cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.c.3815632_d11
title: Additional file 7: of Evaluating the accuracy of genomic prediction of growth and wood traits in two Eucalyptus species and their F1 hybrids

description: Mean and standard deviation of predictive ability across increasing numbers of SNPs, statistical methods (RKHS and GBLUP), four Training Set/Validation Set compositions for each of eight traits. (XLSX 61Â kb)
DOI: 10.15468/dl.n4egds
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Careproctus micropus (Günther, 1887)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 "CoordinateUncertaintyInMeters is less than or equal to 10000"
 ]
}

 The dataset includes 60 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039240-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.c.3816289_d2.v1
title: Additional file 2: of The metabolic footprint of the airway bacterial community in cystic fibrosis

description: Demographic data of seven CF subjects used in paired analysis. CF genotype data were previously collected on each subject and were identified in medical record review. * CF genotype data were previously collected on each subject and identified in medical record review. (XLSX 34Â kb)
DOI: 10.6084/m9.figshare.c.3816289_d1.v1
title: Additional file 1: of The metabolic footprint of the airway bacterial community in cystic fibrosis

description: Genotype and therapy of 16 CF subjects. * CF genotype data were previously collected on each subject and identified in medical record review. â   Clinical microbiology was generated from a duplicate sputum sample collected at the same time and was analyzed by the clinical microbiology laboratory at the University of Chicago Medicine. (XLSX 49Â kb)
DOI: 10.6084/m9.figshare.c.3816289_d1
title: Additional file 1: of The metabolic footprint of the airway bacterial community in cystic fibrosis

description: Genotype and therapy of 16 CF subjects. * CF genotype data were previously collected on each subject and identified in medical record review. â   Clinical microbiology was generated from a duplicate sputum sample collected at the same time and was analyzed by the clinical microbiology laboratory at the University of Chicago Medicine. (XLSX 49Â kb)
DOI: 10.6084/m9.figshare.c.3816262_d4.v1
title: Additional file 4: of The effects of chronic and acute physical activity on working memory performance in healthy participants: a systematic review with meta-analysis of randomized controlled trials

description: Raw screening data. (XLSX 6436 kb)
DOI: 10.6084/m9.figshare.c.3816289_d2
title: Additional file 2: of The metabolic footprint of the airway bacterial community in cystic fibrosis

description: Demographic data of seven CF subjects used in paired analysis. CF genotype data were previously collected on each subject and were identified in medical record review. * CF genotype data were previously collected on each subject and identified in medical record review. (XLSX 34Â kb)
DOI: 10.6084/m9.figshare.c.3816262_d4
title: Additional file 4: of The effects of chronic and acute physical activity on working memory performance in healthy participants: a systematic review with meta-analysis of randomized controlled trials

description: Raw screening data. (XLSX 6436 kb)
DOI: 10.6084/m9.figshare.c.3816301_d1
title: Additional file 10: of Deep Super-SAGE transcriptomic analysis of cold acclimation in lentil (Lens culinaris Medik.)

description: Lists of significant Super-SAGE tags. Significant over represented SuperSAGE tags (fold change &gt;4) from the susceptible lentil RILs considering both treatments together (S). (XLSX 16 kb)
DOI: 10.6084/m9.figshare.c.3816340_d3
title: Additional file 12: of Comparative transcriptome analysis reveals different strategies for degradation of steam-exploded sugarcane bagasse by Aspergillus niger and Trichoderma reesei

description: Putative new CAZymes of A. niger N402 and T. reesei RUT-C30 differentially expressed in their transcriptomes and identified by dbCAN. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.27616510
title: Another Look at Dependence: The Most Predictable Aspects of Time Series

description: Serial dependence and predictability are two sides of the same coin. The literature has considered alternative measures of these two fundamental concepts. In this article, we aim to distill the most predictable aspect of a univariate time series, that is, the one for which predictability is optimized. Our target measure is the mutual information between the past and future of a random process, a broad measure of predictability that takes into account all future forecast horizons, rather than focusing on the one-step-ahead prediction error mean square error. The most predictable aspect is defined as the measurable transformation of the series that maximizes the mutual information between past and future. This transformation arises from the linear combination of a set of basis functions localized at the quantiles of the unconditional distribution of the process. The mutual information is estimated as a function of the sample partial autocorrelations, using a semiparametric method that estimates an infinite sum by a regularized finite sum. The second most predictable aspect can also be defined, subject to suitable orthogonality restrictions. Finally, we illustrate the use of the most predictable aspect for testing the null hypothesis of no predictability and for point and interval prediction of the original time series.
DOI: 10.6084/m9.figshare.c.3816340_d5.v1
title: Additional file 14: of Comparative transcriptome analysis reveals different strategies for degradation of steam-exploded sugarcane bagasse by Aspergillus niger and Trichoderma reesei

description: Known and putative transporters upregulated in T. reesei RUT-C30 transcriptome. (XLSX 26 kb)
DOI: 10.6084/m9.figshare.27616510.v1
title: Another Look at Dependence: the Most Predictable Aspects of Time Series

description: Serial dependence and predictability are two sides of the same coin. The literature has considered alternative measures of these two fundamental concepts. In this paper, we aim to distill the most predictable aspect of a univariate time series, i.e., the one for which predictability is optimized. Our target measure is the mutual information between the past and future of a random process, a broad measure of predictability that takes into account all future forecast horizons, rather than focusing on the one-step-ahead prediction error mean square error. The most predictable aspect is defined as the measurable transformation of the series that maximizes the mutual information between past and future. This transformation arises from the linear combination of a set of basis functions localized at the quantiles of the unconditional distribution of the process. The mutual information is estimated as a function of the sample partial autocorrelations, using a semiparametric method that estimates an infinite sum by a regularized finite sum. The second most predictable aspect can also be defined, subject to suitable orthogonality restrictions. Finally, we illustrate the use of the most predictable aspect for testing the null hypothesis of no predictability and for point and interval prediction of the original time series.
DOI: 10.6084/m9.figshare.27616510.v2
title: Another Look at Dependence: The Most Predictable Aspects of Time Series

description: Serial dependence and predictability are two sides of the same coin. The literature has considered alternative measures of these two fundamental concepts. In this article, we aim to distill the most predictable aspect of a univariate time series, that is, the one for which predictability is optimized. Our target measure is the mutual information between the past and future of a random process, a broad measure of predictability that takes into account all future forecast horizons, rather than focusing on the one-step-ahead prediction error mean square error. The most predictable aspect is defined as the measurable transformation of the series that maximizes the mutual information between past and future. This transformation arises from the linear combination of a set of basis functions localized at the quantiles of the unconditional distribution of the process. The mutual information is estimated as a function of the sample partial autocorrelations, using a semiparametric method that estimates an infinite sum by a regularized finite sum. The second most predictable aspect can also be defined, subject to suitable orthogonality restrictions. Finally, we illustrate the use of the most predictable aspect for testing the null hypothesis of no predictability and for point and interval prediction of the original time series.
DOI: 10.6084/m9.figshare.c.3816301_d13
title: Additional file 3. of Deep Super-SAGE transcriptomic analysis of cold acclimation in lentil (Lens culinaris Medik.)

description: Lists of significant Super-SAGE tags. Exclusive significant SuperSAGE tags (fold change &gt;4) observed in acclimated lentils of the frost-susceptible RILs (AS). (XLSX 16 kb)
DOI: 10.6084/m9.figshare.c.3816340_d4.v1
title: Additional file 13: of Comparative transcriptome analysis reveals different strategies for degradation of steam-exploded sugarcane bagasse by Aspergillus niger and Trichoderma reesei

description: Known and putative transporters upregulated in A. niger N402 transcriptome. (XLSX 41 kb)
DOI: 10.6084/m9.figshare.c.3816331_d6.v1
title: Additional file 3: Table S2. of Olfactory coding from the periphery to higher brain centers in the Drosophila brain

description: Odor responses of 31 PN classes to 17 odors. (XLSX 18 kb)
DOI: 10.6084/m9.figshare.c.3816340_d4
title: Additional file 13: of Comparative transcriptome analysis reveals different strategies for degradation of steam-exploded sugarcane bagasse by Aspergillus niger and Trichoderma reesei

description: Known and putative transporters upregulated in A. niger N402 transcriptome. (XLSX 41 kb)
DOI: 10.6084/m9.figshare.c.3816340_d5
title: Additional file 14: of Comparative transcriptome analysis reveals different strategies for degradation of steam-exploded sugarcane bagasse by Aspergillus niger and Trichoderma reesei

description: Known and putative transporters upregulated in T. reesei RUT-C30 transcriptome. (XLSX 26 kb)
DOI: 10.6084/m9.figshare.c.3816301_d14
title: Additional file 4: of Deep Super-SAGE transcriptomic analysis of cold acclimation in lentil (Lens culinaris Medik.)

description: Lists of significant Super-SAGE tags. Exclusive significant SuperSAGE tags (fold change &gt;4) observed in acclimated lentils of the frost-tolerant RILs (AT). (XLSX 13 kb)
DOI: 10.6084/m9.figshare.c.3816331_d6
title: Additional file 3: Table S2. of Olfactory coding from the periphery to higher brain centers in the Drosophila brain

description: Odor responses of 31 PN classes to 17 odors. (XLSX 18 kb)
DOI: 10.6084/m9.figshare.c.3816301_d15.v1
title: Additional file 5: of Deep Super-SAGE transcriptomic analysis of cold acclimation in lentil (Lens culinaris Medik.)

description: Lists of significant Super-SAGE tags. Exclusive significant SuperSAGE tags (fold change &gt;4) observed in non-acclimated lentils of the frost-susceptible RILs (NAS). (XLSX 15 kb)
DOI: 10.6084/m9.figshare.c.3816331_d7.v1
title: Additional file 4: Table S3. of Olfactory coding from the periphery to higher brain centers in the Drosophila brain

description: Odor responses of 29 OSN classes to 17 odors. (XLSX 17 kb)
DOI: 10.6084/m9.figshare.c.3816301_d15
title: Additional file 5: of Deep Super-SAGE transcriptomic analysis of cold acclimation in lentil (Lens culinaris Medik.)

description: Lists of significant Super-SAGE tags. Exclusive significant SuperSAGE tags (fold change &gt;4) observed in non-acclimated lentils of the frost-susceptible RILs (NAS). (XLSX 15 kb)
DOI: 10.6084/m9.figshare.c.3816331_d7
title: Additional file 4: Table S3. of Olfactory coding from the periphery to higher brain centers in the Drosophila brain

description: Odor responses of 29 OSN classes to 17 odors. (XLSX 17 kb)
DOI: 10.6084/m9.figshare.c.3816340_d6.v1
title: Additional file 15: of Comparative transcriptome analysis reveals different strategies for degradation of steam-exploded sugarcane bagasse by Aspergillus niger and Trichoderma reesei

description: Predicted orthologue genes which code upregulated transporters in both A. niger N402 and T. reesei RUT-C30 transcriptomes. (XLSX 21 kb)
DOI: 10.6084/m9.figshare.c.3816340_d6
title: Additional file 15: of Comparative transcriptome analysis reveals different strategies for degradation of steam-exploded sugarcane bagasse by Aspergillus niger and Trichoderma reesei

description: Predicted orthologue genes which code upregulated transporters in both A. niger N402 and T. reesei RUT-C30 transcriptomes. (XLSX 21 kb)
DOI: 10.15468/dl.fxz4zt
title: Occurrence Download

description: A dataset containing 2551251 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Denmark",
 "IucnRedListCategory is one of (EX, EW, CR, EN, VU, NT, DD)"
 ]
}

 The dataset includes 2551251 records from 322 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039231-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1147701.10fu
title: SH1147701.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1147703.10fu
title: SH1147703.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1147706.10fu
title: SH1147706.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1147707.10fu
title: SH1147707.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1147709.10fu
title: SH1147709.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1147714.10fu
title: SH1147714.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1147716.10fu
title: SH1147716.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1147718.10fu
title: SH1147718.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1147719.10fu
title: SH1147719.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.