cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.26627872
title: Additional file 7 of Association between gut microbiota and influenza: a bidirectional two-sample mendelian randomization study

description: Supplementary Material 7
DOI: 10.15468/dl.rwz7w6
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
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 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068556-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26627872.v1
title: Additional file 7 of Association between gut microbiota and influenza: a bidirectional two-sample mendelian randomization study

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.26627953
title: Additional file 6 of Exosomal Linc00969 induces trastuzumab resistance in breast cancer by increasing HER-2 protein expression and mRNA stability by binding to HUR

description: Additional file 6: Table S2. The CirRNAs that were differentially expressed in exosomes from trastuzumab-sensitive breast cancer tissues compared with trastuzumab-resistant breast cancer tissues.
DOI: 10.6084/m9.figshare.26627953.v1
title: Additional file 6 of Exosomal Linc00969 induces trastuzumab resistance in breast cancer by increasing HER-2 protein expression and mRNA stability by binding to HUR

description: Additional file 6: Table S2. The CirRNAs that were differentially expressed in exosomes from trastuzumab-sensitive breast cancer tissues compared with trastuzumab-resistant breast cancer tissues.
DOI: 10.6084/m9.figshare.26627863
title: Additional file 4 of Association between gut microbiota and influenza: a bidirectional two-sample mendelian randomization study

description: Supplementary Material 4
DOI: 10.6084/m9.figshare.26627818
title: Additional file 1 of A novel deep learning-based algorithm combining histopathological features with tissue areas to predict colorectal cancer survival from whole-slide images

description: Additional file 1: Table S1. The performance of different combinations of histopathological tissue.
DOI: 10.6084/m9.figshare.26627869.v1
title: Additional file 6 of Association between gut microbiota and influenza: a bidirectional two-sample mendelian randomization study

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.26627950
title: Additional file 5 of Exosomal Linc00969 induces trastuzumab resistance in breast cancer by increasing HER-2 protein expression and mRNA stability by binding to HUR

description: Additional file 5: Table S1. The lncRNAs that were differentially expressed in exosomes from trastuzumab-sensitive breast cancer tissues compared with trastuzumab-resistant breast cancer tissues.
DOI: 10.6084/m9.figshare.26627950.v1
title: Additional file 5 of Exosomal Linc00969 induces trastuzumab resistance in breast cancer by increasing HER-2 protein expression and mRNA stability by binding to HUR

description: Additional file 5: Table S1. The lncRNAs that were differentially expressed in exosomes from trastuzumab-sensitive breast cancer tissues compared with trastuzumab-resistant breast cancer tissues.
DOI: 10.6084/m9.figshare.26627866.v1
title: Additional file 5 of Association between gut microbiota and influenza: a bidirectional two-sample mendelian randomization study

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.26737026
title: Additional file 2 of Novel hypoxia- and lactate metabolism-related molecular subtyping and prognostic signature for colorectal cancer

description: Supplementary Material 2.
DOI: 10.15468/dl.vw88a8
title: Occurrence Download

description: A dataset containing 630 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is USGS Nonindigenous Aquatic Species database",
 "Geometry POLYGON((-92.31548 42.7768,-91.32131 42.7768,-91.32131 43.78062,-92.31548 43.78062,-92.31548 42.7768))",
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}

 The dataset includes 630 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068557-240626123714530/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.26627866
title: Additional file 5 of Association between gut microbiota and influenza: a bidirectional two-sample mendelian randomization study

description: Supplementary Material 5
DOI: 10.15468/dl.byvcty
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.412172 -33.233866, 148.412172 -33.236111, 148.418909 -33.236111, 148.418909 -33.233866, 148.412172 -33.233866))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068558-240626123714530/datasets/export for details.
DOI: 10.6084/m9.figshare.26066206.v1
title: Additional file 2 of An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

description: Additional file 2: Table S1. Contains all marker gene lists used for enrichment analyses in this manuscript.
DOI: 10.6084/m9.figshare.26736354
title: Additional file 3 of An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

description: Additional file 3: Table S2. Author annotations for acNMF GEPs in the GOSH dataset.
DOI: 10.6084/m9.figshare.26736360
title: Additional file 5 of An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

description: Additional file 5: Table S4. Network and Dataset-specific GEP annotation.
DOI: 10.6084/m9.figshare.26736360.v1
title: Additional file 5 of An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

description: Additional file 5: Table S4. Network and Dataset-specific GEP annotation.
DOI: 10.6084/m9.figshare.26736366
title: Additional file 7 of An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

description: Additional file 7: Table S6. Final annotations of GEMM gene expression programs.
DOI: 10.6084/m9.figshare.26736366.v1
title: Additional file 7 of An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

description: Additional file 7: Table S6. Final annotations of GEMM gene expression programs.
DOI: 10.6084/m9.figshare.26736369
title: Additional file 8 of An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

description: Additional file 8: Table S7. GSEA analysis of drug-induced transcriptional response in GEMM.
DOI: 10.6084/m9.figshare.26736372.v1
title: Additional file 9 of An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs

description: Additional file 9: Table S8. P-values relevant to Figure 6 (panels f-j).
DOI: 10.6084/m9.figshare.26737176
title: Additional file 12 of Cholesin receptor signalling is active in cardiovascular system-associated adipose tissue and correlates with SGLT2i treatment in patients with diabetes

description: Supplementary material 12: Supplementary Table 5.
DOI: 10.15468/dl.jt69j7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
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 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068559-240626123714530/datasets/export for details.
DOI: 10.15468/dl.ybevbf
title: Occurrence Download

description: A dataset containing 628 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Thailand, Myanmar, India, Viet Nam)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhododendron delavayi Franch."
 ]
}

 The dataset includes 628 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068560-240626123714530/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.26737188.v1
title: Additional file 2 of Comprehensive meta-analysis of severe fever with thrombocytopenia syndrome virus infections in humans, vertebrate hosts and questing ticks

description: Additional file 2: Table S2. Publications reporting RNA prevalence of SFTSV in vertebrate hosts.
DOI: 10.6084/m9.figshare.26737203
title: Additional file 7 of Comprehensive meta-analysis of severe fever with thrombocytopenia syndrome virus infections in humans, vertebrate hosts and questing ticks

description: Additional file 7: Table S5. Multivariable meta-regression analyses for RNA prevalence of SFTSV in vertebrate hosts.
DOI: 10.6084/m9.figshare.26737203.v1
title: Additional file 7 of Comprehensive meta-analysis of severe fever with thrombocytopenia syndrome virus infections in humans, vertebrate hosts and questing ticks

description: Additional file 7: Table S5. Multivariable meta-regression analyses for RNA prevalence of SFTSV in vertebrate hosts.
DOI: 10.6084/m9.figshare.26581184
title: Additional file 1 of Potential roles of the rectum keystone microbiota in modulating the microbial community and growth performance in goat model

description: Additional file 1: Table S1. The feeding programs of the experiment goats. Table S2. The relationship between rectum microbiota (relative abundance &gt; 0.1%) and ADG of young goats (n = 76). Table S3. The topological roles of ASV in the HADG and LADG network. Table S4. The relationship between ADG-related bacteria in all young goats (n = 76, Spearman’s correlation, P &lt; 0.05). Table S5. The relationship between NH3-N, lactate and growth performance traits of young goats (n = 76). Table S6. Prediction of the differential function of rectum microbiota between young goats (n = 20) and adult goats (n = 16) in KEGG pathways based on PICRUSt2. The P value was calculated based on the Wilcoxon rank-sum test.
DOI: 10.6084/m9.figshare.26581247
title: Additional file 2 of Rocuronium bromide suppresses esophageal cancer via blocking the secretion of C–X–C motif chemokine ligand 12 from cancer associated fibroblasts

description: Additional file 2: Table S1. DEGs of human fibroblasts treated by RB. DEGs screening condition is (log2FC &gt; 1 or &lt; -1, P &lt; 0.05)
DOI: 10.15468/dl.chcrq9
title: Occurrence Download

description: A dataset containing 12755075 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((72.78327 36.70618,86.99782 24.20906,115.54844 19.80228,122.37986 27.79295,123.20603 38.63232,134.94541 45.58627,132.32599 52.08344,120.6642 53.43073,104.61979 43.11753,81.35668 49.24534,72.78327 36.70618))",
 "HasGeospatialIssue is false",
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 "Year 2010-2024"
 ]
}

 The dataset includes 12755075 records from 2404 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068555-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vevrmp
title: Occurrence Download

description: A dataset listing the 155 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((21.53755 -18.13246,21.56792 -18.13246,21.56792 -18.10105,21.53755 -18.10105,21.53755 -18.13246))",
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}

 The dataset's 155 records were derived from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069465-250525065834625/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.28386774
title: Additional file 5 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.28386774.v1
title: Additional file 5 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 5
DOI: 10.6084/m9.figshare.28386777
title: Additional file 6 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.28386777.v1
title: Additional file 6 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 6
DOI: 10.6084/m9.figshare.28386780
title: Additional file 7 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.28386780.v1
title: Additional file 7 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 7
DOI: 10.6084/m9.figshare.28386783
title: Additional file 8 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 8
DOI: 10.6084/m9.figshare.28386783.v1
title: Additional file 8 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 8
DOI: 10.6084/m9.figshare.28386786
title: Additional file 9 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 9
DOI: 10.6084/m9.figshare.28386789
title: Additional file 10 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 10
DOI: 10.6084/m9.figshare.28386789.v1
title: Additional file 10 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 10
DOI: 10.6084/m9.figshare.28386792
title: Additional file 11 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 11
DOI: 10.6084/m9.figshare.28386792.v1
title: Additional file 11 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 11
DOI: 10.6084/m9.figshare.28386786.v1
title: Additional file 9 of Identification and validation of genomic regions for pod shatter resistance in Brassica rapa using QTL-seq and traditional QTL mapping

description: Supplementary Material 9
DOI: 10.34740/kaggle/dsv/10718445
title: Egypt Gold Prices | Daily Updated
DOI: 10.6084/m9.figshare.28386772
title: Additional file 6 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 6.
DOI: 10.6084/m9.figshare.28386772.v1
title: Additional file 6 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 6.
DOI: 10.6084/m9.figshare.28386775
title: Additional file 7 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 7.
DOI: 10.6084/m9.figshare.28386775.v1
title: Additional file 7 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 7.
DOI: 10.6084/m9.figshare.28386778
title: Additional file 8 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 8.
DOI: 10.6084/m9.figshare.28386778.v1
title: Additional file 8 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 8.
DOI: 10.6084/m9.figshare.28386781
title: Additional file 9 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 9.
DOI: 10.6084/m9.figshare.28386781.v1
title: Additional file 9 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 9.
DOI: 10.6084/m9.figshare.28386784
title: Additional file 10 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 10.
DOI: 10.6084/m9.figshare.28386784.v1
title: Additional file 10 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 10.
DOI: 10.6084/m9.figshare.28386790
title: Additional file 11 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 11.
DOI: 10.6084/m9.figshare.28386790.v1
title: Additional file 11 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 11.
DOI: 10.6084/m9.figshare.28386793
title: Additional file 12 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 12.
DOI: 10.6084/m9.figshare.28386793.v1
title: Additional file 12 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 12.
DOI: 10.6084/m9.figshare.28386796
title: Additional file 13 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 13.
DOI: 10.6084/m9.figshare.28386796.v1
title: Additional file 13 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 13.
DOI: 10.6084/m9.figshare.28386799
title: Additional file 14 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 14.
DOI: 10.6084/m9.figshare.28386799.v1
title: Additional file 14 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 14.
DOI: 10.6084/m9.figshare.28386802
title: Additional file 15 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 15.
DOI: 10.6084/m9.figshare.28386802.v1
title: Additional file 15 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 15.
DOI: 10.6084/m9.figshare.28386805
title: Additional file 16 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 16.
DOI: 10.6084/m9.figshare.28386805.v1
title: Additional file 16 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 16.
DOI: 10.6084/m9.figshare.28386808.v1
title: Additional file 17 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 17.
DOI: 10.6084/m9.figshare.28386808
title: Additional file 17 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 17.
DOI: 10.6084/m9.figshare.28386811
title: Additional file 18 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 18.
DOI: 10.6084/m9.figshare.28386811.v1
title: Additional file 18 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 18.
DOI: 10.6084/m9.figshare.28386814
title: Additional file 19 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 19.
DOI: 10.6084/m9.figshare.28386814.v1
title: Additional file 19 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 19.
DOI: 10.6084/m9.figshare.28386817
title: Additional file 20 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 20.
DOI: 10.6084/m9.figshare.28386817.v1
title: Additional file 20 of Predicting substrates for orphan solute carrier proteins using multi-omics datasets

description: Supplementary Material 20.
DOI: 10.6084/m9.figshare.28386822
title: Additional file 1 of Microbial profiling of black soldier fly larvae reared on substrates supplemented with different mineral sources originating from phosphorus recycling technologies

description: Additional file 1.
DOI: 10.6084/m9.figshare.28386822.v1
title: Additional file 1 of Microbial profiling of black soldier fly larvae reared on substrates supplemented with different mineral sources originating from phosphorus recycling technologies

description: Additional file 1.
DOI: 10.6084/m9.figshare.28386828
title: Additional file 3 of Microbial profiling of black soldier fly larvae reared on substrates supplemented with different mineral sources originating from phosphorus recycling technologies

description: Additional file 3.
DOI: 10.6084/m9.figshare.28386828.v1
title: Additional file 3 of Microbial profiling of black soldier fly larvae reared on substrates supplemented with different mineral sources originating from phosphorus recycling technologies

description: Additional file 3.
DOI: 10.5281/zenodo.14848021
title: AI-Generated Code Dataset
DOI: 10.5281/zenodo.14848022
title: AI-Generated Code Dataset
DOI: 10.5281/zenodo.14839921
title: unimpeded: lcdm bicep_keck_2018+planck_2018_CamSpec_nolens

description: cosmological model:lcdm, dataset:bicep_keck_2018+planck_2018_CamSpec_nolens
DOI: 10.5281/zenodo.14839922
title: unimpeded: lcdm bicep_keck_2018+planck_2018_CamSpec_nolens

description: cosmological model:lcdm, dataset:bicep_keck_2018+planck_2018_CamSpec_nolens
DOI: 10.5281/zenodo.14839927
title: unimpeded: lcdm bicep_keck_2018+planck_2018_plik_nolens

description: cosmological model:lcdm, dataset:bicep_keck_2018+planck_2018_plik_nolens
DOI: 10.5281/zenodo.14839928
title: unimpeded: lcdm bicep_keck_2018+planck_2018_plik_nolens

description: cosmological model:lcdm, dataset:bicep_keck_2018+planck_2018_plik_nolens
DOI: 10.6084/m9.figshare.28386626
title: AlphaFold3 Structure predictions for Spodoptera fruigperda corn and rice mis-annotated GST genes

description: AlphaFold3 Structure predictions for Spodoptera fruigperda corn and rice mis-annotated GST genes. <br>Amino acid sequences from the BIPAA corn and rice annotations provided. Target sequences extracted and structures generated with the online portal of AlphaFold3 on 11/02/2025. All data provided from AlphaFold3 prediction. Spodoptera frugiperda annotation versions - Corn = OGS7.0_20190530; Rice = OGS4.0_20180609.
DOI: 10.5281/zenodo.14840017
title: unimpeded: walcdm bicep_keck_2018+planck_2018_plik

description: cosmological model:walcdm, dataset:bicep_keck_2018+planck_2018_plik
DOI: 10.5281/zenodo.14840018
title: unimpeded: walcdm bicep_keck_2018+planck_2018_plik

description: cosmological model:walcdm, dataset:bicep_keck_2018+planck_2018_plik