cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4478250
title: The growth of COVID-19 scientific literature: A forecast analysis of different daily time series in specific settings

description: Submitted to The ISSI 2021 Conference. The conference is organised by KU Leuven in close collaboration with the university of Antwerp under the auspices of ISSI – the International Society for Informetrics and Scientometrics (http://www.issi-society.org/). We present a forecasting analysis on the growth of scientific literature related to COVID-19 expected for 2021. Considering the paramount scientific and financial efforts made by the research community to find solutions to end the COVID-19 pandemic, an unprecedented volume of scientific outputs is being produced. This questions the capacity of scientists, politicians and citizens to maintain infrastructure, digest content and take scientifically informed decisions. A crucial aspect is to make predictions to prepare for such a large corpus of scientific literature. Here we base our predictions on the ARIMA model and use two different data sources: the Dimensions and World Health Organization COVID-19 databases. These two sources have the particularity of including in the metadata information on the date in which papers were indexed. We present global predictions, plus predictions in three specific settings: by type of access (Open Access), by NLM source (PubMed and PMC), and by domain-specific repository (SSRN and MedRxiv). We conclude by discussing our findings.
DOI: 10.21942/uva.13655516.v1
title: GerAB

description: <i>Bacillus</i> <i>subtilis</i> forms dormant spores upon nutrient depletion. Germinant receptors (GRs) in spore’s inner membrane respond to ligands such as L-alanine, and trigger spore germination. In <i>B. subtilis</i> spores, GerA is the major GR, and has three subunits, GerAA, GerAB, and GerAC. L-Alanine activation of GerA requires all three subunits, but which binds L-alanine is unknown. To date, how GRs trigger germination is unknown, in particular due to lack of detailed structural information about B subunits. Using homology modelling with molecular dynamics (MD) simulations, we present structural predictions for the integral membrane protein GerAB. These predictions indicate that GerAB is an alpha-helical transmembrane protein containing a water channel. The MD simulations with free L-alanine show that alanine binds transiently to specific sites on GerAB. These results provide a starting point for unraveling the mechanism of L-alanine mediated signaling by GerAB, which may facilitate early events in spore germination.
DOI: 10.6084/m9.figshare.13662257
title: Policy Evolution Analysis

description: The dataset is the supporting information of a paper that focuses on the evolution analysis of provincial new energy policy tools in China<br>
DOI: 10.6084/m9.figshare.13662534.v1
title: Additional file 2 of Patterns of introgression vary within an avian hybrid zone

description: Additional file 2. Metadata for sparrow individuals from 2016 & 2017 sampled in this study .
DOI: 10.6084/m9.figshare.13662534
title: Additional file 2 of Patterns of introgression vary within an avian hybrid zone

description: Additional file 2. Metadata for sparrow individuals from 2016 & 2017 sampled in this study .
DOI: 10.6084/m9.figshare.13662537.v1
title: Additional file 3 of Patterns of introgression vary within an avian hybrid zone

description: Additional file 3. Fixed SNP panel (135) for all individuals.
DOI: 10.6084/m9.figshare.13662537
title: Additional file 3 of Patterns of introgression vary within an avian hybrid zone

description: Additional file 3. Fixed SNP panel (135) for all individuals.
DOI: 10.6084/m9.figshare.13662543
title: Additional file 4 of Patterns of introgression vary within an avian hybrid zone

description: Additional file 4. Paternity SNP panel (589) for hybrid zone center individuals.
DOI: 10.6084/m9.figshare.13662543.v1
title: Additional file 4 of Patterns of introgression vary within an avian hybrid zone

description: Additional file 4. Paternity SNP panel (589) for hybrid zone center individuals.
DOI: 10.6084/m9.figshare.13662567.v1
title: Additional file 3 of Ceftiofur reduced Fusobacterium leading to uterine microbiota alteration in dairy cows with metritis

description: Additional file 3: Table S2. Metadata, MG-RAST IDs, and sequence results.
DOI: 10.6084/m9.figshare.13662567
title: Additional file 3 of Ceftiofur reduced Fusobacterium leading to uterine microbiota alteration in dairy cows with metritis

description: Additional file 3: Table S2. Metadata, MG-RAST IDs, and sequence results.
DOI: 10.5281/zenodo.4478247
title: Count agronomic phenotypes

description: Data contains 976 wheat lines from the CIMMYT Global Wheat Program
DOI: 10.5281/zenodo.4478246
title: Count agronomic phenotypes

description: Data contains 976 wheat lines from the CIMMYT Global Wheat Program
DOI: 10.5519/qd.uhs44nzm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4872 records)
DOI: 10.6084/m9.figshare.13662693
title: Additional file 1 of Phylogenetic signal in floral temperature patterns

description: Additional file 1. Comma delimited data file, reformatting the used subset of the data originally presented in [48].
DOI: 10.6084/m9.figshare.13662693.v1
title: Additional file 1 of Phylogenetic signal in floral temperature patterns

description: Additional file 1. Comma delimited data file, reformatting the used subset of the data originally presented in [48].
DOI: 10.6084/m9.figshare.13662699.v1
title: Additional file 2 of Phylogenetic signal in floral temperature patterns

description: Additional file 2. R code file describing analysis (opens as a text file).
DOI: 10.6084/m9.figshare.13662705
title: Additional file 3 of Phylogenetic signal in floral temperature patterns

description: Additional file 3. Text file presenting temperature data reordered for use with phylo4d data structures.
DOI: 10.6084/m9.figshare.13662705.v1
title: Additional file 3 of Phylogenetic signal in floral temperature patterns

description: Additional file 3. Text file presenting temperature data reordered for use with phylo4d data structures.
DOI: 10.6084/m9.figshare.13662699
title: Additional file 2 of Phylogenetic signal in floral temperature patterns

description: Additional file 2. R code file describing analysis (opens as a text file).
DOI: 10.6084/m9.figshare.13662789
title: Additional file 7 of The pleiotropic effects of prebiotic galacto-oligosaccharides on the aging gut

description: Additional file 7: Table S2. Expression data from colons of young and old mice fed either the control or GOS diets.
DOI: 10.6084/m9.figshare.13662789.v1
title: Additional file 7 of The pleiotropic effects of prebiotic galacto-oligosaccharides on the aging gut

description: Additional file 7: Table S2. Expression data from colons of young and old mice fed either the control or GOS diets.
DOI: 10.6084/m9.figshare.13662804
title: Additional file 1 of A preliminary study: designing and validating projective images of Young’s early maladaptive schema (EMS) domains

description: Additional file 1. Images data.
DOI: 10.6084/m9.figshare.13662804.v1
title: Additional file 1 of A preliminary study: designing and validating projective images of Young’s early maladaptive schema (EMS) domains

description: Additional file 1. Images data.
DOI: 10.6084/m9.figshare.13662942
title: Additional file 1 of Evaluation of genetic structure in European wheat cultivars and advanced breeding lines using high-density genotyping-by-sequencing approach

description: Additional file 1.
DOI: 10.6084/m9.figshare.13662942.v1
title: Additional file 1 of Evaluation of genetic structure in European wheat cultivars and advanced breeding lines using high-density genotyping-by-sequencing approach

description: Additional file 1.
DOI: 10.6084/m9.figshare.13662951
title: Additional file 11 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 11: Table S5. Enriched biological processes by Gene Ontology analysis.
DOI: 10.6084/m9.figshare.13662951.v1
title: Additional file 11 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 11: Table S5. Enriched biological processes by Gene Ontology analysis.
DOI: 10.6084/m9.figshare.13662978.v1
title: Additional file 5 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 5: Table S1. H3K27me3, H3K4me2 and H3K4me3 levels (median, IQR) according to patient and disease characteristics in AML.
DOI: 10.6084/m9.figshare.13662981
title: Additional file 6 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 6: Table S2. H3K27me3, H4K4me2, H3K4me3 levels (median, IQR) according to patient and disease characteristics in ALL.
DOI: 10.6084/m9.figshare.13662978
title: Additional file 5 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 5: Table S1. H3K27me3, H3K4me2 and H3K4me3 levels (median, IQR) according to patient and disease characteristics in AML.
DOI: 10.6084/m9.figshare.13662981.v1
title: Additional file 6 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 6: Table S2. H3K27me3, H4K4me2, H3K4me3 levels (median, IQR) according to patient and disease characteristics in ALL.
DOI: 10.6084/m9.figshare.13662984
title: Additional file 7 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 7: Table S3. Pairwise associations between driver mutations presented by Pearson's Correlation Coefficient (cor) and p-value (p).
DOI: 10.6084/m9.figshare.13662984.v1
title: Additional file 7 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 7: Table S3. Pairwise associations between driver mutations presented by Pearson's Correlation Coefficient (cor) and p-value (p).
DOI: 10.6084/m9.figshare.13662987
title: Additional file 8 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 8: Table S4. Pairwise associations between affected pathways presented by Pearson's Correlation Coefficient (cor) and p-value (p).
DOI: 10.6084/m9.figshare.13662987.v1
title: Additional file 8 of Loss of H3K27 methylation identifies poor outcomes in adult-onset acute leukemia

description: Additional file 8: Table S4. Pairwise associations between affected pathways presented by Pearson's Correlation Coefficient (cor) and p-value (p).
DOI: 10.6084/m9.figshare.13663035
title: Additional file 1 of Higher genome variability within metabolism genes associates with recurrent Clostridium difficile infection

description: Additional file 1 Further data are available as Supplementary Tables: Table S1. COG categories prevalence in C. difficile core genome. Table S2. KEGG pathways present in core genome. Table S3. Logistic regression results for odds of infection recurrence after adjustment for ST. Table S4. Gene set enrichment analysis for results of logistic regression. Table S5. Log-likelihood ratio test results for comparison between M2a and M1a models. Table S6. Fisher’s exact test results for prevalence difference in prophage sequence between single and recurrent infections.
DOI: 10.6084/m9.figshare.13663035.v1
title: Additional file 1 of Higher genome variability within metabolism genes associates with recurrent Clostridium difficile infection

description: Additional file 1 Further data are available as Supplementary Tables: Table S1. COG categories prevalence in C. difficile core genome. Table S2. KEGG pathways present in core genome. Table S3. Logistic regression results for odds of infection recurrence after adjustment for ST. Table S4. Gene set enrichment analysis for results of logistic regression. Table S5. Log-likelihood ratio test results for comparison between M2a and M1a models. Table S6. Fisher’s exact test results for prevalence difference in prophage sequence between single and recurrent infections.
DOI: 10.6084/m9.figshare.13663065
title: Additional file 10 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 10: Table S9. Protein sequences blast from 17 plant genomes LRR-RLKs using Arabidopsis protein sequences as a query
DOI: 10.6084/m9.figshare.13663065.v1
title: Additional file 10 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 10: Table S9. Protein sequences blast from 17 plant genomes LRR-RLKs using Arabidopsis protein sequences as a query
DOI: 10.6084/m9.figshare.13663074
title: Additional file 3 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 3: Table S2. LRR motifs manually added to the Phyto-LRR database
DOI: 10.6084/m9.figshare.13663074.v1
title: Additional file 3 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 3: Table S2. LRR motifs manually added to the Phyto-LRR database
DOI: 10.6084/m9.figshare.13663077
title: Additional file 4 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 4: Table S3. LRR-RLK members in each SG, refined neighbor-joining (NJ) tree of SG_x, and ten test sets of the phylogenetic tree
DOI: 10.6084/m9.figshare.13663077.v1
title: Additional file 4 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 4: Table S3. LRR-RLK members in each SG, refined neighbor-joining (NJ) tree of SG_x, and ten test sets of the phylogenetic tree
DOI: 10.6084/m9.figshare.13663080
title: Additional file 5 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 5: Table S4. N-glycosylation sites annotated in the Arabidopsis proteome GFF file from Swiss-Prot
DOI: 10.6084/m9.figshare.13663080.v1
title: Additional file 5 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 5: Table S4. N-glycosylation sites annotated in the Arabidopsis proteome GFF file from Swiss-Prot
DOI: 10.6084/m9.figshare.13663083
title: Additional file 6 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 6: Table S5. Information on the protein sequence datasets
DOI: 10.6084/m9.figshare.13663083.v1
title: Additional file 6 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 6: Table S5. Information on the protein sequence datasets
DOI: 10.6084/m9.figshare.13663086
title: Additional file 7 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 7: Table S6. Training dataset 1 for Phyto-LRR predict program
DOI: 10.6084/m9.figshare.13663086.v1
title: Additional file 7 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 7: Table S6. Training dataset 1 for Phyto-LRR predict program
DOI: 10.6084/m9.figshare.13663089
title: Additional file 8 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 8: Table S7. Training dataset 2 for Phyto-LRR predict program
DOI: 10.6084/m9.figshare.13663089.v1
title: Additional file 8 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 8: Table S7. Training dataset 2 for Phyto-LRR predict program
DOI: 10.6084/m9.figshare.13663092
title: Additional file 9 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 9: Table S8. The distribution pattern of LRR motifs and potential N-glycosylation sites of each LRR-RLK member in different SGs
DOI: 10.6084/m9.figshare.13663092.v1
title: Additional file 9 of Identification and characterization of the LRR repeats in plant LRR-RLKs

description: Additional file 9: Table S8. The distribution pattern of LRR motifs and potential N-glycosylation sites of each LRR-RLK member in different SGs
DOI: 10.6084/m9.figshare.13663191
title: Additional file 1 of Genome-wide characterization of the WAK gene family and expression analysis under plant hormone treatment in cotton

description: Additional file 1: Figure S1. Synteny comparison of WAK regions from the homeologous in three cotton genomes. Black and orange ovals indicate WAK genes from dispersed and proximal duplication, respectively. The red lines indicate WAK gene from WGD. Green dots indicate WAK gene from tandem duplication. The blue lines indicate orthologous gene pairs. Figure S2. Heatmap of RNA-seq data of GhWAK gene expression levels in five different tissues of G. hirsutum (Xuzhou 142). The transcriptome data were normalized and visualized by the pheatmap package in R language. The colorful bars from green to red indicate the expression levels from low to high, respectively. Figure S3. Expression profile of six GhWAK genes during fiber cell development stages.
DOI: 10.6084/m9.figshare.13663194.v1
title: Additional file 2 of Genome-wide characterization of the WAK gene family and expression analysis under plant hormone treatment in cotton

description: Additional file 2: Table S1. Physicochemical parameters of 14 GrWAK and 19 GaWAK genes in G. raimondii and G. arboreum genomes. Table S2. Analysis of duplication events of GhWAK, GaWAK and GrWAK in G. hirsutum, G. arboreum and G. raimondii, respectively. Table S3. Orthologous and paralogous relationships among WAK genes in G. hirsutum, G. arboreum and G. raimondii. Table S4. Ka/Ks analysis and divergence times of duplicated GhWAK gene pairs of G. hirsutum, G.raimondii and G. arboreum. Table S5. cis-elements related to plant growth regulators in the promoters of GhWAK genes. Table S6. Physicochemical parameters of five AtWAK genes in the A. thaliana genome. Table S7. GhWAK gene primer pairs used for qRT-PCR and GUS staining.
DOI: 10.6084/m9.figshare.13663191.v1
title: Additional file 1 of Genome-wide characterization of the WAK gene family and expression analysis under plant hormone treatment in cotton

description: Additional file 1: Figure S1. Synteny comparison of WAK regions from the homeologous in three cotton genomes. Black and orange ovals indicate WAK genes from dispersed and proximal duplication, respectively. The red lines indicate WAK gene from WGD. Green dots indicate WAK gene from tandem duplication. The blue lines indicate orthologous gene pairs. Figure S2. Heatmap of RNA-seq data of GhWAK gene expression levels in five different tissues of G. hirsutum (Xuzhou 142). The transcriptome data were normalized and visualized by the pheatmap package in R language. The colorful bars from green to red indicate the expression levels from low to high, respectively. Figure S3. Expression profile of six GhWAK genes during fiber cell development stages.
DOI: 10.6084/m9.figshare.13663194
title: Additional file 2 of Genome-wide characterization of the WAK gene family and expression analysis under plant hormone treatment in cotton

description: Additional file 2: Table S1. Physicochemical parameters of 14 GrWAK and 19 GaWAK genes in G. raimondii and G. arboreum genomes. Table S2. Analysis of duplication events of GhWAK, GaWAK and GrWAK in G. hirsutum, G. arboreum and G. raimondii, respectively. Table S3. Orthologous and paralogous relationships among WAK genes in G. hirsutum, G. arboreum and G. raimondii. Table S4. Ka/Ks analysis and divergence times of duplicated GhWAK gene pairs of G. hirsutum, G.raimondii and G. arboreum. Table S5. cis-elements related to plant growth regulators in the promoters of GhWAK genes. Table S6. Physicochemical parameters of five AtWAK genes in the A. thaliana genome. Table S7. GhWAK gene primer pairs used for qRT-PCR and GUS staining.
DOI: 10.6084/m9.figshare.13663203
title: Additional file 1 of Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model

description: Additional file 1. The results of the correlation between some genes and signature activity in 14 cancer types with high Spearman correlation coefficients.
DOI: 10.6084/m9.figshare.13663209
title: Additional file 2 of Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model

description: Additional file 2. The similarity matrices based on tissue type information corresponding to GDSC dataset.
DOI: 10.6084/m9.figshare.13663212
title: Additional file 3 of Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model

description: Additional file 3. The similarity matrices based on tissue type information corresponding to CCLE dataset.
DOI: 10.6084/m9.figshare.13663203.v1
title: Additional file 1 of Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model

description: Additional file 1. The results of the correlation between some genes and signature activity in 14 cancer types with high Spearman correlation coefficients.
DOI: 10.6084/m9.figshare.13663209.v1
title: Additional file 2 of Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model

description: Additional file 2. The similarity matrices based on tissue type information corresponding to GDSC dataset.
DOI: 10.6084/m9.figshare.13663260.v1
title: Additional file 1 of Analysis of Rice Transcriptome Reveals the LncRNA/CircRNA Regulation in Tissue Development

description: Additional file 1.
DOI: 10.6084/m9.figshare.13663260
title: Additional file 1 of Analysis of Rice Transcriptome Reveals the LncRNA/CircRNA Regulation in Tissue Development

description: Additional file 1.
DOI: 10.6084/m9.figshare.13663278.v1
title: Additional file 1 of Application of the BACs-on-Beads assay for the prenatal diagnosis of chromosomal abnormalities in Quanzhou, China

description: Additional file 1.
DOI: 10.6084/m9.figshare.13663278
title: Additional file 1 of Application of the BACs-on-Beads assay for the prenatal diagnosis of chromosomal abnormalities in Quanzhou, China

description: Additional file 1.
DOI: 10.6084/m9.figshare.13663281.v1
title: Additional file 1 of MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples

description: Additional file 1: Table S1. List of UCSC XENA TCGA samples used for the development of the MethCORR matrix and regression models.
DOI: 10.6084/m9.figshare.13663281
title: Additional file 1 of MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples

description: Additional file 1: Table S1. List of UCSC XENA TCGA samples used for the development of the MethCORR matrix and regression models.
DOI: 10.6084/m9.figshare.13663284
title: Additional file 2 of MethCORR infers gene expression from DNA methylation and allows molecular analysis of ten common cancer types using fresh-frozen and formalin-fixed paraffin-embedded tumor samples

description: Additional file 2: Table S2. Gene-specific model fit for UCSC XENA TCGA BRCA. Table S3. Gene-specific model fit for UCSC XENA TCGA PRAD. Table S4. Gene-specific model fit for UCSC XENA TCGA LUAD. Table S5. Gene-specific model fit for UCSC XENA TCGA LUSC. Table S6. Gene-specific model fit for UCSC XENA TCGA STAD. Table S7. Gene-specific model fit for UCSC XENA TCGA BLCA. Table S8. Gene-specific model fit for UCSC XENA TCGA SKCM. Table S9. Gene-specific model fit for UCSC XENA TCGA KIRC. Table S10. Gene-specific model fit for UCSC XENA TCGA UCEC. Table S11. Gene-specific model fit for UCSC XENA TCGA ESCA.