cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2fxsrx
title: CCDC 2262000: Experimental Crystal Structure Determination

description: Related Article: Marius Reinhold, Justin Steinebach, Christopher Golz, Johannes C. L. Walker|2023|Chemical Science|14|9885|doi:10.1039/D3SC03083K
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.cc2fxssy
title: CCDC 2262001: Experimental Crystal Structure Determination

description: Related Article: Marius Reinhold, Justin Steinebach, Christopher Golz, Johannes C. L. Walker|2023|Chemical Science|14|9885|doi:10.1039/D3SC03083K
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.cc2fyrv0
title: CCDC 2262933: Experimental Crystal Structure Determination

description: Related Article: Lei Tang, Qi-Nan Huang, Feng Wu, Yuanjiu Xiao, Jin-Lan Zhou, Tong-Tong Xu, Wen-Biao Wu, Shuanglin Qu, Jian-Jun Feng|2023|Chemical Science|14|9696|doi:10.1039/D3SC03258B
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.cc2ghfr5
title: CCDC 2278957: Experimental Crystal Structure Determination

description: Related Article: Chada Raji Reddy, Sana Fatima, Dattahari H. Kolgave, Balasubramanian Sridhar|2023|Org.Biomol.Chem.|21|7327|doi:10.1039/D3OB01068F
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.cc2ghfs6
title: CCDC 2278958: Experimental Crystal Structure Determination

description: Related Article: Chada Raji Reddy, Sana Fatima, Dattahari H. Kolgave, Balasubramanian Sridhar|2023|Org.Biomol.Chem.|21|7327|doi:10.1039/D3OB01068F
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.cc2g21k5
title: CCDC 2266086: Experimental Crystal Structure Determination

description: Related Article: Shuaiqiang Zhao, Zhiqiang Yang, Xiangyu Zhang, Haichao Liu, Yingbo Lv, Shiyin Wang, Zhongzhao Yang, Shi-Tong Zhang, Bing Yang|2023|Chemical Science|14|9733|doi:10.1039/D3SC03668E
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.cc2g21l6
title: CCDC 2266087: Experimental Crystal Structure Determination

description: Related Article: Shuaiqiang Zhao, Zhiqiang Yang, Xiangyu Zhang, Haichao Liu, Yingbo Lv, Shiyin Wang, Zhongzhao Yang, Shi-Tong Zhang, Bing Yang|2023|Chemical Science|14|9733|doi:10.1039/D3SC03668E
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.cc2g21m7
title: CCDC 2266088: Experimental Crystal Structure Determination

description: Related Article: Shuaiqiang Zhao, Zhiqiang Yang, Xiangyu Zhang, Haichao Liu, Yingbo Lv, Shiyin Wang, Zhongzhao Yang, Shi-Tong Zhang, Bing Yang|2023|Chemical Science|14|9733|doi:10.1039/D3SC03668E
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.cc2gv74q
title: CCDC 2289323: Experimental Crystal Structure Determination

description: Related Article: Marius Reinhold, Justin Steinebach, Christopher Golz, Johannes C. L. Walker|2023|Chemical Science|14|9885|doi:10.1039/D3SC03083K
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.cc2gv75r
title: CCDC 2289324: Experimental Crystal Structure Determination

description: Related Article: Marius Reinhold, Justin Steinebach, Christopher Golz, Johannes C. L. Walker|2023|Chemical Science|14|9885|doi:10.1039/D3SC03083K
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.cc2gv76s
title: CCDC 2289325: Experimental Crystal Structure Determination

description: Related Article: Marius Reinhold, Justin Steinebach, Christopher Golz, Johannes C. L. Walker|2023|Chemical Science|14|9885|doi:10.1039/D3SC03083K
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: 10.5281/zenodo.8355969
title: Clinical subtyping of cancer from plasma based on comprehensive epigenomic profiling

description: <strong><em>Fragment bed files part 3.</em></strong> While circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1mL of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors, and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling could unlock clinically actionable information that is currently accessible only via direct tissue sampling.
DOI: 10.5281/zenodo.8355970
title: Clinical subtyping of cancer from plasma based on comprehensive epigenomic profiling

description: <strong><em>Fragment bed files part 3.</em></strong> While circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1mL of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors, and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling could unlock clinically actionable information that is currently accessible only via direct tissue sampling.
DOI: 10.5281/zenodo.8363384
title: Clinical subtyping of cancer from plasma based on comprehensive epigenomic profiling

description: <strong><em>Fragment bed files part 3.</em></strong> While circulating tumor DNA (ctDNA) assays are increasingly used to inform clinical decisions in cancer care, they have limited ability to identify the transcriptional programs that govern cancer phenotypes and their dynamic changes during the course of disease. To address these limitations, we developed a method for comprehensive epigenomic profiling of cancer from 1mL of patient plasma. Using an immunoprecipitation-based approach targeting histone modifications and DNA methylation, we measured 1,268 epigenomic profiles in plasma from 433 individuals with one of 15 cancers. Our assay provided a robust proxy for transcriptional activity, allowing us to infer the expression levels of diagnostic markers and drug targets, measure the activity of therapeutically targetable transcription factors, and detect epigenetic mechanisms of resistance. This proof-of-concept study in advanced cancers shows how plasma epigenomic profiling could unlock clinically actionable information that is currently accessible only via direct tissue sampling.
DOI: 10.5281/zenodo.8356107
title: Exploring the Impact of Neuroscience Preprints: A Citation Analysis

description: 1. Neuroscience_Records_Contain_Reference_to_Preprints.Scopus.V3.xlsx This Excel file contains the titles, DOIs, references, and EIDs of those Neuroscience publications (journal articles, books/book chapters, conference papers, notes, etc.) from 2004 to 2022 that have at least one reference to a preprint. For example, if a Neuroscience journal article has 40 references and one of these references is a preprint, then it's included in this Excel file. These records are retrieved from Scopus through the following query: REFSRCTITLE ( "OSF Preprints" OR "open science foundation Preprints" OR *africarxiv* OR *agrixiv* OR *arabixiv* OR *arxiv* OR *biohackrxiv* OR *biorxiv* OR *bodoarxiv* OR *cogprints* OR *eartharxiv* OR *ecoevorxiv* OR *ecsarxiv* OR *edarxiv* OR *engrxiv* OR *frenxiv* OR "INA-Rxiv" OR *indiarxiv* OR *lawarxiv* OR "LIS Scholarship Archive" OR *marxiv* OR *mediarxiv* OR *metaarxiv* OR mindrxiv OR *nutrixiv* OR paleorxiv OR "Preprints.org" OR psyarxiv OR *repec* OR *socarxiv* OR *sportrxiv* OR "Thesis Commons" OR "CoP preprint" OR "FocUS Archive preprint" OR "PeerJ preprint" OR "Law Archive preprint" OR *medrxiv* ) AND SUBJAREA ( neur ) AND PUBYEAR &lt; 2023 2. ReferencesToPreprints.V3.txt References of the publications are split through a Python code (SplitReferences.py) and organized into separate lines in a text file. For example, if a publication has 40 references, all of these 40 references are split into 40 separate lines. After splitting references, those lines containing one of these words/terms ("OSF Preprints" OR "open science foundation preprints" OR africarxiv OR agrixiv OR arabixiv OR arxiv OR biohackrxiv OR biorxiv OR bodoarxiv OR cogprints OR eartharxiv OR ecoevorxiv OR ecsarxiv OR edarxiv OR engrxiv OR frenxiv OR "INA-Rxiv" OR indiarxiv OR lawarxiv OR "LIS Scholarship Archive" OR marxiv OR mediarxiv OR metaarxiv OR mindrxiv OR nutrixiv OR paleorxiv OR "Preprints.org" OR psyarxiv OR repec OR socarxiv OR sportrxiv OR "Thesis Commons" OR "CoP preprint" OR "FocUS Archive preprint" OR "PeerJ preprint" OR "Law Archive preprint" OR medrxiv) are selected (through RetrieveLinesContainingSpeceficString.py) and organized into this text file (ReferencesToPreprints.V3.txt). Each reference contains an EID (separated by ";") in order to specify which publication contains this specific reference. After this step, through a Python code (AddPreprintServerToEndOfLines.py) the name of a certain preprint was added to the end of each line. For example, if a line (or a reference) contains "biorxiv", the word "biorxiv" will be added to the end of this line after the "@" sign.
DOI: 10.5281/zenodo.8356108
title: Exploring the Impact of Neuroscience Preprints: A Citation Analysis

description: 1. Neuroscience_Records_Contain_Reference_to_Preprints.Scopus.xlsx This Excel file contains the titles, DOIs, references, and EIDs of those Neuroscience publications (journal articles, books/book chapters, conference papers, notes, etc.) from 2004 to 2022 that have at least one reference to a preprint. For example, if a Neuroscience journal article has 40 references and one of these references is a preprint, then it's included in this Excel file. These records are retrieved from Scopus through the following query: REFSRCTITLE ( "OSF Preprints" OR africarxiv OR agrixiv OR arabixiv OR arxiv OR biohackrxiv OR biorxiv OR bodoarxiv OR cogprints OR eartharxiv OR ecoevorxiv OR ecsarxiv OR edarxiv OR engrxiv OR frenxiv OR "INA-Rxiv" OR indiarxiv OR lawarxiv OR "LIS Scholarship Archive" OR marxiv OR mediarxiv OR metaarxiv OR mindrxiv OR nutrixiv OR paleorxiv OR "Preprints.org" OR psyarxiv OR repec OR socarxiv OR sportrxiv OR "Thesis Commons" OR "CoP preprint" OR "FocUS Archive preprint" OR "PeerJ preprint" OR "Law Archive preprint" ) AND SUBJAREA ( neur ) AND PUBYEAR &lt; 2023 2. ReferencesToPreprints.txt References of the publications are split through a Python code (SplitReferences.py) and organized into separate lines in a text file. For example, if a publication has 40 references, all of these 40 references are split into 40 separate lines. After splitting references, those lines containing one of these words/terms ("OSF Preprints" OR africarxiv OR agrixiv OR arabixiv OR arxiv OR biohackrxiv OR biorxiv OR bodoarxiv OR cogprints OR eartharxiv OR ecoevorxiv OR ecsarxiv OR edarxiv OR engrxiv OR frenxiv OR "INA-Rxiv" OR indiarxiv OR lawarxiv OR "LIS Scholarship Archive" OR marxiv OR mediarxiv OR metaarxiv OR mindrxiv OR nutrixiv OR paleorxiv OR "Preprints.org" OR psyarxiv OR repec OR socarxiv OR sportrxiv OR "Thesis Commons" OR "CoP preprint" OR "FocUS Archive preprint" OR "PeerJ preprint" OR "Law Archive preprint") are selected (through RetrieveLinesContainingSpeceficString.py) and organized into this text file (ReferencesToPreprints.txt). Each reference contains an EID (separated by ";") in order to specify which publication contains this specific reference.
DOI: 10.5281/zenodo.8360746
title: Exploring the Impact of Neuroscience Preprints: A Citation Analysis

description: 1. Neuroscience_Records_Contain_Reference_to_Preprints.Scopus.V2.xlsx This Excel file contains the titles, DOIs, references, and EIDs of those Neuroscience publications (journal articles, books/book chapters, conference papers, notes, etc.) from 2004 to 2022 that have at least one reference to a preprint. For example, if a Neuroscience journal article has 40 references and one of these references is a preprint, then it's included in this Excel file. These records are retrieved from Scopus through the following query: REFSRCTITLE ("OSF Preprints" OR africarxiv OR agrixiv OR arabixiv OR arxiv OR biohackrxiv OR biorxiv OR bodoarxiv OR cogprints OR eartharxiv OR ecoevorxiv OR ecsarxiv OR edarxiv OR engrxiv OR frenxiv OR "INA-Rxiv" OR indiarxiv OR lawarxiv OR "LIS Scholarship Archive" OR marxiv OR mediarxiv OR metaarxiv OR mindrxiv OR nutrixiv OR paleorxiv OR "Preprints.org" OR psyarxiv OR repec OR socarxiv OR sportrxiv OR "Thesis Commons" OR "CoP preprint" OR "FocUS Archive preprint" OR "PeerJ preprint" OR "Law Archive preprint" OR medrxiv) AND SUBJAREA ( neur ) AND PUBYEAR &lt; 2023 2. ReferencesToPreprints.V2.txt References of the publications are split through a Python code (SplitReferences.py) and organized into separate lines in a text file. For example, if a publication has 40 references, all of these 40 references are split into 40 separate lines. After splitting references, those lines containing one of these words/terms ("OSF Preprints" OR africarxiv OR agrixiv OR arabixiv OR arxiv OR biohackrxiv OR biorxiv OR bodoarxiv OR cogprints OR eartharxiv OR ecoevorxiv OR ecsarxiv OR edarxiv OR engrxiv OR frenxiv OR "INA-Rxiv" OR indiarxiv OR lawarxiv OR "LIS Scholarship Archive" OR marxiv OR mediarxiv OR metaarxiv OR mindrxiv OR nutrixiv OR paleorxiv OR "Preprints.org" OR psyarxiv OR repec OR socarxiv OR sportrxiv OR "Thesis Commons" OR "CoP preprint" OR "FocUS Archive preprint" OR "PeerJ preprint" OR "Law Archive preprint" OR medrxiv) are selected (through RetrieveLinesContainingSpeceficString.py) and organized into this text file (ReferencesToPreprints.txt). Each reference contains an EID (separated by ";") in order to specify which publication contains this specific reference.
DOI: 10.5281/zenodo.8364724
title: Exploring the Impact of Neuroscience Preprints: A Citation Analysis

description: 1. Neuroscience_Records_Contain_Reference_to_Preprints.Scopus.V3.xlsx This Excel file contains the titles, DOIs, references, and EIDs of those Neuroscience publications (journal articles, books/book chapters, conference papers, notes, etc.) from 2004 to 2022 that have at least one reference to a preprint. For example, if a Neuroscience journal article has 40 references and one of these references is a preprint, then it's included in this Excel file. These records are retrieved from Scopus through the following query: REFSRCTITLE ( "OSF Preprints" OR "open science foundation Preprints" OR *africarxiv* OR *agrixiv* OR *arabixiv* OR *arxiv* OR *biohackrxiv* OR *biorxiv* OR *bodoarxiv* OR *cogprints* OR *eartharxiv* OR *ecoevorxiv* OR *ecsarxiv* OR *edarxiv* OR *engrxiv* OR *frenxiv* OR "INA-Rxiv" OR *indiarxiv* OR *lawarxiv* OR "LIS Scholarship Archive" OR *marxiv* OR *mediarxiv* OR *metaarxiv* OR mindrxiv OR *nutrixiv* OR paleorxiv OR "Preprints.org" OR psyarxiv OR *repec* OR *socarxiv* OR *sportrxiv* OR "Thesis Commons" OR "CoP preprint" OR "FocUS Archive preprint" OR "PeerJ preprint" OR "Law Archive preprint" OR *medrxiv* ) AND SUBJAREA ( neur ) AND PUBYEAR &lt; 2023 2. ReferencesToPreprints.V3.txt References of the publications are split through a Python code (SplitReferences.py) and organized into separate lines in a text file. For example, if a publication has 40 references, all of these 40 references are split into 40 separate lines. After splitting references, those lines containing one of these words/terms ("OSF Preprints" OR "open science foundation preprints" OR africarxiv OR agrixiv OR arabixiv OR arxiv OR biohackrxiv OR biorxiv OR bodoarxiv OR cogprints OR eartharxiv OR ecoevorxiv OR ecsarxiv OR edarxiv OR engrxiv OR frenxiv OR "INA-Rxiv" OR indiarxiv OR lawarxiv OR "LIS Scholarship Archive" OR marxiv OR mediarxiv OR metaarxiv OR mindrxiv OR nutrixiv OR paleorxiv OR "Preprints.org" OR psyarxiv OR repec OR socarxiv OR sportrxiv OR "Thesis Commons" OR "CoP preprint" OR "FocUS Archive preprint" OR "PeerJ preprint" OR "Law Archive preprint" OR medrxiv) are selected (through RetrieveLinesContainingSpeceficString.py) and organized into this text file (ReferencesToPreprints.V3.txt). Each reference contains an EID (separated by ";") in order to specify which publication contains this specific reference. After this step, through a Python code (AddPreprintServerToEndOfLines.py) the name of a certain preprint was added to the end of each line. For example, if a line (or a reference) contains "biorxiv", the word "biorxiv" will be added to the end of this line after the "@" sign.
DOI: 10.34740/kaggle/dsv/6507225
title: Balochi Language to English Translation Dataset
DOI: 10.17909/65s1-pv09
title: Data for paper on NGC 6302

description: Once upon a time...
DOI: 10.17909/ds95-f096
title: Slava

description: Test
DOI: 10.6084/m9.figshare.23285321.v1
title: Major element, trace element, and 87Sr/86Sr isotope compositions for dikes, sills, dike profiles, and carbonates at Merry Widow and Quinsam, Vancouver Island, Canada

description: Table S1: Bulk rock major element (wt.%) and trace element (ppm) composition Table S2: 87Sr/86Sr isotope compositions for bulk rock powders Table S3: SN ICP-MS vs LA-ICP-MS concentrations on repeat samples
DOI: 10.6084/m9.figshare.24171402
title: Supplementary Tables and sequences S3, S4 and S5.docx

description: This data supports the generation of fully segregated Synechocystis mutants via CRISPR/Cas9 knckins and the design of an effective sgRNA.
DOI: 10.6084/m9.figshare.24171402.v1
title: Supplementary Tables and sequences S3, S4 and S5.docx

description: This data supports the generation of fully segregated Synechocystis mutants via CRISPR/Cas9 knckins and the design of an effective sgRNA.
DOI: 10.5517/ccdc.csd.cc2fg6bg
title: CCDC 2247975: Experimental Crystal Structure Determination

description: Related Article: Hanen Elgahami, Abderrazek Oueslati, Samia Nasr, Ferdinando Costantino, Houcine Naïli|2023|RSC Advances|13|26122|doi:10.1039/D3RA04289H
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: 10.3886/e193941
title: The Great Reform Act 1832, House of Lords Dataset

description: The dataset contains the data that underpin the results reported in Chapter 7 “The Battle with the Lords: Voting on Reform in the House of Lords” of the book “Peaceful and Violent Origins of Voting Rights. A Political Economy Analysis of the Great Reform Act of 1832”. The goal of the project is to understand the origins of democracy in general and the motivation behind the Great Reform Act of 1832 in particular. The data are used to study the roll call votes on 7 October 1831, 13 April 1832 and 7 May 1832 in the House of Lords.
description: The English and Welsh peers sitting in the House of Lords during the 1831-1832 period . Smallest Geographic Unit: England, Wales, London
description: The deposited Read Me Metadata document contains details of the sources from which the data are drawn and a definition of each variable in the dataset.