cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1491492
title: Calculated Entropy for all Sensors

description: In this data, each Datarun is a different sensor and each column after that until average minutiae is a portion of what goes into the joint entropy equation. Each datarun is a different sensor.
DOI: 10.6084/m9.figshare.1491492.v1
title: Calculated Entropy for all Sensors

description: In this data, each Datarun is a different sensor and each column after that until average minutiae is a portion of what goes into the joint entropy equation. Each datarun is a different sensor.
DOI: 10.6084/m9.figshare.1491488
title: GO_oxidationFiltered

description: YEASTRACT Gene Ontology analysis of genes filtered based on having at least a 40% change to differential gene expression in at least one of three post-oxidation time points as compared to normal growth conditions. The three conditions were: (1) 10 min oxidative stress, (2) 60 min oxidative stress, (3) 60 min oxidative stress followed by 60 min no oxidative stress.
DOI: 10.6084/m9.figshare.1491489
title: 27_Clusters_excelFile

description: Clusters formed as part of a study to determine the function of <em>kap108 </em>in <em>Saccharomyces cerevisiae.</em> Genes clustered were those that underwent at least a 40% change in differential expression between wild-type and <em>kap108∆</em> cells following the addition of oxidative stress. Three oxidative time points were considered--10 min oxidative stress, 60 min oxidative stress, and 60 min oxidative stress followed by 60 min no stress--and clustering was done based on how differential gene expression between mutant and wild-type cells changed between time points. A 20% increase was considered "Up", a 20% decrease was considered "Dn", and everything else was considered "Nc". With four time points considered, having three possibilities for each meant 27 possible clusters. This file contains information on all 27 clusters, including the genes within them, graphical depictions of how differential expression changes for each gene over all four time points, a summary of YEASTRACT Gene Ontology analysis for each cluster, and links to full YEASTRACT Gene Ontology analyses.
DOI: 10.6084/m9.figshare.1491487
title: ICBR - FIS Booth and Usability Project

description: The last decade has seen an increase in the application of biometrics to security systems such as those implemented for protecting our border. Suppliers and researchers continue to improve the feasibility of these systems through analyzing biometric algorithms and potential vulnerabilities. The Human-Biometric Sensor Interaction (HBSI) evaluation method uses ergonomics, usability and sample quality criteria as explanatory variables for the overall biometric performance of a system. Recent work with the HBSI model has investigated the applicability of the Kinect Sensor for the automation of detecting errors from a user interaction when made to a biometric system. In this research, we discuss the use of critical and associated tracking points for evaluation within a scenario testing environment. The Kinect sensor is tested for its robustness and ability to provide reliable and stable range of skeletal tracking points across a number of transactions where travelers interact with a US-VISIT inspection booth whilst carrying different luggage combinations.
DOI: 10.6084/m9.figshare.1491489.v1
title: 27_Clusters_excelFile

description: Clusters formed as part of a study to determine the function of <em>kap108 </em>in <em>Saccharomyces cerevisiae.</em> Genes clustered were those that underwent at least a 40% change in differential expression between wild-type and <em>kap108∆</em> cells following the addition of oxidative stress. Three oxidative time points were considered--10 min oxidative stress, 60 min oxidative stress, and 60 min oxidative stress followed by 60 min no stress--and clustering was done based on how differential gene expression between mutant and wild-type cells changed between time points. A 20% increase was considered "Up", a 20% decrease was considered "Dn", and everything else was considered "Nc". With four time points considered, having three possibilities for each meant 27 possible clusters. This file contains information on all 27 clusters, including the genes within them, graphical depictions of how differential expression changes for each gene over all four time points, a summary of YEASTRACT Gene Ontology analysis for each cluster, and links to full YEASTRACT Gene Ontology analyses.
DOI: 10.6084/m9.figshare.1491493.v1
title: ICBR - Interoperability and Entropy Research Prokect

description: Recently there has been an industry-wide push away from passwords for personal verification and towards biometrics. Several different phone manufacturers have already begun to implement fingerprint sensors into their unlocking mechanisms. In this research, we discuss the use of different fingerprint sensors and the entropy of each. The security of all of these fingerprint sensors is tracked in bits of entropy and a number of minutiae points they recognize.
DOI: 10.6084/m9.figshare.1491484
title: GO_Underexpressed_t0

description: YEASTRACT Gene Ontology analysis of underexpressed genes in <em>kap108</em>∆ <em>Saccharomyces cerevisiae</em> cells under normal growth conditions. Genes were determined to be underexpressed if they had a 1.5 fold or greater decrease in mutant cells as compared to wild-type cells (p&lt;0.05 by unpaired t-test with Bonferonni correction).
DOI: 10.6084/m9.figshare.1491485
title: GO_overexpressed_t0

description: YEASTRACT Gene Ontology analysis of overexpressed genes in <em>kap108</em>∆ <em>Saccharomyces cerevisiae</em> cells under normal growth conditions. Genes were determined to be overexpressed if they had a 1.5 fold or greater increase in mutant cells as compared to wild-type cells (p&lt;0.05 by unpaired t-test with Bonferonni correction).
DOI: 10.6084/m9.figshare.1491487.v2
title: ICBR - FIS Booth and Usability Project

description: The last decade has seen an increase in the application of biometrics to security systems such as those implemented for protecting our border. Suppliers and researchers continue to improve the feasibility of these systems through analyzing biometric algorithms and potential vulnerabilities. The Human-Biometric Sensor Interaction (HBSI) evaluation method uses ergonomics, usability and sample quality criteria as explanatory variables for the overall biometric performance of a system. Recent work with the HBSI model has investigated the applicability of the Kinect Sensor for the automation of detecting errors from a user interaction when made to a biometric system. In this research, we discuss the use of critical and associated tracking points for evaluation within a scenario testing environment. The Kinect sensor is tested for its robustness and ability to provide reliable and stable range of skeletal tracking points across a number of transactions where travelers interact with a US-VISIT inspection booth whilst carrying different luggage combinations.
DOI: 10.6084/m9.figshare.1491487.v1
title: FIS Booth and Usability Project

description: The last decade has seen an increase in the application of biometrics to security systems such as those implemented for protecting our border. Suppliers and researchers continue to improve the feasibility of these systems through analyzing biometric algorithms and potential vulnerabilities. The Human-Biometric Sensor Interaction (HBSI) evaluation method uses ergonomics, usability and sample quality criteria as explanatory variables for the overall biometric performance of a system. Recent work with the HBSI model has investigated the applicability of the Kinect Sensor for the automation of detecting errors from a user interaction when made to a biometric system. In this research, we discuss the use of critical and associated tracking points for evaluation within a scenario testing environment. The Kinect sensor is tested for its robustness and ability to provide reliable and stable range of skeletal tracking points across a number of transactions where travelers interact with a US-VISIT inspection booth whilst carrying different luggage combinations.
DOI: 10.6084/m9.figshare.1491475
title: Cluster GOs

description: YEASTRACT Gene Ontology analyses performed for each of 25 gene clusters. Gene clusters were formed based on changes to differential gene expression between time points: a 20% increase qualified as "Up", a 20% decrease qualified as "Dn", and all others qualified as "Nc". Having four time points meant 27 clusters were possible, but two of them (UpUpUp and DnDnDn) did not have any genes.
DOI: 10.6084/m9.figshare.1491488.v1
title: GO_oxidationFiltered

description: YEASTRACT Gene Ontology analysis of genes filtered based on having at least a 40% change to differential gene expression in at least one of three post-oxidation time points as compared to normal growth conditions. The three conditions were: (1) 10 min oxidative stress, (2) 60 min oxidative stress, (3) 60 min oxidative stress followed by 60 min no oxidative stress.
DOI: 10.6084/m9.figshare.1491484.v1
title: GO_Underexpressed_t0

description: YEASTRACT Gene Ontology analysis of underexpressed genes in <em>kap108</em>∆ <em>Saccharomyces cerevisiae</em> cells under normal growth conditions. Genes were determined to be underexpressed if they had a 1.5 fold or greater decrease in mutant cells as compared to wild-type cells (p&lt;0.05 by unpaired t-test with Bonferonni correction).
DOI: 10.6084/m9.figshare.1491485.v1
title: GO_overexpressed_t0

description: YEASTRACT Gene Ontology analysis of overexpressed genes in <em>kap108</em>∆ <em>Saccharomyces cerevisiae</em> cells under normal growth conditions. Genes were determined to be overexpressed if they had a 1.5 fold or greater increase in mutant cells as compared to wild-type cells (p&lt;0.05 by unpaired t-test with Bonferonni correction).
DOI: 10.6084/m9.figshare.1491447
title: ICBR - Core Zoo Performance Analysis Project

description: This research project examines the performance of fingerprints of individuals in a particular dataset after more individuals of good and bad quality are added to the dataset. Does the performance of users change when the addition of the others are added? Notes: - Zoo menagerie plots are used for this research's performance analysis to show the movement of users - The Core dataset consisted of 154 subject's right index finger - The top 25% and bottom 25% of images of different individuals from two additional datasets (dataset 1 and dataset 2) was added to the core zoo. - Performance was ran to see if subjects changed
DOI: 10.6084/m9.figshare.1491484.v3
title: GO_Underexpressed_t0

description: YEASTRACT Gene Ontology analysis of underexpressed genes in <em>kap108</em>∆ <em>Saccharomyces cerevisiae</em> cells under normal growth conditions. Genes were determined to be underexpressed if they had a 1.5 fold or greater decrease in mutant cells as compared to wild-type cells (p&lt;0.05 by unpaired t-test with Bonferonni correction).
DOI: 10.6084/m9.figshare.1491485.v3
title: GO_overexpressed_t0

description: YEASTRACT Gene Ontology analysis of overexpressed genes in <em>kap108</em>∆ <em>Saccharomyces cerevisiae</em> cells under normal growth conditions. Genes were determined to be overexpressed if they had a 1.5 fold or greater increase in mutant cells as compared to wild-type cells (p&lt;0.05 by unpaired t-test with Bonferonni correction).
DOI: 10.6084/m9.figshare.1491488.v2
title: GO_oxidationFiltered

description: YEASTRACT Gene Ontology analysis of genes filtered based on having at least a 40% change to differential gene expression in at least one of three post-oxidation time points as compared to normal growth conditions. The three conditions were: (1) 10 min oxidative stress, (2) 60 min oxidative stress, (3) 60 min oxidative stress followed by 60 min no oxidative stress.
DOI: 10.6084/m9.figshare.1491475.v2
title: Cluster GOs

description: YEASTRACT Gene Ontology analyses performed for each of 25 gene clusters. Gene clusters were formed based on changes to differential gene expression between time points: a 20% increase qualified as "Up", a 20% decrease qualified as "Dn", and all others qualified as "Nc". Having four time points meant 27 clusters were possible, but two of them (UpUpUp and DnDnDn) did not have any genes.
DOI: 10.6084/m9.figshare.1491484.v2
title: GO_Underexpressed_t0

description: YEASTRACT Gene Ontology analysis of underexpressed genes in <em>kap108</em>∆ <em>Saccharomyces cerevisiae</em> cells under normal growth conditions. Genes were determined to be underexpressed if they had a 1.5 fold or greater decrease in mutant cells as compared to wild-type cells (p&lt;0.05 by unpaired t-test with Bonferonni correction).
DOI: 10.6084/m9.figshare.1491475.v1
title: Cluster GOs

description: YEASTRACT Gene Ontology analyses performed for each of 25 gene clusters. Gene clusters were formed based on changes to differential gene expression between time points: a 20% increase qualified as "Up", a 20% decrease qualified as "Dn", and all others qualified as "Nc". Having four time points meant 27 clusters were possible, but two of them (UpUpUp and DnDnDn) did not have any genes.
DOI: 10.6084/m9.figshare.1491485.v2
title: GO_overexpressed_t0

description: YEASTRACT Gene Ontology analysis of overexpressed genes in <em>kap108</em>∆ <em>Saccharomyces cerevisiae</em> cells under normal growth conditions. Genes were determined to be overexpressed if they had a 1.5 fold or greater increase in mutant cells as compared to wild-type cells (p&lt;0.05 by unpaired t-test with Bonferonni correction).
DOI: 10.6084/m9.figshare.1491488.v3
title: GO_oxidationFiltered

description: YEASTRACT Gene Ontology analysis of genes filtered based on having at least a 40% change to differential gene expression in at least one of three post-oxidation time points as compared to normal growth conditions. The three conditions were: (1) 10 min oxidative stress, (2) 60 min oxidative stress, (3) 60 min oxidative stress followed by 60 min no oxidative stress.
DOI: 10.6084/m9.figshare.1491447.v2
title: ICBR - Core Zoo Performance Analysis Project

description: This research project examines the performance of fingerprints of individuals in a particular dataset after more individuals of good and bad quality are added to the dataset. Does the performance of users change when the addition of the others are added? Notes: - Zoo menagerie plots are used for this research's performance analysis to show the movement of users - The Core dataset consisted of 154 subject's right index finger - The top 25% and bottom 25% of images of different individuals from two additional datasets (dataset 1 and dataset 2) was added to the core zoo. - Performance was ran to see if subjects changed
DOI: 10.6084/m9.figshare.1491432
title: SImilar property names using Normalized Levenshtein with 0.85 threshold

description: An analysis of property names based on their similarity using the Normalized Levenshtein with a threshold of 0.85. This analysis is used to find typos in properties and other types of similar properties.
DOI: 10.6084/m9.figshare.1491435
title: Monte o seu perfil de solo

description: Perfil de Solo, monolito para ser colorido, pintado e montado.
DOI: 10.6084/m9.figshare.1491447.v1
title: ICBR - Core Zoo Performance Analysis

description: This research project examines the performance of fingerprints of individuals in a particular dataset after more individuals of good and bad quality are added to the dataset. Does the performance of users change when the addition of the others are added? Notes: - Zoo menagerie plots are used for this research's performance analysis to show the movement of users - The Core dataset consisted of 154 subject's right index finger - The top 25% and bottom 25% of images of different individuals from two additional datasets (dataset 1 and dataset 2) was added to the core zoo. - Performance was ran to see if subjects changed
DOI: 10.6084/m9.figshare.1491432.v1
title: SImilar property names using Normalized Levenshtein with 0.85 threshold

description: An analysis of property names based on their similarity using the Normalized Levenshtein with a threshold of 0.85. This analysis is used to find typos in properties and other types of similar properties.
DOI: 10.6084/m9.figshare.1491430
title: SCS-Africa 2015

description: ISCB's Student Council Symposium-Africa 2015 held in Dar es Salaam, Tanzania.
DOI: 10.6084/m9.figshare.1491430.v1
title: SCS-Africa 2015

description: ISCB's Student Council Symposium-Africa 2015 held in Dar es Salaam, Tanzania.
DOI: 10.6084/m9.figshare.1491435.v1
title: Solos

description: Perfil de Solo, monolito para ser colorido, pintado e montado.
DOI: 10.6084/m9.figshare.1491414
title: Long Fusion Correction of Degenerative Adult Spinal Deformity and the Decision between the Upper versus Lower Thoracic Region as the Site of Proximal Instrumentation

description: The raw data of Long Fusion Correction of Degenerative Adult Spinal Deformity and the Decision between the Upper versus Lower Thoracic Region as the Site of Proximal Instrumentation: A Systematic Review and Meta-Analysis
DOI: 10.6084/m9.figshare.1491421
title: Data and plotting scripts file for the project

description: Data set and figure scripts for " Automated adaptive inference of phenomenological dynamical models" by B. Daniels and I. Nemenman, Nature Communications, 2015.
DOI: 10.6084/m9.figshare.1491403
title: Working memory training

description: Mutual transfer between training on working memory (n-back task) and on perceptual tasks (frequency discrimination, duration discrimination) that require online updating of representations.
DOI: 10.6084/m9.figshare.1491403.v1
title: Working memory training

description: Mutual transfer between training on working memory (n-back task) and on perceptual tasks (frequency discrimination, duration discrimination) that require online updating of representations.
DOI: 10.6084/m9.figshare.1491385
title: Impact of satellite tagging on black kites

description: The file includes values of several vital rates for satellite-tagged individuals of a raptor species (the black kite Milvus migrans) and control individuals. These data are ideally suited for incorporation into meta-analyses of the impact of animal tagging through electronic devices.
DOI: 10.6084/m9.figshare.1491385.v1
title: Impact of satellite tagging on black kites

description: The file includes values of several vital rates for satellite-tagged individuals of a raptor species (the black kite Milvus migrans) and control individuals. These data are ideally suited for incorporation into meta-analyses of the impact of animal tagging through electronic devices.
DOI: 10.6084/m9.figshare.1491372
title: Accent irregularities in esDBpedia 2014 properties

description: This table provides the accent irregularities in esDBpedia 2014 properties. For each normalized (all accents removed) property name, the table provides their different accent variations.
DOI: 10.6084/m9.figshare.1491366
title: Catalog of Sectm1 protein sequences

description: Spreadsheet of Sectm1 accession numbers, protein database, short taxonomy, sequence quality annotation
DOI: 10.6084/m9.figshare.1491367
title: Capitalization irregularities in esDBpedia 2014 properties

description: This table proviedes a summary of the capitalization irregularities in esDBpedia 2014 properties. For each normalized (simple case) property local name, the table provides a list of variations in capitalization (with both their local names and corresponding IRIs).
DOI: 10.6084/m9.figshare.1491365
title: Catalog of Tex19 protein sequences

description: Spreadsheet of Tex19 accession numbers, protein database, short taxonomy, sequence quality annotation
DOI: 10.6084/m9.figshare.1491364
title: Sectm1 multiple alignment of complete protein sequences

description: Multiple alignment of complete Sectm1 protein sequences (58 sequences)
DOI: 10.6084/m9.figshare.1491363
title: Tex19 multiple alignment of complete protein sequences

description: Multiple alignment of Tex19 complete protein sequences (58 sequences)
DOI: 10.6084/m9.figshare.1491363.v1
title: Tex19 multiple alignment of complete protein sequences

description: Multiple alignment of Tex19 complete protein sequences (58 sequences)
DOI: 10.6084/m9.figshare.1491364.v1
title: Sectm1 multiple alignment of complete protein sequences

description: Multiple alignment of complete Sectm1 protein sequences (58 sequences)
DOI: 10.6084/m9.figshare.1491375.v2
title: GIS Research UK (GISRUK) 2015 Proceedings

description: This volume contains the papers presented at GIS Research UK 2015 (GISRUK2015) held at the School of Geography, University of Leeds, on 15-17 April 2015.
DOI: 10.6084/m9.figshare.1490822
title: Master Table for BANYAN VII

description: This dataset contains multiple formats of the master table of all objects in the BANYAN VII paper (link below). Please cite this paper if you use the data in this table.
DOI: 10.6084/m9.figshare.1491315
title: Supplementary data for: Seasonal Differences in Relative Gene Expression of Putative Central Appetite Regulators in Arctic charr (Salvelinus alpinus) Do Not Reflect Its Annual Feeding Cycle

description: Please see "Seasonal Differences in Relative Gene Expression of Putative Central Appetite Regulators in Arctic charr (Salvelinus alpinus) Do Not Reflect Its Annual Feeding Cycle" published in PLOS ONE for details about methodology etc.
DOI: 10.6084/m9.figshare.1490822.v1
title: Master Table for BANYAN VII

description: This dataset contains multiple formats of the master table of all objects in the BANYAN VII paper (link below). Please cite this paper if you use the data in this table.
DOI: 10.6084/m9.figshare.1490071
title: daily ocean time-series non-demultiplexed, raw

description: time-series
DOI: 10.6084/m9.figshare.1491315.v1
title: Supplementary data for: Seasonal Differences in Relative Gene Expression of Putative Central Appetite Regulators in Arctic charr (Salvelinus alpinus) Do Not Reflect Its Annual Feeding Cycle

description: Please see "Seasonal Differences in Relative Gene Expression of Putative Central Appetite Regulators in Arctic charr (Salvelinus alpinus) Do Not Reflect Its Annual Feeding Cycle" published in PLOS ONE for details about methodology etc.
DOI: 10.6084/m9.figshare.1490056
title: Data from "Carbon content and climate variability drive global soil bacterial diversity patterns"

description: Data from "M. Delgado-Baquerizo, F.T. Maestre, P.B. Reich, P. Trivedi, Y. Osanai, Y. Liu, K. Hamonts, T.C. Jeffries & B.K. Singh. Carbon content and climate variability drive global soil bacterial diversity patterns. There are four spreadsheets with data. The spreadsheets "Data_sample_level" and "Data_site_level" contain the raw data used in the different analyses presented in the article. The spreadsheet "Metadata" contains the associated metadata, where a description of all the variables and units can be found. The spreadsheet "List of publications" contains the complete list of publications used in our meta-analysis.
DOI: 10.6084/m9.figshare.1490056.v1
title: Data from "Carbon content and climate variability drive global soil bacterial diversity patterns"

description: Data from "M. Delgado-Baquerizo, F.T. Maestre, P.B. Reich, P. Trivedi, Y. Osanai, Y. Liu, K. Hamonts, T.C. Jeffries & B.K. Singh. Carbon content and climate variability drive global soil bacterial diversity patterns. There are four spreadsheets with data. The spreadsheets "Data_sample_level" and "Data_site_level" contain the raw data used in the different analyses presented in the article. The spreadsheet "Metadata" contains the associated metadata, where a description of all the variables and units can be found. The spreadsheet "List of publications" contains the complete list of publications used in our meta-analysis.
DOI: 10.6084/m9.figshare.1490071.v1
title: daily ocean time-series non-demultiplexed, raw

description: time-series
DOI: 10.6084/m9.figshare.1490071.v2
title: daily ocean time-series non-demultiplexed, raw

description: time-series