1):624-643, 2017. <br>
DOI: 10.6084/m9.figshare.22559947
title: IRF5 genetic variants are associated with the incidence of kidney disease

description: The first data set contains the individual genotypes and renal phenotypes of subjects from a study entitled: "IRF5 genetic variants are associated with the incidence of kidney disease. The DESIR study". The second data set contains the characteristics of the SNPs used for this study.
DOI: 10.6084/m9.figshare.22559947.v1
title: IRF5 genetic variants are associated with the incidence of kidney disease

description: The first data set contains the individual genotypes and renal phenotypes of subjects from a study entitled: "IRF5 genetic variants are associated with the incidence of kidney disease. The DESIR study". The second data set contains the characteristics of the SNPs used for this study.
DOI: 10.5281/zenodo.7142734
title: Small mammal classification model

description: Classification model for small mammals and images used for training, validating and testing the model. The script used for training and further information are available on https://github.com/hannaboe/camera_trap_workflow.
DOI: 10.5281/zenodo.7801786
title: Small mammal classification model

description: Classification model for small mammals and images used for training, validating and testing the model. The script used for training and further information are available on https://github.com/hannaboe/camera_trap_workflow.
DOI: 10.5281/zenodo.7654581
title: Data: Contrasting current and future surface melt rates on the ice sheets of Greenland and Antarctica: lessons from in situ observations and climate models

description: These data accompany the publication "Contrasting current and future surface melt rates on the ice sheets of Greenland and Antarctica: lessons from in situ observations and climate models". The data are organized as follows: - two files with time series (csv) of hourly near-surface climate and surface energy balance values for Neumayer station (ice shelf, East Antarctic ice sheet) and automatic weather station S5 (southwest Greenland ice sheet) - two files (nc) with monthly melt fields from the regional climate model RACMO2.3p2 forced by ERA5 over Greenland (0.05-degree resolution) and Antarctica (0.25-degree resolution) - two files (nc) with annual melt fields from the regional climate model RACMO2.3p2 forced by CESM2 over Greenland (0.1-degree resolution) and Antarctica (0.25-degree resolution) or the historical period (1950-2014) - two files (nc) with annual melt fields from the regional climate model RACMO2.3p2 forced by CESM2 over Greenland (0.1-degree resolution) and Antarctica (0.25-degree resolution) for the future emission scenario SSP5-8.5 (2015-2099)
DOI: 10.5281/zenodo.7654580
title: Data: Contrasting current and future surface melt rates on the ice sheets of Greenland and Antarctica: lessons from in situ observations and climate models

description: These data accompany the publication "Contrasting current and future surface melt rates on the ice sheets of Greenland and Antarctica: lessons from in situ observations and climate models". The data are organized as follows: - two files with time series (csv) of hourly near-surface climate and surface energy balance values for Neumayer station (ice shelf, East Antarctic ice sheet) and automatic weather station S5 (southwest Greenland ice sheet) - two files (nc) with monthly melt fields from the regional climate model RACMO2.3p2 forced by ERA5 over Greenland (0.05-degree resolution) and Antarctica (0.25-degree resolution) - two files (nc) with annual melt fields from the regional climate model RACMO2.3p2 forced by CESM2 over Greenland (0.1-degree resolution) and Antarctica (0.25-degree resolution) or the historical period (1950-2014) - two files (nc) with annual melt fields from the regional climate model RACMO2.3p2 forced by CESM2 over Greenland (0.1-degree resolution) and Antarctica (0.25-degree resolution) for the future emission scenario SSP5-8.5 (2015-2099)
DOI: 10.6084/m9.figshare.22560271
title: Supplementary Material for: Distribution and clinical significance of HPV16 variants in head and neck squamous cell carcinomas: data from a Portuguese cohort and systematic review

description: Introduction: Genomic variants of the human papillomavirus type 16 (HPV16) are thought to play differential roles in the susceptibility to head and neck squamous cell carcinomas (HNSCC) and its biological behaviour. This study aims to establish the prevalence of HPV16 variants in an HNSCC cohort and associate them with clinical-pathological characteristics and patient survival. Methods: We retrieved samples and clinical data from 68 HNSCC patients. DNA samples were available from tumour biopsy at the time of the primary diagnosis. Targeted next-generation sequencing (NGS) was used to obtain whole-genome sequences and variants were established based on phylogenetic classification. Results: 74.% of samples clustered in lineage A, 5.7% lineage B, 2.9% C and 17.1% D. Comparative genome analysis revealed 243 single nucleotide variations (SNVs). Of these one hundred were previously reported, according to our systematic review. No significant associations with clinical-pathological variables or patient survival were observed. The E6 amino acid variations E31G, L83V and D25E and E7 N29S, associated with cervical cancer, were not observed, except for N29S in a single patient. Discussion/Conclusion: These results provide a comprehensive genomic map of HPV16 in HSNCC, highlighting tissue-specific characteristics which will help design tailored therapies for cancer patients.
DOI: 10.6084/m9.figshare.22560271.v1
title: Supplementary Material for: Distribution and clinical significance of HPV16 variants in head and neck squamous cell carcinomas: data from a Portuguese cohort and systematic review

description: Introduction: Genomic variants of the human papillomavirus type 16 (HPV16) are thought to play differential roles in the susceptibility to head and neck squamous cell carcinomas (HNSCC) and its biological behaviour. This study aims to establish the prevalence of HPV16 variants in an HNSCC cohort and associate them with clinical-pathological characteristics and patient survival. Methods: We retrieved samples and clinical data from 68 HNSCC patients. DNA samples were available from tumour biopsy at the time of the primary diagnosis. Targeted next-generation sequencing (NGS) was used to obtain whole-genome sequences and variants were established based on phylogenetic classification. Results: 74.% of samples clustered in lineage A, 5.7% lineage B, 2.9% C and 17.1% D. Comparative genome analysis revealed 243 single nucleotide variations (SNVs). Of these one hundred were previously reported, according to our systematic review. No significant associations with clinical-pathological variables or patient survival were observed. The E6 amino acid variations E31G, L83V and D25E and E7 N29S, associated with cervical cancer, were not observed, except for N29S in a single patient. Discussion/Conclusion: These results provide a comprehensive genomic map of HPV16 in HSNCC, highlighting tissue-specific characteristics which will help design tailored therapies for cancer patients.
DOI: 10.6084/m9.figshare.22560274
title: Supplementary Material for: Distribution and clinical significance of HPV16 variants in head and neck squamous cell carcinomas: data from a Portuguese cohort and systematic review

description: Introduction: Genomic variants of the human papillomavirus type 16 (HPV16) are thought to play differential roles in the susceptibility to head and neck squamous cell carcinomas (HNSCC) and its biological behaviour. This study aims to establish the prevalence of HPV16 variants in an HNSCC cohort and associate them with clinical-pathological characteristics and patient survival. Methods: We retrieved samples and clinical data from 68 HNSCC patients. DNA samples were available from tumour biopsy at the time of the primary diagnosis. Targeted next-generation sequencing (NGS) was used to obtain whole-genome sequences and variants were established based on phylogenetic classification. Results: 74.% of samples clustered in lineage A, 5.7% lineage B, 2.9% C and 17.1% D. Comparative genome analysis revealed 243 single nucleotide variations (SNVs). Of these one hundred were previously reported, according to our systematic review. No significant associations with clinical-pathological variables or patient survival were observed. The E6 amino acid variations E31G, L83V and D25E and E7 N29S, associated with cervical cancer, were not observed, except for N29S in a single patient. Discussion/Conclusion: These results provide a comprehensive genomic map of HPV16 in HSNCC, highlighting tissue-specific characteristics which will help design tailored therapies for cancer patients.
DOI: 10.6084/m9.figshare.22560274.v1
title: Supplementary Material for: Distribution and clinical significance of HPV16 variants in head and neck squamous cell carcinomas: data from a Portuguese cohort and systematic review

description: Introduction: Genomic variants of the human papillomavirus type 16 (HPV16) are thought to play differential roles in the susceptibility to head and neck squamous cell carcinomas (HNSCC) and its biological behaviour. This study aims to establish the prevalence of HPV16 variants in an HNSCC cohort and associate them with clinical-pathological characteristics and patient survival. Methods: We retrieved samples and clinical data from 68 HNSCC patients. DNA samples were available from tumour biopsy at the time of the primary diagnosis. Targeted next-generation sequencing (NGS) was used to obtain whole-genome sequences and variants were established based on phylogenetic classification. Results: 74.% of samples clustered in lineage A, 5.7% lineage B, 2.9% C and 17.1% D. Comparative genome analysis revealed 243 single nucleotide variations (SNVs). Of these one hundred were previously reported, according to our systematic review. No significant associations with clinical-pathological variables or patient survival were observed. The E6 amino acid variations E31G, L83V and D25E and E7 N29S, associated with cervical cancer, were not observed, except for N29S in a single patient. Discussion/Conclusion: These results provide a comprehensive genomic map of HPV16 in HSNCC, highlighting tissue-specific characteristics which will help design tailored therapies for cancer patients.
DOI: 10.6084/m9.figshare.22560286
title: Supplementary Material for: Distribution and clinical significance of HPV16 variants in head and neck squamous cell carcinomas: data from a Portuguese cohort and systematic review

description: Introduction: Genomic variants of the human papillomavirus type 16 (HPV16) are thought to play differential roles in the susceptibility to head and neck squamous cell carcinomas (HNSCC) and its biological behaviour. This study aims to establish the prevalence of HPV16 variants in an HNSCC cohort and associate them with clinical-pathological characteristics and patient survival. Methods: We retrieved samples and clinical data from 68 HNSCC patients. DNA samples were available from tumour biopsy at the time of the primary diagnosis. Targeted next-generation sequencing (NGS) was used to obtain whole-genome sequences and variants were established based on phylogenetic classification. Results: 74.% of samples clustered in lineage A, 5.7% lineage B, 2.9% C and 17.1% D. Comparative genome analysis revealed 243 single nucleotide variations (SNVs). Of these one hundred were previously reported, according to our systematic review. No significant associations with clinical-pathological variables or patient survival were observed. The E6 amino acid variations E31G, L83V and D25E and E7 N29S, associated with cervical cancer, were not observed, except for N29S in a single patient. Discussion/Conclusion: These results provide a comprehensive genomic map of HPV16 in HSNCC, highlighting tissue-specific characteristics which will help design tailored therapies for cancer patients.
DOI: 10.6084/m9.figshare.22560286.v1
title: Supplementary Material for: Distribution and clinical significance of HPV16 variants in head and neck squamous cell carcinomas: data from a Portuguese cohort and systematic review

description: Introduction: Genomic variants of the human papillomavirus type 16 (HPV16) are thought to play differential roles in the susceptibility to head and neck squamous cell carcinomas (HNSCC) and its biological behaviour. This study aims to establish the prevalence of HPV16 variants in an HNSCC cohort and associate them with clinical-pathological characteristics and patient survival. Methods: We retrieved samples and clinical data from 68 HNSCC patients. DNA samples were available from tumour biopsy at the time of the primary diagnosis. Targeted next-generation sequencing (NGS) was used to obtain whole-genome sequences and variants were established based on phylogenetic classification. Results: 74.% of samples clustered in lineage A, 5.7% lineage B, 2.9% C and 17.1% D. Comparative genome analysis revealed 243 single nucleotide variations (SNVs). Of these one hundred were previously reported, according to our systematic review. No significant associations with clinical-pathological variables or patient survival were observed. The E6 amino acid variations E31G, L83V and D25E and E7 N29S, associated with cervical cancer, were not observed, except for N29S in a single patient. Discussion/Conclusion: These results provide a comprehensive genomic map of HPV16 in HSNCC, highlighting tissue-specific characteristics which will help design tailored therapies for cancer patients.
DOI: 10.5281/zenodo.7789370
title: Research data related to switchable contact model (SCM) development

description: Research data of the linked journal article, is composed of input and output files of the LIGGGHTS simulations (Project folders) and an Excel data sheet (Results_Excel) which includes calculated data. The contents are the simulation data and results of cake formation in centrifugal filtration using conventional (mesh) method and novel Switchable contact model (SCM, primitive) method. (For more information see the linked article and the source code of SCM: https://github.com/DamlaSerper/SCM)
DOI: 10.5281/zenodo.7789371
title: Research data related to SCM

description: Research data of the linked journal article, is composed of input and output files of the LIGGGHTS simulations (Project folders) and an Excel data sheet (Results_Excel) which includes calculated data. The contents are the simulation data and results of cake formation in centrifugal filtration using conventional (mesh) method and novel Switchable contact model (SCM, primitive) method. (For more information the source code of SCM: https://github.com/DamlaSerper/SCM)
DOI: 10.5281/zenodo.7799246
title: Research data related to switchable contact model (SCM) development

description: Research data of the linked journal article, is composed of input and output files of the LIGGGHTS simulations (Project folders) and an Excel data sheet (Results_Excel) which includes calculated data. The contents are the simulation data and results of cake formation in centrifugal filtration using conventional (mesh) method and novel Switchable contact model (SCM, primitive) method. (For more information see the linked article and the source code of SCM: https://github.com/DamlaSerper/SCM)
DOI: 10.34740/kaggle/dsv/5320834
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5517/ccdc.csd.cc2678yp
title: CCDC 2032792: Experimental Crystal Structure Determination

description: Related Article: Xiaojia Wang, Gaihong Zhu, Chaohai Wang, Yunyin Niu|2021|Environ.Res.|198|111253|doi:10.1016/j.envres.2021.111253
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2678zq
title: CCDC 2032793: Experimental Crystal Structure Determination

description: Related Article: Xiaojia Wang, Gaihong Zhu, Chaohai Wang, Yunyin Niu|2021|Environ.Res.|198|111253|doi:10.1016/j.envres.2021.111253
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27xyhm
title: CCDC 2083401: Experimental Crystal Structure Determination

description: Related Article: Xiaojia Wang, Gaihong Zhu, Chaohai Wang, Yunyin Niu|2021|Environ.Res.|198|111253|doi:10.1016/j.envres.2021.111253
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29h320
title: CCDC 2129671: Experimental Crystal Structure Determination

description: Related Article: Bailey S. Bouley, Fengzhi Tang, Dae Young Bae, Liviu M. Mirica|2023|Chemical Science|14|3800|doi:10.1039/D3SC00034F
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.