cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.c.3645743_d2
title: Additional file 1: Table S1. of Oil biosynthesis in a basal angiosperm: transcriptome analysis of Persea Americana mesocarp

description: Summary of RNA-seq data with details of datasets available on the NCBI Short Read Archive. Table S2. Contigs represented by at least 10 reads per kilobase per million mapped reads (RPKM) and their annotation in relation to Arabidopsis proteins. Table S3. Annotation and transcript levels for select genes associated with conversion of sucrose to triacylglycerol, as shown in Fig.Â 2. Table S4. Transcript levels for genes associated with TAG assembly in the ER, relative to GPAT9 expression in avocado mesocarp (Pa Me), rapeseed embryo (Bn Em), castor endosperm (Rc En), oil palm mesocarp (Eg Me), and date palm mesocarp (Pd Me). (XLSX 1350 kb)
DOI: 10.6084/m9.figshare.c.3645743_d4
title: Additional file 2: of Oil biosynthesis in a basal angiosperm: transcriptome analysis of Persea Americana mesocarp

description: Data S1. The sequence information for contigs represented by at least 10 reads per kilobase per million mapped reads (RPKM) and their annotation in relation to Arabidopsis proteins. (TXT 13061 kb)
DOI: 10.6084/m9.figshare.c.3645752_d1
title: Additional file 2: of COMParative Early Treatment Effectiveness between physical therapy and usual care for low back pain (COMPETE): study protocol for a randomized controlled trial

description: Appendix 2. Treatment-based Classification Approach - Manual Therapy. Appendix 3. Treatment-based Classification Approach - Core Strengthening. Appendix 4. Treatment-based Classification Approach - Extension Oriented Treatment Approach. (PDF 792 kb)
DOI: 10.6084/m9.figshare.c.3645764_d2
title: Additional file 3: of Variation in population levels of sedentary time in European children and adolescents according to cross-European studies: a systematic literature review within DEDIPAC

description: Data extraction file. (XLSX 80Â kb)
DOI: 10.6084/m9.figshare.c.3645806_d1
title: Additional file 1: Table S1. of Absolute quantification reveals the stable transmission of a high copy number variant linked to autoinflammatory disease

description: Summary information for each individual included in the current study. (XLSX 69 kb)
DOI: 10.6084/m9.figshare.c.3645815_d1
title: Additional file 3: of Genome-scale metabolic model of Rhodococcus jostii RHA1 (iMT1174) to study the accumulation of storage compounds during nitrogen-limited condition

description: Unique reactions and metabolites, along with their properties, that are involved in the i MT1174Â network. It includes unique reactions ( Additional file 3-1 ) and unique metabolites ( Additional file 3-2 ). These data were utilized to make the stoichiometric matrix of the iMT1174 metabolic network. Note also that the names, IDs and chemical formulas of the metabolites are reported. In this file, the comma separated genes were meant to show the association of the cluster of the genes encoding the respective enzyme. Moreover, some reactions are associated with more than one enzyme; in this case, the additional enzymes were placed in the subsequent rows, along with their respective genes. (XLSX 265Â kb)
DOI: 10.6084/m9.figshare.c.3645815_d2
title: Additional file 2: of Genome-scale metabolic model of Rhodococcus jostii RHA1 (iMT1174) to study the accumulation of storage compounds during nitrogen-limited condition

description: Total metabolites and reactions and their corresponding biochemical pathways, along with exchange reactions, that are involved in the i MT1174Â network. It contains reaction properties such as name, ID, definition, equation, directionality, lower and upper bounds, enzyme commission (EC) numbers, open reading frames (ORFs), KEGG IDs of reactions that were replaced by added reactions (replaced reactions), and references (Additional file 2-1). It also contains unique metabolites (Additional file 2-2). (XLSX 325Â kb)
DOI: 10.6084/m9.figshare.c.3645815_d6
title: Additional file 1: of Genome-scale metabolic model of Rhodococcus jostii RHA1 (iMT1174) to study the accumulation of storage compounds during nitrogen-limited condition

description: Biomass and storage lipid compositions. It includes the compositions of the RHA1 biomass, macromolecules, PHA, TAG, and WE used in this study. (XLS 64Â kb)
DOI: 10.6084/m9.figshare.c.3645821_d1
title: MOESM3 of GWAS analyses reveal QTL in egg layers that differ in response to diet differences

description: Additional file 3. Additional QTL detected using the data for egg quality traits according to age. This file gives the position of the QTL detected with the dataset divided by age, with the top SNP corresponding to the SNP with the highest effect in the QTL region. The QTL is defined by the first (left) and last (right) SNPs that are 1 % significant at the chromosome level, respectively. Var (%) is the percentage of variance explained by the top SNP in the analysis with the whole dataset. Var 50(%) is the percentage of variance explained by the top SNP in the analysis with data for egg collection at 50 weeks only. Var 70(%) is the percentage of variance explained by the top SNP in the analysis with data for egg collection at 70 weeks only. Z Age is the Z test statistic used to compare the two estimates calculated from the data for egg collection at 50 and 70 weeks of age. The difference was significant when P
DOI: 10.6084/m9.figshare.c.3645821_d2
title: MOESM1 of GWAS analyses reveal QTL in egg layers that differ in response to diet differences

description: Additional file 1. QTL detected using the whole dataset to determine the genetic architecture of egg production and egg quality traits. This file gives the position of all the QTL detected using the whole dataset, with the top SNP corresponding to the SNP with the highest effect in the QTL region. The QTL is defined by the first (left) and last (right) SNPs that are 1 % significant at the chromosome level, respectively. Var (%) is the percentage of variance explained by the top SNP in the analysis with the whole dataset. Var LE(%) is the percentage of variance explained by the top SNP in the analysis with data for the low-energy diet only. Var HE(%) is the percentage of variance explained by the top SNP in the analysis with data for the high-energy diet only. Var 50(%) is the percentage of variance explained by the top SNP in the analysis with data for egg collection at 50 weeks only. Var 70(%) is the percentage of variance explained by the top SNP in the analysis with data for egg collection at 70 weeks only. Z Diet is the Z test statistics used to compare the two estimates calculated from the data for LE and HE diets. Z Age is the Z test statistics used to compare the two estimates calculated from the data for egg collection at 50 and 70 weeks of age. The difference was significant when P
DOI: 10.6084/m9.figshare.c.3645821_d3
title: MOESM2 of GWAS analyses reveal QTL in egg layers that differ in response to diet differences

description: Additional file 2. Additional QTL detected using the data for egg production and egg quality traits within diet. This file gives the position of the QTL detected with the dataset divided by diet, with the top SNP corresponding to the SNP with the highest effect in the QTL region. The QTL is defined by the first (left) and last (right) SNPs that are 1 % significant at the chromosome level, respectively. Var (%) is the percentage of variance explained by the top SNP in the analysis with the whole dataset. Var LE(%) is the percentage of variance explained by the top SNP in the analysis with data for the low-energy diet only. Var HE(%) is the percentage of variance explained by the top SNP in the analysis with data for the high-energy diet only. Z Diet is the Z test statistic used to compare the two estimates calculated from the data for LE and HE diets. The difference was significant when P
DOI: 10.6084/m9.figshare.c.3645833_d5
title: Additional file 10: of Functional integration of the circulatory, immune, and respiratory systems in mosquito larvae: pathogen killing in the hemocyte-rich tracheal tufts

description: Data file S1. Fluorescence and optical density (OD) data. (XLSX 91Â kb)
DOI: 10.15468/dl.hvet4w
title: Occurrence Download

description: A dataset containing 112 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Anopheles sacharovi Favre, 1903"
 ]
}

 The dataset includes 112 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034024-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6ukv2c
title: Occurrence Download

description: A dataset containing 279 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Brachygalaxias bullocki (Regan, 1908))"
 ]
}

 The dataset includes 279 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034025-241126133413365/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.3645842_d9
title: Additional file 6: Table S6. of Transcriptome analysis of Sporisorium scitamineum reveals critical environmental signals for fungal sexual mating and filamentous growth

description: List of enriched KEGG terms in SsÎ MAT-1b mutant compared to the wild-type MAT-1. (XLS 47Â kb)
DOI: 10.6084/m9.figshare.c.3645854_d1
title: Additional file 6: of Generation of an integrated Hieracium genomic and transcriptomic resource enables exploration of small RNA pathways during apomixis initiation

description: Predicted MIRNA genes in the D18 genome. (TXT 784 kb)
DOI: 10.6084/m9.figshare.c.3645854_d2
title: Additional file 3: of Generation of an integrated Hieracium genomic and transcriptomic resource enables exploration of small RNA pathways during apomixis initiation

description: Supplemental data regarding transcriptome and differential expression analysis. (XLSX 4996 kb)
DOI: 10.6084/m9.figshare.c.3645854_d3
title: Additional file 4: of Generation of an integrated Hieracium genomic and transcriptomic resource enables exploration of small RNA pathways during apomixis initiation

description: Cloned and consensus HpAGO sequences in fasta format. (TXT 825 kb)
DOI: 10.6084/m9.figshare.c.3645854_d5
title: Additional file 5: of Generation of an integrated Hieracium genomic and transcriptomic resource enables exploration of small RNA pathways during apomixis initiation

description: Supplemental data regarding small RNA analysis. (XLSX 1496 kb)
DOI: 10.6084/m9.figshare.c.3645854_d6
title: Additional file 1: Tables S1â  S8. of Generation of an integrated Hieracium genomic and transcriptomic resource enables exploration of small RNA pathways during apomixis initiation

description: Table S1. Summary of sequencing data across all samples. Table S2. Full list of Arabidopsis genes used for sexual pathway analysis. Table S3. Marker analysis in deletion mutants and polyhaploid mapping populations. Table S4. List of predicted AGO, RDR and DCL genes within the D18 genomic assembly. Table S5. Differentially expressed genes between MMC and FM stage ovaries in R35 and D36. Table S6. Enriched GO terms within differentially expressed genes between MMC and FM stage ovaries in R35 and D36. Table S7. List of predicted gene models with complementary small RNA and transcriptome fold changes. Table S8. List of oligonucleotides used in this study. (XLSX 142 kb)
DOI: 10.15468/dl.dtjpy8
title: Occurrence Download

description: A dataset containing 143 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Anopheles sergentii (Theobald, 1907)"
 ]
}

 The dataset includes 143 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034026-241126133413365/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.3645893_d10
title: Additional file 22: Table S11. of Extensive identification and analysis of conserved small ORFs in animals

description: Experimental evidence for mouse sORFs. (ODS 91 kb)
DOI: 10.6084/m9.figshare.c.3645893_d12
title: Additional file 8: Table S6. of Extensive identification and analysis of conserved small ORFs in animals

description: Summary of datasets used in Fig.Â 3 (other sORF predictions). (ODS 13 kb)
DOI: 10.6084/m9.figshare.c.3645893_d15
title: Additional file 15: Table S9. of Extensive identification and analysis of conserved small ORFs in animals

description: Summary of datasets used in Fig.Â 6b (mass spectrometry). (ODS 13 kb)
DOI: 10.6084/m9.figshare.c.3645893_d17
title: Additional file 6: Table S5. of Extensive identification and analysis of conserved small ORFs in animals

description: All sORF information for worm. (TXT 1536 kb)
DOI: 10.6084/m9.figshare.c.3645893_d18
title: Additional file 4: Table S3. of Extensive identification and analysis of conserved small ORFs in animals

description: All sORF information for zebrafish. (TXT 734 kb)
DOI: 10.6084/m9.figshare.c.3645893_d19
title: Additional file 23: Table S12. of Extensive identification and analysis of conserved small ORFs in animals

description: Experimental evidence for zebrafish sORFs. (ODS 49 kb)
DOI: 10.6084/m9.figshare.c.3645893_d22
title: Additional file 14: Table S8. of Extensive identification and analysis of conserved small ORFs in animals

description: Summary of datasets used in Fig.Â 6a (ribosome profiling). (ODS 14 kb)
DOI: 10.6084/m9.figshare.c.3645893_d24
title: Additional file 24: Table S13. of Extensive identification and analysis of conserved small ORFs in animals

description: Experimental evidence for fruit fly sORFs. (ODS 69 kb)
DOI: 10.6084/m9.figshare.c.3645893_d25
title: Additional file 3: Table S2. of Extensive identification and analysis of conserved small ORFs in animals

description: All sORF information for mouse. (TXT 3192 kb)
DOI: 10.6084/m9.figshare.c.3645899_d1
title: Additional file 1: of The transcription factor ERG increases expression of neurotransmitter receptors on prostate cancer cells

description: ERG-dependent neurotransmitter receptor expression, pathscan data, and patient tumor pathology scoring. (XLSX 100 kb)
DOI: 10.15468/dl.r5mxjn
title: Occurrence Download

description: A dataset containing 1392 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Anopheles stephensi Liston, 1901"
 ]
}

 The dataset includes 1392 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0034027-241126133413365/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.3645980_d2
title: Additional file 2 of Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types

description: Table S2. Mappings from each of the FANTOM5 project primary cell-type samples to its facet, sub-facet and cell-type group. CELL_TYPE: Name of the cell-type group that each sample was finally assigned to. The sample expression data was combined using these groups to produce expression profiles for 73 cell types. If the value in CELL_TYPE is NA then the sample was discarded, either due to a lack of replicate samples or because of the quality-control procedures. (XLS 42.5 kb)
DOI: 10.6084/m9.figshare.c.3645980_d6
title: Additional file 11 of Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types

description: Table S6. Disease-associated cell types identified by the GSC method with an FDR of 10 %. DISEASE: Disease name. CELL_TYPE: Cell-type name. P_VALUE: Unadjusted P value computed using the GSC method. Q_VALUE: Minimum FDR at which the association can be declared significant, computed using the Benjaminiâ  Hochberg procedure for multiple testing. SIG_GSO: Whether the association is declared significant using the GSO method at an FDR of 10 %. SIG_TEXT: Whether the association is declared significant using text-mining at an FDR of 10 %. (XLS 78 kb)
DOI: 10.6084/m9.figshare.c.3645980_d7
title: Additional file 1 of Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types

description: Table S1. Diseaseâ  gene associations extracted from DisGeNET used in the analyses. DISEASE: Name of the disease in the analysis. GENE: Ensembl gene identifier of the associated gene. PUBMED_ID: PubMed identifiers reported by DisGeNET as supporting the association between the gene and the disease. SNP_ID: dbSNP identifiers reported by DisGeNET as linking the gene to the disease. (XLS 830 kb)
DOI: 10.6084/m9.figshare.c.3645980_d9
title: Additional file 4 of Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types

description: Table S4. Performance of the GSC method when applied to sets of diseases with different numbers of associated genes. Performance is measured using associations identified by the text-mining as true positives. Sets of diseaseâ  cell-type associations were produced by applying an FDR cutoff of 10 % to the GSC and text-mined associations. Overlap significance was measured using Fisherâ  s exact test. The GSC method cannot be applied to diseases with only one associated gene and for this reason, the corresponding statistics are not available. (XLS 7.50 kb)
DOI: 10.6084/m9.figshare.c.3645980_d10
title: Additional file 10 of Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types

description: Table S5. Diseaseâ  cell-type association P values computed using the GSC method. (XLS 686 kb)
DOI: 10.6084/m9.figshare.c.3645980_d14
title: Additional file 16 of Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types

description: Table S11. Disease-associated cell types identified by the GSO method with an FDR of 10 %. DISEASE: Disease name. CELL_TYPE: Cell-type name. P_VALUE: Unadjusted P value computed using the GSO method. Q_VALUE: Minimum FDR at which the association can be declared significant, computed using the Benjaminiâ  Hochberg procedure for multiple testing. SIG_GSC: Whether the association is declared significant using the GSC method at an FDR of 10 %. SIG_TEXT: Whether the association is declared significant using text-mining at an FDR of 10 %. (XLS 69 kb)
DOI: 10.6084/m9.figshare.c.3645980_d16
title: Additional file 12 of Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types

description: Table S7. Term mappings for the cell types used in the analyses. NAME: Cell-type name used throughout the analyses (derived from the FANTOM5 project sample name). CL_ID: Cell ontology identifier mapped to the cell type. MESH: The one or two MeSH terms mapped to the cell type used to conduct the text-mining. (XLS 14 kb)
DOI: 10.6084/m9.figshare.c.3645980_d17
title: Additional file 19 of Exploring the cellular basis of human disease through a large-scale mapping of deleterious genes to cell types

description: Table S12. The number of diseaseâ  cell-type associations identified by the GSC and GSO methods supported by text-mining at FDRs of 5, 10 and 20 %. Precision, recall and the F1 score are computed using associations identified by the text-mining method as true positives. Overlap significance was measured using Fisherâ  s exact test. (XLS 7.50 kb)
DOI: 10.21227/edzz-7d60
title: Simulated Resistive Drift of Memristive Devices

description: A dataset of simulated resistive drift series for an illustrative stochastic memristor.Dataset DescriptionThe memristor has an equilibrium resistance of approximately 500kΩ.5000 series are generated with starting resistances sampled uniformly from the range [100Ω, 750kΩ].Each series consists of 1001 datapoints, with the first (zeroth) point corresponding to the initial resistance, and subsequent points sampled at subsequent timesteps.Dataset CreationThe simulations were conducted using the event-based memristor model in [1], with parameters as follows, as specified in [2]:N = 1.8 × 106nthresh = 0gparallel = 1 × 10-6gstep = 1 × 10-8 Va = 0.256Voff = 0.2533References[1] Waleed El-Geresy, Christos Papavassiliou, Deniz Gündüz (2024), Event-Based Simulation of Stochastic Memristive Devices for Neuromorphic Computing, arXiv:2407.04718 [cs.ET][2] Waleed El-Geresy, Christos Papavassiliou, Deniz Gündüz (2024), Delay Conditioned Generative Modelling of Resistive Drift in Memristors, arXiv:2408.01539 [cs.ET]
DOI: 10.6084/m9.figshare.c.3646001_d5
title: Additional file 6: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Genome sizes of indica cultivars. (XLSX 16Â kb)
DOI: 10.6084/m9.figshare.c.3646001_d8
title: Additional file 5: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Assembly quality assessment by QUAST. (XLSX 16Â kb)
DOI: 10.6084/m9.figshare.c.3646001_d6
title: Additional file 14: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Chromosome-wise distribution of repeat elements in HR-12 genome. (XLSX 29Â kb)
DOI: 10.6084/m9.figshare.c.3646001_d9
title: Additional file 9: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Unique genes in HR-12 genome. (XLSX 97Â kb)
DOI: 10.6084/m9.figshare.c.3646001_d11
title: Additional file 4: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Short and long read assembly statistics of HR-12. (XLSX 16Â kb)
DOI: 10.6084/m9.figshare.c.3646001_d13
title: Additional file 15: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Functional annotation of variants in Co-39, HR-12, Tetep and Tadukan varieties. (XLSX 18Â kb)
DOI: 10.6084/m9.figshare.c.3646001_d12
title: Additional file 12: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Unique SSRs in HR-12 genome in comparison with Nipponbare and 93â  11. (XLSX 133Â kb)
DOI: 10.6084/m9.figshare.c.3646001_d14
title: Additional file 10: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Gene under positive selection in indica-indica and indica-japonica comparisons. (XLSX 21Â kb)
DOI: 10.6084/m9.figshare.c.3646001_d15
title: Additional file 13: of Indica rice genome assembly, annotation and mining of blast disease resistance genes

description: Repeat content in HR-12, Nipponbare and 93â  11 genomes. (XLSX 19Â kb)
DOI: 10.6084/m9.figshare.c.3646007_d1
title: Additional file 2: Table S4. of Seeking consent for research with indigenous communities: a systematic review

description: Research describing the consent process with Indigenous populations in detail. (XLSM 50Â kb)
DOI: 10.6084/m9.figshare.c.3646007_d2
title: Additional file 3: Table S5. of Seeking consent for research with indigenous communities: a systematic review

description: International guidelines for seeking consent for research with Indigenous populations. (XLSM 39Â kb)
DOI: 10.6084/m9.figshare.c.3646007_d3
title: Additional file 4: Table S6. of Seeking consent for research with indigenous communities: a systematic review

description: National guidelines on seeking consent for research with Indigenous populations. (XLSX 40Â kb)