cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6519263
title: Song Interpretation Dataset

description: The Song Interpretation Dataset combines data from two sources: (1) music and metadata from the Music4All Dataset and (2) lyrics and user interpretations from SongMeanings.com. We design a music metadata-based matching algorithm that aligns matching items in the two datasets with each other. In the end, we successfully match 25.47% of the tracks in the Music4All Dataset. The dataset contains audio excerpts from 27,834 songs (30 seconds each, recorded at 44.1 kHz), the corresponding music metadata, about 490,000 user interpretations of the lyric text, and the number of votes given for each of these user interpretations. The average length of the interpretations is 97 words. Music in the dataset covers various genres, of which the top 5 are: Rock (11,626), Pop (6,071), Metal (2,516), Electronic (2,213) and Folk (1,760). For more details, please refer to our paper "Interpreting Song Lyrics with an Audio-Informed Pre-trained Language Model".
DOI: 10.25386/genetics.21585612
title: Supplemental Material for Fisher et al., 2022

description: Figure S1 - Heatmap showing target gene clustering. Clustering was done using R, DESeq2 and ggplot (custom script). We find that biological replicates clustered together. Similarly, RNA isolated from the same time points clustered together. <br> Table S1 - complete set of RNAi differential gene expression scores
DOI: 10.25386/genetics.21585612.v2
title: Supplemental Material for Fisher et al., 2022

description: Figure S1 - Heatmap showing target gene clustering. Clustering was done using R, DESeq2 and ggplot (custom script). We find that biological replicates clustered together. Similarly, RNA isolated from the same time points clustered together. <br> Table S1 - complete set of RNAi differential gene expression scores
DOI: 10.25386/genetics.21585612.v1
title: Supplemental Material for Fisher et al., 2022 (in review)

description: Figure S1 - Heatmap showing target gene clustering. Clustering was done using R, DESeq2 and ggplot (custom script). We find that biological replicates clustered together. Similarly, RNA isolated from the same time points clustered together. <br> Table S1 - complete set of RNAi differential gene expression scores
DOI: 10.57967/hf/0258
title: DirectQuote
DOI: 10.5517/ccdc.csd.cc29bwn6
title: CCDC 2125628: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bwp7
title: CCDC 2125629: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxp8
title: CCDC 2125660: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxq9
title: CCDC 2125661: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxrb
title: CCDC 2125662: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxsc
title: CCDC 2125663: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxtd
title: CCDC 2125664: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxvf
title: CCDC 2125665: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxwg
title: CCDC 2125666: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxxh
title: CCDC 2125667: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxyj
title: CCDC 2125668: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29bxzk
title: CCDC 2125669: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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.cc29by0m
title: CCDC 2125670: Experimental Crystal Structure Determination

description: Related Article: Silvana Urcia-Romero, Rodinson R. Arrieta-Pérez, Brian H. Toby, Arturo J. Hernández-Maldonado|2022|Cryst.Growth Des.|22|2382|doi:10.1021/acs.cgd.1c01460
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: 10.15482/usda.adc/1528399
title: Data from: The pathogenesis of a 2022 North American highly pathogenic clade 2.3.4.4b H5N1 avian influenza virus in mallards (Anas platyrhynchos)

description: Treatment groups of ducks were exposed to different virus doses (2, 4, 6 log10 50% egg infectious doses) and by different routes (contact or intrachoanal). The experimental setting was a laboratory with animal care as approved by the institutional animal care and use committee as appropriate for the species and age of bird. Data are the virus titers shed by the oral and cloacal route for individual mallard ducks exposed to H5N1 highly pathogenic avian influenza virus by day post exposure. Samples were collected through 11 days post exposure. Virus titer equivalents were determined by quantitative real-time RT-PCR. Serological data are serum antibody titers to the challenge virus as determined by hemagglutination inhibition assay (reciprocal of the log2 dilution) determined with serum collected 10 or 11 days post exposure.
DOI: 10.6084/m9.figshare.21842640
title: total-final-energy-consumption.xlsx

description: Energy use has long been a major concern in assessments and plans for sustainable urban development. Key energy types are used to breakdown energy consumption from home, transportation, and industrial sources (coal, gas, petroleum products, manufactured fuels, renewables, and electricity).
DOI: 10.6084/m9.figshare.21842640.v1
title: total-final-energy-consumption.xlsx

description: Energy use has long been a major concern in assessments and plans for sustainable urban development. Key energy types are used to breakdown energy consumption from home, transportation, and industrial sources (coal, gas, petroleum products, manufactured fuels, renewables, and electricity).
DOI: 10.7910/dvn/lndjsn
title: test

description: test
DOI: 10.5281/zenodo.7192170
title: Figure files for Coherent spin-valley oscillations in silicon

description: This repository contains .fig (matlab) files corresponding to the figures in Coherent spin-valley oscillations in silicon.
DOI: 10.5281/zenodo.7192171
title: Figure files for Coherent spin-valley oscillations in silicon

description: This repository contains .fig (matlab) files corresponding to the figures in Coherent spin-valley oscillations in silicon.
DOI: 10.6084/m9.figshare.21789092.v2
title: Pain, physical function, and depression in poststroke patients before and after the intervention.xlsx

description: Pain, physical function, and depression in stroke patients before and after the intervention.
DOI: 10.5281/zenodo.7515406
title: CTU-50-FEEL

description: This dataset contains HTTPS-based features of the CTU-50 dataset. These features dataset was created for the purposes of a thesis on Distributed Federated Learning for Network Security. The code of the thesis, as well as the code used for generating these features, can be found in this repository. The dataset spans five days and is split into benign client data, which comes from the day-to-day traffic of real users, and malicious data, which was generated from captured traffic of malware. The dataset does not include any identifiable information. The features were created from the raw Zeek captures by splitting them into one-hour widows and grouping all connections with the same 4-tuple. This means every hour, a connection to one service will produce a single feature vector. The data is in the form of CSV, with the first 41 columns being numerical features. Each feature vector contains two columns with label information. Every vector is uniquely identifiable using these columns: id.orig_h - source IP address. The last octet of the addres is obfuscated with a value consistent across the dataset. id.resp_h - target IP address id.resp_p - target port proto - used protocol day - the day of the capture (value from 1 to 5) hour - an hour of the day from which the feature vector was computed
DOI: 10.5281/zenodo.7515405
title: CTU-50-FEEL

description: This dataset contains HTTPS-based features of the CTU-50 dataset. These features dataset was created for the purposes of a thesis on Distributed Federated Learning for Network Security. The code of the thesis, as well as the code used for generating these features, can be found in this repository. The dataset spans five days and is split into benign client data, which comes from the day-to-day traffic of real users, and malicious data, which was generated from captured traffic of malware. The dataset does not include any identifiable information. The features were created from the raw Zeek captures by splitting them into one-hour widows and grouping all connections with the same 4-tuple. This means every hour, a connection to one service will produce a single feature vector. The data is in the form of CSV, with the first 41 columns being numerical features. Each feature vector contains two columns with label information. Every vector is uniquely identifiable using these columns: id.orig_h - source IP address. The last octet of the addres is obfuscated with a value consistent across the dataset. id.resp_h - target IP address id.resp_p - target port proto - used protocol day - the day of the capture (value from 1 to 5) hour - an hour of the day from which the feature vector was computed
DOI: 10.6084/m9.figshare.21215777
title: A reference genome for Bluegill Sunfish (Centrarchidae: Lepomis macrochirus)

description: North American sunfishes (Family Centrarchidae) are among the most popular sportfish throughout the United States and Canada. Despite the popularity of sunfishes, their ecological importance, and their extensive stocking and aquacultural history, few molecular studies have examined the evolutionary relationships and species limits among members of this group, many of which are known to hybridize. Here, we describe a chromosome-scale, genome assembly representing Bluegill Sunfish (<em>Lepomis macrochirus</em>), one of the most widespread centrarchid species. By combining long-read, Oxford Nanopore sequencing data with short-insert, whole genome and HiC sequence reads, we produced an assembly (Lm_LA_1.0) having a total length of 889 MBP including 1,841 scaffolds and having a scaffold N50 of 36 MBP, L50 of 12, N90 of 29 MBP, and L90 of 22. BUSCO analyses indicated that Lm_LA_1.0 was relatively complete with 99% (eukaryota_odb10) and 98% (actinopterygii_odb10) BUSCOs detected, and <em>ab initio</em>gene prediction performed using this new assembly identified a set of 15,873 genes that were supported by external data. This new assembly provides an important addition to the growing set of assemblies already available for spiny-rayed fishes (Acanthomorpha), and it will serve as a resource for future studies that focus on the complex evolutionary history of centrarchids.
DOI: 10.6084/m9.figshare.21215777.v2
title: A reference genome for Bluegill Sunfish (Centrarchidae: Lepomis macrochirus)

description: North American sunfishes (Family Centrarchidae) are among the most popular sportfish throughout the United States and Canada. Despite the popularity of sunfishes, their ecological importance, and their extensive stocking and aquacultural history, few molecular studies have examined the evolutionary relationships and species limits among members of this group, many of which are known to hybridize. Here, we describe a chromosome-scale, genome assembly representing Bluegill Sunfish (<em>Lepomis macrochirus</em>), one of the most widespread centrarchid species. By combining long-read, Oxford Nanopore sequencing data with short-insert, whole genome and HiC sequence reads, we produced an assembly (Lm_LA_1.0) having a total length of 889 MBP including 1,841 scaffolds and having a scaffold N50 of 36 MBP, L50 of 12, N90 of 29 MBP, and L90 of 22. BUSCO analyses indicated that Lm_LA_1.0 was relatively complete with 99% (eukaryota_odb10) and 98% (actinopterygii_odb10) BUSCOs detected, and <em>ab initio</em>gene prediction performed using this new assembly identified a set of 15,873 genes that were supported by external data. This new assembly provides an important addition to the growing set of assemblies already available for spiny-rayed fishes (Acanthomorpha), and it will serve as a resource for future studies that focus on the complex evolutionary history of centrarchids.
DOI: 10.5281/zenodo.7516377
title: Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis

description: Genetic studies have identified ≥240 loci associated with risk of type 2 diabetes (T2D), yet most of these loci lie in non-coding regions, masking the underlying molecular mechanisms. Recent studies investigating mRNA expression in human pancreatic islets have yielded important insights into the molecular drivers of normal islet function and T2D pathophysiology. However, similar studies investigating microRNA (miRNA) expression remain limited. Here, we present data from 63 individuals, the largest sequencing-based analysis of miRNA expression in human islets to date. We characterize the genetic regulation of miRNA expression by decomposing the expression of highly heritable miRNAs into <em>cis</em>- and <em>trans</em>-acting genetic components and mapping <em>cis</em>-acting loci associated with miRNA expression (miRNA-eQTLs). We find (i) 84 heritable miRNAs, primarily regulated by <em>trans</em>-acting genetic effects, and (ii) 5 miRNA-eQTLs. We also use several different strategies to identify T2D-associated miRNAs. First, we colocalize miRNA-eQTLs with genetic loci associated with T2D and multiple glycemic traits, identifying one miRNA, miR-1908, that shares genetic signals for blood glucose and glycated hemoglobin (HbA1c). Next, we intersect miRNA seed regions and predicted target sites with credible set SNPs associated with T2D and glycemic traits and find 32 miRNAs that may have altered binding and function due to disrupted seed regions. Finally, we perform differential expression analysis and identify 14 miRNAs associated with T2D status—including miR-187-3p, miR-21-5p, miR-668, and miR-199b-5p—and 4 miRNAs associated with a polygenic score for HbA1c levels—miR-216a, miR-25, miR-30a-3p, and miR-30a-5p.
DOI: 10.5281/zenodo.7516376
title: Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis

description: Genetic studies have identified ≥240 loci associated with risk of type 2 diabetes (T2D), yet most of these loci lie in non-coding regions, masking the underlying molecular mechanisms. Recent studies investigating mRNA expression in human pancreatic islets have yielded important insights into the molecular drivers of normal islet function and T2D pathophysiology. However, similar studies investigating microRNA (miRNA) expression remain limited. Here, we present data from 63 individuals, the largest sequencing-based analysis of miRNA expression in human islets to date. We characterize the genetic regulation of miRNA expression by decomposing the expression of highly heritable miRNAs into <em>cis</em>- and <em>trans</em>-acting genetic components and mapping <em>cis</em>-acting loci associated with miRNA expression (miRNA-eQTLs). We find (i) 84 heritable miRNAs, primarily regulated by <em>trans</em>-acting genetic effects, and (ii) 5 miRNA-eQTLs. We also use several different strategies to identify T2D-associated miRNAs. First, we colocalize miRNA-eQTLs with genetic loci associated with T2D and multiple glycemic traits, identifying one miRNA, miR-1908, that shares genetic signals for blood glucose and glycated hemoglobin (HbA1c). Next, we intersect miRNA seed regions and predicted target sites with credible set SNPs associated with T2D and glycemic traits and find 32 miRNAs that may have altered binding and function due to disrupted seed regions. Finally, we perform differential expression analysis and identify 14 miRNAs associated with T2D status—including miR-187-3p, miR-21-5p, miR-668, and miR-199b-5p—and 4 miRNAs associated with a polygenic score for HbA1c levels—miR-216a, miR-25, miR-30a-3p, and miR-30a-5p.
DOI: 10.34740/kaggle/dsv/4830418
title: List of mass shootings in the United States (Raw)