cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.c.3612344_d4
title: Additional file 6: of De novo analysis of transcriptome reveals genes associated with leaf abscission in sugarcane (Saccharum officinarum L.)

description: ABA-associated transcripts upregulated in Q2 in comparison of Q1. (XLSX 38 kb)
DOI: 10.6084/m9.figshare.c.3612344_d3
title: Additional file 4: of De novo analysis of transcriptome reveals genes associated with leaf abscission in sugarcane (Saccharum officinarum L.)

description: KEGG pathway analysis for Q1 sugarcane upregulated transcripts relatively to Q2 sugarcane. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.c.3612344_d2
title: Additional file 7: of De novo analysis of transcriptome reveals genes associated with leaf abscission in sugarcane (Saccharum officinarum L.)

description: Primer sequences used in qRT-PCR experiment. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.c.3612344_d1
title: Additional file 1: of De novo analysis of transcriptome reveals genes associated with leaf abscission in sugarcane (Saccharum officinarum L.)

description: Number of sugarcane transcripts aligned to different species. (XLSX 19 kb)
DOI: 10.15468/dl.95atcp
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Etelis carbunculus Cuvier, 1828",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 45 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032222-241126133413365/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.3612191_d3
title: Additional file 1: of Identification of potential mutations and genomic alterations in the epithelial and spindle cell components of biphasic synovial sarcomas using a human exome SNP chip

description: The summary of 336 differentiated data of SNP. (XLSX 91Â kb)
DOI: 10.6084/m9.figshare.c.3612191_d4
title: Additional file 2: of Identification of potential mutations and genomic alterations in the epithelial and spindle cell components of biphasic synovial sarcomas using a human exome SNP chip

description: Enrichment analysis of the Pathway Commons Pathway of differentiated genes. (HTML 20Â kb)
DOI: 10.6084/m9.figshare.c.3612191_d1
title: Additional file 3: of Identification of potential mutations and genomic alterations in the epithelial and spindle cell components of biphasic synovial sarcomas using a human exome SNP chip

description: Enrichment analysis of the Wikipathways Pathway of differentiated genes. (HTML 24Â kb)
DOI: 10.6084/m9.figshare.c.3612191_d2
title: Additional file 4: of Identification of potential mutations and genomic alterations in the epithelial and spindle cell components of biphasic synovial sarcomas using a human exome SNP chip

description: Enrichment analysis of the KEGG Pathway of differentiated genes. (HTML 26Â kb)
DOI: 10.6084/m9.figshare.c.3612134_d9
title: MOESM2 of Oestrogen receptor β regulates epigenetic patterns at specific genomic loci through interaction with thymine DNA glycosylase

description: Additional file 2. Genes differently expressed in wt and βerko MEFs. List of genes that show changed expression in βerko compared to wt MEFs assessed by microarray gene expression analyses using the Affymetrix® Mouse Gene 1.1. ST platform. The list includes fold change, p value, chromosomal location, gene name and annotation.
DOI: 10.6084/m9.figshare.c.3612158_d3
title: Additional file 3 of Analyzing Th17 cell differentiation dynamics using a novel integrative modeling framework for time-course RNA sequencing data

description: Implementation of population-based Markov chain Monte Carlo in Matlab. (ZIP 46 kb)
DOI: 10.6084/m9.figshare.c.3612134_d7
title: MOESM6 of Oestrogen receptor β regulates epigenetic patterns at specific genomic loci through interaction with thymine DNA glycosylase

description: Additional file 6. Links to enriched transcription factor motifs identified using Haystack software.
DOI: 10.6084/m9.figshare.c.3612158_d1
title: Additional file 2 of Analyzing Th17 cell differentiation dynamics using a novel integrative modeling framework for time-course RNA sequencing data

description: Mathematical model encoded in SBML. (XML 28 kb)
DOI: 10.6084/m9.figshare.c.3612134_d5
title: MOESM4 of Oestrogen receptor β regulates epigenetic patterns at specific genomic loci through interaction with thymine DNA glycosylase

description: Additional file 4. Genomic location of the identified EREs.
DOI: 10.6084/m9.figshare.c.3612140_d3
title: Additional file 1: Table S1. of Multi-layered Gag-specific immunodominant responses contribute to improved viral control in the CRF01_AE subtype of HIV-1-infected MSM subjects

description: Peptide matrix setup for Gag, Pol and Nef. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.c.3612134_d4
title: MOESM5 of Oestrogen receptor β regulates epigenetic patterns at specific genomic loci through interaction with thymine DNA glycosylase

description: Additional file 5. Links to enriched transcription factor motifs identified using Haystack software.
DOI: 10.6084/m9.figshare.c.3612119_d6
title: Additional file 3: Table S3. of Transcriptomic analysis of mouse liver reveals a potential hepato-enteric pathogenic mechanism in acute Toxoplasma gondii infection

description: Differentially expressed molecular functions. (XLSX 37Â kb)
DOI: 10.6084/m9.figshare.c.3612134_d2
title: MOESM3 of Oestrogen receptor β regulates epigenetic patterns at specific genomic loci through interaction with thymine DNA glycosylase

description: Additional file 3. Genes differently expressed in βerko and βerkohERβ MEFs. List of genes that show changed expression in βerkohERβ compared to βerko MEFs assessed by microarray gene expression analyses using the Affymetrix® Mouse Gene 1.1. ST platform. The list includes fold change, p value, chromosomal location, gene name and annotation.
DOI: 10.6084/m9.figshare.c.3612119_d4
title: Additional file 6: Table S6. of Transcriptomic analysis of mouse liver reveals a potential hepato-enteric pathogenic mechanism in acute Toxoplasma gondii infection

description: Relationship between differentially expressed genes and liver diseases. (XLSX 44Â kb)
DOI: 10.6084/m9.figshare.c.3612140_d1
title: Additional file 2: Table S2. of Multi-layered Gag-specific immunodominant responses contribute to improved viral control in the CRF01_AE subtype of HIV-1-infected MSM subjects

description: Sequences, position and HLA restriction of optimal epitopes used in this study. (XLSX 24 kb)
DOI: 10.6084/m9.figshare.c.3611879_d16
title: Additional file 16 of The Local Edge Machine: inference of dynamic models of gene regulation

description: Table: Compilation of literature that supports the designation of circadian core nodes. The first column gives the names of the genes that were considered to be circadian core genes in our analysis. The second column provides any alternative gene names, and the third column lists literature references that support the designation of the corresponding gene as being part of the circadian core. (XLSX 54 kb)
DOI: 10.6084/m9.figshare.c.3611879_d14
title: Additional file 2 of The Local Edge Machine: inference of dynamic models of gene regulation

description: Table: Biological prior information about gene function used for LEM inference on yeast cell-cycle networks 1â  5. LEM can incorporate biological priors to remove any impossible edges (e.g., a TF known to be an activator cannot repress a given target), which improves inference on real data (see Additional files 5 and 13). Here we provide literature evidence for TFs that function as an activator of target gene transcription, repressor, or both. Genes marked N/A do not function as TFs. Note 1. CLN3 is included as a regulator in networks 1, 2, and 5 because it is known to inhibit Whi5 at cell-cycle START [2]. The other cyclins, CLN2 and CLB2, are not included as regulators because their effects on TFs are redundant with other edges included in the networks (instead, CLN2 and CLB2 are used to represent canonical targets of TFs in the networks). Note 2. PLM2 is lacking specific literature evidence for its role as a TF activator. However, PLM2 is a paralog of TOS4 from the S. cerevisiae whole-genome duplication, and we propose that the activator function is shared between the paralogs. (XLSX 43 kb)
DOI: 10.6084/m9.figshare.c.3611879_d11
title: Additional file 7 of The Local Edge Machine: inference of dynamic models of gene regulation

description: Table: Saccharomyces cerevisiae gene expression dynamics used in this study. The wild-type gene expression data of 28 genes over approximately two cell cycles were obtained from previous work [2]. Expression values from each profile were smoothed from 13 experimental time points to 40 time points by fitting a cubic spline (the function splinefun in R package stats). A Rescon Ltd. tool was used to rank the splined profiles by 50 % of the peak expression value. Genes are ordered from earliest (top) to latest (bottom) half-maximal expression and presented in the heat map in Fig. 1. (XLSX 51 kb)
DOI: 10.6084/m9.figshare.c.3611879_d9
title: Additional file 3 of The Local Edge Machine: inference of dynamic models of gene regulation

description: Table: Evidence for regulatory interactions in yeast cell-cycle networks 1â  5. Each row corresponds to a regulatory interaction (edge), where an upstream regulator acts on a target gene. p values from four high-throughput chromatin immunoprecipitation (ChIP) studies are shown to provide evidence (when available) for a regulator transcription factor (TF) binding to a target promoter [11, 50, 51]. ChIP p values were combined using Fisherâ  s method [52]. Combined p values less than 0.001 were considered high-confidence evidence for a given edge (shown in bold red). Where available, edges are supported by additional literature references (see Additional file 8). In the absence of ChIP data, literature evidence was used to determine edges. Evidence for many edges provided here is also documented in the YEASTRACT database [42]. The direction of each interaction (activation, repression, or N/A unknown) is derived from the YEASTRACT database, literature evidence, and/or biological priors about gene function (see Additional file 1). (XLSX 75 kb)
DOI: 10.15468/dl.mycuwe
title: Occurrence Download

description: A dataset containing 5840 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Geometry POLYGON((-12.2044 35.39179,46.64022 35.39179,46.64022 71.04976,-12.2044 71.04976,-12.2044 35.39179))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Psilocybe semilanceata (Fr.) P.Kumm."
 ]
}

 The dataset includes 5840 records from 131 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032223-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jzkj4u
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cheilopogon pinnatibarbatus (Bennett, 1831)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 43 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032224-241126133413365/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.3611765_d7
title: Additional file 10: of Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

description: The gene list and expression patterns for all transcription factors involved in all tissues and stress treatments. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.c.3611765_d8
title: Additional file 13: of Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

description: Gene information used for qRT-PCR verification of RNA-Seq data and corresponding expression patterns extracted by RNA-Seq. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.c.3611765_d6
title: Additional file 11: of Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

description: Enriched motif analysis in each group involved in roots and different stress levels. The DREAM tool was used to reveal over-represented elements in the promoter regions of certain groups of genes that were differentially regulated in roots and different stress levels. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.c.3611765_d4
title: Additional file 1: of Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

description: Gene annotation and expression analysis for primary metabolism. (XLSX 26 kb)
DOI: 10.6084/m9.figshare.c.3611765_d5
title: Additional file 7: of Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

description: Gene annotation and expression analysis of JA, GA, and SA synthesis and the response pathway. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.c.3611765_d3
title: Additional file 3: of Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

description: Gene annotation and expression analysis for carbohydrate metabolism. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.c.3611765_d1
title: Additional file 2: of Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

description: Gene annotation and expression analysis for secondary metabolism. (XLSX 19 kb)
DOI: 10.6084/m9.figshare.c.3611765_d2
title: Additional file 5: of Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

description: Gene annotation and expression analysis of ethylene synthesis and the response pathway. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.c.3611741_d1
title: Additional file 3: of Nosocomial outbreak of KPC-2- and NDM-1-producing Klebsiella pneumoniae in a neonatal ward: a retrospective study

description: Raw data of minimal inhibitory concentration. (XLSX 13Â kb)
DOI: 10.6084/m9.figshare.c.3611717_d6
title: Additional file 3: of Nonlinear transcriptomic response to dietary fat intake in the small intestine of C57BL/6J mice

description: Differentially expressed genes (normalized and processed data) in the three sections of small intestine. There are 1,976 genes in the proximal section, 2,489 genes in the middle part and 313 genes in the distal section. For each gene we indicated Affymetrix ID, gene symbol, response type (lm = linear, log = logarithmic, exp = exponential, quad = quadratic and cub = cubic), and response direction (either up- or down-regulated). Last 40 columns refer to log2 transformed expression values in the small intestine of mice fed with 10, 20, 30 and 45 E% from fat. (XLSX 2795 kb)
DOI: 10.6084/m9.figshare.c.3611564_d11
title: Additional file 11: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Measurement reliability at low sequencing depth. As Fig.Â 4kâ  m, but using low-depth in silico samples in place of individual 10Â pg. replicates. (A) aRNA. (B) SmartSeq Plus. (C) NuGen. (XLS 329 kb)
DOI: 10.6084/m9.figshare.c.3611564_d12
title: Additional file 13: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Optimization dataset sample identification, protocol information, and RNA sequencing stats. As Additional file 1 for samples used in protocol optimization analyses. (XLS 37 kb)
DOI: 10.6084/m9.figshare.c.3611564_d10
title: Additional file 9: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Precision outliers. Genes with residuals within the upper or lower 1%ile with respect to regression of standard deviation on the mean (see Methods ). â  Gene setâ   indicates whether gene is classified as computationally unambiguous (1) or not (2). Only genes whose mean is within the range of fitted model were included. Column values indicate whether indicate whether the gene standard deviation is unexpectedly low (L) or high (H), given mean. (XLS 114 kb)
DOI: 10.6084/m9.figshare.c.3611564_d8
title: Additional file 10: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Accuracy outliers. Genes were identified as accuracy outliers if its median fold deviation, taken across dilution replicates, was contained in the upper or lower 1%ile of all considered genes (see Methods ). Columns labeled by single-cell protocol contain an “H” if a gene was identified as an overestimated outlier, and an “L” if a gene was identified as an underestimated outlier. “Gene set” indicates whether gene is classified as computationally unambiguous (1) or not (2). (XLS 218 kb)
DOI: 10.6084/m9.figshare.c.3611564_d9
title: Additional file 6: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Gene detection logistic regression fit and validation. Model was fit using randomly selected 90% of 10 pg. data, excluding 17 large influence genes. Fit was evaluated on the remaining 10% of the data. Fit was also evaluated on sequence data that was in silico truncated to 50 base pair single end (“Truncated”), ERCC read counts (“ERCC”), and 100 pg. dilution replicates (“100 pg.”). AUC (area under receiver operating characteristic curve) reported as mean values ± 2 Sd. calculated over 10,000 bootstrap samples. AUC (molecules) predicts detection based on number of input molecules alone. See Methods for further details. (XLS 29 kb)
DOI: 10.6084/m9.figshare.c.3611564_d7
title: Additional file 5: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Gene detection logistic regression model. See model details in Methods . Abbreviations: M expected number of input molecules; L gene length (kilobases); G gene GC content; S strength of gene local secondary structure (kilocalories per mole); hasA presence of A-hexamer internal to gene body; D Depth (per 10,000,000 reads); S.E. standard error; Wald Z Wald test statistic; Pr(&gt;|Z|) Wald test p-value. (XLS 40 kb)
DOI: 10.6084/m9.figshare.c.3611564_d5
title: Additional file 4: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Number of detected genes for low-depth in silico samples. As Fig.Â 2a, except that each dilution replicate has been subsampled to a depth of 500,000 unique genic reads. (XLS 74 kb)
DOI: 10.6084/m9.figshare.c.3611564_d4
title: Additional file 1: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Control dataset sample identification, protocol information, and RNA sequencing stats. Experimental group, protocol information and RNA sequencing statistics for each sample used in primary analyses. Alignment statistics were based on STAR alignment to hg19 and were with respect to reads retained after trimming for primer or poly-A sequences [21]. (XLS 62 kb)
DOI: 10.6084/m9.figshare.c.3611564_d3
title: Additional file 12: of Assessing characteristics of RNA amplification methods for single cell RNA sequencing

description: Normalized read counts and expectation for ERCC transcripts. A–B. ERCC transcripts are found along the x-axis, ordered by expected number of input molecules. Axis labels are in the format of “ERCC spike-in ID, expected number of input molecules”. Points indicate the normalized read count for one transcript in one sample. Horizontal gray lines and background gray boxes indicate the expected normalized read count and a 95% CI under a Poisson model of dilution. Wide red horizontal lines indicate mean normalized read counts across all ERCC transcripts with a common expected number of input molecule, and red boxes indicate mean ± 2 × s.e.m. (A) aRNA. (B) SmartSeq Plus. (XLS 964 kb)
DOI: 10.6084/m9.figshare.c.3611525_d3
title: Additional file 3: of Identification of new biomarkers for Acute Respiratory Distress Syndrome by expression-based genome-wide association study

description: Table S3.Â Contribution of each ARDS model to the overall gene expression signal of an ARDS gene candidate. Each dataset obtained from GEO was reanalyzed using SAM 2.0. The d-score and fold change values for 42 gene candidates were extracted from SAM 2.0 outputs and reported according to the ARDS model. (XLSX 45Â kb)
DOI: 10.6084/m9.figshare.c.3611525_d2
title: Additional file 2: of Identification of new biomarkers for Acute Respiratory Distress Syndrome by expression-based genome-wide association study

description: Table S2. Chi-square values of cross-referenced genes. Given that different microarray platforms have multiple probes for a single gene, the cross-referencing of such platforms generates numerous combinations of expression values for a given gene (32160 in this study). Chi-square value was calculated for each of these combinations and combination with the best chi-square value for a given gene was retained, which resulted in 3152 unique gene entries. These genes were linked to human genome and plotted against their location (Fig. 1). (XLS 185Â kb)
DOI: 10.6084/m9.figshare.c.3611525_d1
title: Additional file 1: of Identification of new biomarkers for Acute Respiratory Distress Syndrome by expression-based genome-wide association study

description: Table S1. Detailed representation of data obtained from GEO. ARDS gene expression submissions were retrieved from GEO using two terms “Acute lung injury” and “Lung injury”, which resulted in 23 and 25 data sets, respectively. These 48 entries were filtered down to 31 entries according to conditions described in Methods. The reason for filtering out an experiment is provided. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.c.3611513_d3
title: Additional file 2: of Quantitative trait loci analysis of Verticillium wilt resistance in interspecific backcross populations of Gossypium hirsutumâ  Ă â  Gossypium barbadense

description: The phenotype datasets of BC2F1 on June 23, July 19, August 15, and August 25 in 2005 in the artificial disease nursery and of BC2F1 and BC1S1 on 17 September in 2005 in the field. (XLSX 27 kb)
DOI: 10.6084/m9.figshare.c.3611513_d2
title: Additional file 1: of Quantitative trait loci analysis of Verticillium wilt resistance in interspecific backcross populations of Gossypium hirsutum × Gossypium barbadense

description: The details of QTLs identified using interspecific backcross populations on the map of CCRI36 × Hai1 BC1F1 and their corresponding hotspots. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.c.3611513_d1
title: Additional file 3: of Quantitative trait loci analysis of Verticillium wilt resistance in interspecific backcross populations of Gossypium hirsutum × Gossypium barbadense

description: The genotype datasets of 135 BC1F1 plants of CCRI36× Hai1. (XLSX 1247 kb)