cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc20jj47
title: CCDC 1862918: Experimental Crystal Structure Determination

description: Related Article: Udai P. Singh, Neetu Singh, Aurobinda Mohanty, Ray J. Butcher|2021|J.Chem.Cryst.|51|57|doi:10.1007/s10870-020-00831-8
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.cc20jj58
title: CCDC 1862919: Experimental Crystal Structure Determination

description: Related Article: Udai P. Singh, Neetu Singh, Aurobinda Mohanty, Ray J. Butcher|2021|J.Chem.Cryst.|51|57|doi:10.1007/s10870-020-00831-8
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.cc24df00
title: CCDC 1978141: Experimental Crystal Structure Determination

description: Related Article: Shafikul Islam,  Md. Imran Hossain,  Md. Manzurul Karim,  Nikhil C. Bhoumik|2022|J.Chem.Cryst.|52|17|doi:10.1007/s10870-021-00884-3
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.cc24dfcc
title: CCDC 1978152: Experimental Crystal Structure Determination

description: Related Article: Shafikul Islam,  Md. Imran Hossain,  Md. Manzurul Karim,  Nikhil C. Bhoumik|2022|J.Chem.Cryst.|52|17|doi:10.1007/s10870-021-00884-3
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.cc25kf28
title: CCDC 2012739: Experimental Crystal Structure Determination

description: Related Article: Jun Xia, Chen‐Han Wang|2021|Z.Anorg.Allg.Chem.|647|641|doi:10.1002/zaac.202000368
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.cc25kf39
title: CCDC 2012740: Experimental Crystal Structure Determination

description: Related Article: Jun Xia, Chen‐Han Wang|2021|Z.Anorg.Allg.Chem.|647|641|doi:10.1002/zaac.202000368
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: 10.6084/m9.figshare.21370572.v2
title: JARVIS-SuperconDB

description: JARVIS-Superconductor database for 3D materials <br> unzip jarvis_epc_data_figshare_1058.json.zip <br> &gt;&gt;&gt; import pandas as pd &gt;&gt;&gt; df=pd.read_json('jarvis_epc_data_figshare_1058.json') <br> &gt;&gt;&gt; print (df.columns) Index(['stability', 'jid', 'atoms', 'cfid', 'wlog', 'lamb', 'Tc', 'a2F', 'a2F_original_x', 'a2F_original_y', 'press'], dtype='object') <br> We perform electron-phonon coupling calculations to establish a large and systematic database of BCS superconducting properties.
DOI: 10.3886/icpsr35376.v1
title: Survey of Consumer Attitudes and Behavior, August 2005
title: Version 1

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter. The surveys conducted in 2005 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, and other durables. Also explored in this survey were respondents' types of savings and financial investments, loan use, family income, retirement planning, spending and working preferences, as well as general feelings. Other topics in this series typically include ownership, lease, finance and use of automobiles, respondents' use of personal computers at home and in the office, and respondents' familiarity with and use of the Internet. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: The data are not weighted, however, this collection contains four weight variables; WT (HOUSEHOLD HEAD WEIGHT), WT_HH (HOUSEHOLD WEIGHT), WT_ADHD (ADULT HEAD WEIGHT), and WT_AD (ADULT WEIGHT) that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Surveys of Consumers Web site.
description: ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Checked for undocumented or out-of-range codes..
description: Datasets: 
 
 DS1: Dataset
description: Survey of Consumer Attitudes and Behavior Series
description: computer-assisted telephone interview (CATI) 
Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the ICPSR Codebook.
 Additional information on the Survey of Consumers can be found by visiting the Surveys of Consumers Web site.
description: Persons aged 18 years or older living in households with telephones within the United States. Smallest Geographic Unit: Census divison
description: National sampling of dwelling units selected by area probability sampling.
DOI: 10.3886/icpsr35376.v2
title: Survey of Consumer Attitudes and Behavior, August 2005
title: Version 2

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter. The surveys conducted in 2005 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, and other durables. Also explored in this survey were respondents' types of savings and financial investments, loan use, family income, retirement planning, spending and working preferences, as well as general feelings. Other topics in this series typically include ownership, lease, finance and use of automobiles, respondents' use of personal computers at home and in the office, and respondents' familiarity with and use of the Internet. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: The data are not weighted, however, this collection contains four weight variables; WT (HOUSEHOLD HEAD WEIGHT), WT_HH (HOUSEHOLD WEIGHT), WT_ADHD (ADULT HEAD WEIGHT), and WT_AD (ADULT WEIGHT) that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Surveys of Consumers Web site.
description: National sampling of dwelling units selected by area probability sampling.
description: Datasets: DS1: Survey of Consumer Attitudes and Behavior, August 2005
description: Persons aged 18 years or older living in households with telephones within the United States. Smallest Geographic Unit: Census divison
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the ICPSR Codebook. Additional information on the Survey of Consumers can be found by visiting the Surveys of Consumers Web site.
DOI: 10.6084/m9.figshare.12399479.v1
title: Additional file 2 of Strain-resolved microbiome sequencing reveals mobile elements that drive bacterial competition on a clinical timescale

description: Additional file 2. Table S1. Species-level classification of the short read sequencing data for the four timepoints. The relative abundance of the species in the samples was determined after removing human and viral reads from the data. A subset of these data (the top 9 species in the samples) are shown in Fig. 1.
DOI: 10.6084/m9.figshare.12399464
title: Additional file 1 of The corrected gene proximity map for analyzing the 3D genome organization using Hi-C data

description: Additional file 1: Figure S1. Pearson correlation coefficients between the gene co-expression matrix and three different matrices based on spatial positioning of genes: the CGP map (blue bars), the raw gene proximity map (green bars), and the normalized gene proximity map (yellow bars) for each of the 23 chromosomes for 10 ENCODE cell lines. Figure S2. (A) ROC curve for the gene compartment classification using leading eigenvectors of the CGP matrix for GM12878 and K562 cell lines. The horizontal axis is the false positive rate (1 − specificity) and the vertical axis is the true positive rate (sensitivity). The red dot indicates the optimal operating point. Components of the top 50 leading eigenvectors were used as features for the classification model. (B) Effect of the number of eigenvectors used in the gene compartment label classifier. The horizontal axis represents the number of eigenvectors in the CGP matrix used for model construction, ranged from 1 to 50. The vertical axis is the average AUROC of the resultant model over the 10-fold cross validation. The red circles and blue squares (almost completely coincide) represent the GM12878 and K562 cell lines respectively. Using the first leading eigenvector alone does not yield a good classification result. By additionally incorporating the second and third eigenvectors, the AUROC witnesses a dramatic increase (from 0.57 to 0.70). On the other hand, using more than 10 eigenvectors does not provide a substantial performance improvement any more. Figure S3. Objective function based on the empirical gene expression profile and randomized profiles, computed using the raw gene proximity map. The histogram for randomized profiles is normalized to have zero mean. A main difference between the plots generated from the CGP and the raw gene proximity map is that for cell lines RPMI-7951, SJCRH30 and SK-N-DZ, the value of the gene proximity map-based objective function generated from the empirical expression profile is mixed with the values generated from randomized profiles. Figure S4. Change in relative spatial positioning of chromosomes between cell lines GM12878 and K562. The layout of this network is in the same way as Figure 6 in the main text, but the inter-chromosomal proximity matrix here was computed using the gene proximity map instead of the corrected proximity measure. As compared to Figure 6, the connections between chromosomes 3 and 10, and between chromosomes 9 and 22, are no longer easily identified. Table S1. Top 20 inter-chromosomal gene interactions in cell lines GM12878 and K562 respectively. These pairs of genes were selected based on the fact that they are located on different chromosomes and have the largest values in the corresponding CGP map.
DOI: 10.6084/m9.figshare.12399464.v1
title: Additional file 1 of The corrected gene proximity map for analyzing the 3D genome organization using Hi-C data

description: Additional file 1: Figure S1. Pearson correlation coefficients between the gene co-expression matrix and three different matrices based on spatial positioning of genes: the CGP map (blue bars), the raw gene proximity map (green bars), and the normalized gene proximity map (yellow bars) for each of the 23 chromosomes for 10 ENCODE cell lines. Figure S2. (A) ROC curve for the gene compartment classification using leading eigenvectors of the CGP matrix for GM12878 and K562 cell lines. The horizontal axis is the false positive rate (1 − specificity) and the vertical axis is the true positive rate (sensitivity). The red dot indicates the optimal operating point. Components of the top 50 leading eigenvectors were used as features for the classification model. (B) Effect of the number of eigenvectors used in the gene compartment label classifier. The horizontal axis represents the number of eigenvectors in the CGP matrix used for model construction, ranged from 1 to 50. The vertical axis is the average AUROC of the resultant model over the 10-fold cross validation. The red circles and blue squares (almost completely coincide) represent the GM12878 and K562 cell lines respectively. Using the first leading eigenvector alone does not yield a good classification result. By additionally incorporating the second and third eigenvectors, the AUROC witnesses a dramatic increase (from 0.57 to 0.70). On the other hand, using more than 10 eigenvectors does not provide a substantial performance improvement any more. Figure S3. Objective function based on the empirical gene expression profile and randomized profiles, computed using the raw gene proximity map. The histogram for randomized profiles is normalized to have zero mean. A main difference between the plots generated from the CGP and the raw gene proximity map is that for cell lines RPMI-7951, SJCRH30 and SK-N-DZ, the value of the gene proximity map-based objective function generated from the empirical expression profile is mixed with the values generated from randomized profiles. Figure S4. Change in relative spatial positioning of chromosomes between cell lines GM12878 and K562. The layout of this network is in the same way as Figure 6 in the main text, but the inter-chromosomal proximity matrix here was computed using the gene proximity map instead of the corrected proximity measure. As compared to Figure 6, the connections between chromosomes 3 and 10, and between chromosomes 9 and 22, are no longer easily identified. Table S1. Top 20 inter-chromosomal gene interactions in cell lines GM12878 and K562 respectively. These pairs of genes were selected based on the fact that they are located on different chromosomes and have the largest values in the corresponding CGP map.
DOI: 10.6084/m9.figshare.12399422
title: Additional file 13 of Pulmonary and systemic responses to aerosolized lysate of Staphylococcus aureus and Escherichia coli in calves

description: Additional file 13. Data.
DOI: 10.6084/m9.figshare.12399422.v1
title: Additional file 13 of Pulmonary and systemic responses to aerosolized lysate of Staphylococcus aureus and Escherichia coli in calves

description: Additional file 13. Data.
DOI: 10.6084/m9.figshare.12399362
title: Additional file 1 of A novel sphingosylphosphorylcholine and sphingosine-1-phosphate receptor 1 antagonist, KRO-105714, for alleviating atopic dermatitis

description: Additional file 1: Supplementary data. A novel sphingosylphosphorylcholine and sphingosine-1-phosphate receptor 1 antagonist, KRO-105714, for alleviating atopic dermatitis. Supplementary figure 1. NMR results of KRO-105714 compound. Supplementary figure 2. LC-MS/HRMS result of KRO-105714 compound. Supplementary figure 3. Liver toxicity and alanine aminotransferase activity (ALT) of KRO-105714. Supplementary table 1. Hematotoxicity and hERG potassium channel binding assay of KRO-105714.
DOI: 10.6084/m9.figshare.12399362.v1
title: Additional file 1 of A novel sphingosylphosphorylcholine and sphingosine-1-phosphate receptor 1 antagonist, KRO-105714, for alleviating atopic dermatitis

description: Additional file 1: Supplementary data. A novel sphingosylphosphorylcholine and sphingosine-1-phosphate receptor 1 antagonist, KRO-105714, for alleviating atopic dermatitis. Supplementary figure 1. NMR results of KRO-105714 compound. Supplementary figure 2. LC-MS/HRMS result of KRO-105714 compound. Supplementary figure 3. Liver toxicity and alanine aminotransferase activity (ALT) of KRO-105714. Supplementary table 1. Hematotoxicity and hERG potassium channel binding assay of KRO-105714.
DOI: 10.6084/m9.figshare.12399302
title: Additional file 3 of Restoration of KMT2C/MLL3 in human colorectal cancer cells reinforces genome-wide H3K4me1 profiles and influences cell growth and gene expression

description: Additional file 3: Table S4. Genes differentially expressed more than 1.5 log2 fold in RKO cells following restoration of KMT2C expression. Table S5. Genes differentially expressed more than 1.5 log2 fold in HCT116 cells following restoration of KMT2C expression. Table S6. Overlap analysis with the MSigDB Hallmarks gene set for genes differentially regulated &gt;1.5 log2 fold by restoration of KMT2C expression in RKO and HCT116 cells. Table S7. Overlap analysis with the MSigDB Hallmarks gene set for genes upregulated &gt;1.5 log2 fold by restoration of KMT2C expression in RKO and HCT116 cells.
DOI: 10.6084/m9.figshare.12399302.v1
title: Additional file 3 of Restoration of KMT2C/MLL3 in human colorectal cancer cells reinforces genome-wide H3K4me1 profiles and influences cell growth and gene expression

description: Additional file 3: Table S4. Genes differentially expressed more than 1.5 log2 fold in RKO cells following restoration of KMT2C expression. Table S5. Genes differentially expressed more than 1.5 log2 fold in HCT116 cells following restoration of KMT2C expression. Table S6. Overlap analysis with the MSigDB Hallmarks gene set for genes differentially regulated &gt;1.5 log2 fold by restoration of KMT2C expression in RKO and HCT116 cells. Table S7. Overlap analysis with the MSigDB Hallmarks gene set for genes upregulated &gt;1.5 log2 fold by restoration of KMT2C expression in RKO and HCT116 cells.
DOI: 10.6084/m9.figshare.12399272
title: Additional file 7 of Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries

description: Additional file 7: Table S7. KEGG functional classifications of Citrobacter specific unique genes.
DOI: 10.6084/m9.figshare.12399278
title: Additional file 8 of Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries

description: Additional file 8. Supplementary information.
DOI: 10.6084/m9.figshare.12399278.v1
title: Additional file 8 of Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries

description: Additional file 8. Supplementary information.
DOI: 10.6084/m9.figshare.12399266
title: Additional file 5 of Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries

description: Additional file 5: Table S5. Genes present in the pan-genome of 95 Salmonella and Citrobacter strains
DOI: 10.6084/m9.figshare.12399266.v1
title: Additional file 5 of Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries

description: Additional file 5: Table S5. Genes present in the pan-genome of 95 Salmonella and Citrobacter strains
DOI: 10.6084/m9.figshare.12399272.v1
title: Additional file 7 of Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries

description: Additional file 7: Table S7. KEGG functional classifications of Citrobacter specific unique genes.
DOI: 10.6084/m9.figshare.12399254
title: Additional file 3 of Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries

description: Additional file 3: Table S3. Average nucleotide identity (ANI) values between Citrobacter strains falsely identified as Salmonella and reference genomes.
DOI: 10.6084/m9.figshare.12399254.v1
title: Additional file 3 of Similar yet different: phylogenomic analysis to delineate Salmonella and Citrobacter species boundaries

description: Additional file 3: Table S3. Average nucleotide identity (ANI) values between Citrobacter strains falsely identified as Salmonella and reference genomes.
DOI: 10.6084/m9.figshare.12399155
title: Additional file 2 of In vitro biosynthesis of Ag, Au and Te-containing nanostructures by Exiguobacterium cell-free extracts

description: Additional file 2. Availability of Data.
DOI: 10.6084/m9.figshare.12399164
title: Additional file 1 of Human immunodeficiency virus positive status disclosure to a sexual partner and its determinant factors in Ethiopia: a systematic review and meta-analysis

description: Additional file 1.
DOI: 10.6084/m9.figshare.12399164.v1
title: Additional file 1 of Human immunodeficiency virus positive status disclosure to a sexual partner and its determinant factors in Ethiopia: a systematic review and meta-analysis

description: Additional file 1.
DOI: 10.6084/m9.figshare.12399155.v1
title: Additional file 2 of In vitro biosynthesis of Ag, Au and Te-containing nanostructures by Exiguobacterium cell-free extracts

description: Additional file 2. Availability of Data.
DOI: 10.6084/m9.figshare.12399065
title: Additional file 3 of Network-based approaches elucidate differences within APOBEC and clock-like signatures in breast cancer

description: Additional file 3 Supplemental table S3: genes and GO terms for expression correlation modules, dNA metabolic genes only.
DOI: 10.6084/m9.figshare.12399056
title: Additional file 2 of Network-based approaches elucidate differences within APOBEC and clock-like signatures in breast cancer

description: Additional file 2 Supplemental table S2: genes and GO terms for expression correlation modules.
DOI: 10.6084/m9.figshare.12399065.v1
title: Additional file 3 of Network-based approaches elucidate differences within APOBEC and clock-like signatures in breast cancer

description: Additional file 3 Supplemental table S3: genes and GO terms for expression correlation modules, dNA metabolic genes only.
DOI: 10.6084/m9.figshare.12399056.v1
title: Additional file 2 of Network-based approaches elucidate differences within APOBEC and clock-like signatures in breast cancer

description: Additional file 2 Supplemental table S2: genes and GO terms for expression correlation modules.