cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11665563.v1
title: R script for connecting LIM-MCMC results to the enaR library from Shifting levels of ecological network's analysis reveals different system properties

description: Network analyses applied to models of complex systems generally contain at least three levels of analyses. Whole-network metrics summarize general organizational features (properties or relationships) of the entire network, while node-level metrics summarize similar organization features but considering individual nodes at the time. The network- and node-level metrics build upon the primary pairwise relationships in the model. As with many analyses, sometimes there are interesting differences at one level that disappear in the summary at another level of analysis. We illustrate this phenomenon with ecosystem network models, where nodes are trophic compartments and pairwise relationships are flows of organic carbon, such as when a predator eats a prey. For this demonstration, we analysed a time-series of 16 models of a lake planktonic food web that describes carbon exchanges within an autumn cyanobacteria bloom and compared the ecological conclusions drawn from the three levels of analysis based on inter-time-step comparisons. A general pattern in our analyses was that the closer the levels are in hierarchy (node versus network, or flow versus node level), the more they tend to align in their conclusions. Our analyses suggest that selecting the appropriate level of analysis, and above all regularly using multiple levels, may be a critical analytical decision.This article is part of the special issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.
DOI: 10.6084/m9.figshare.11665560.v1
title: Table A1. Table of values of the flows in the new balanced LIM from Shifting levels of ecological network's analysis reveals different system properties

description: Network analyses applied to models of complex systems generally contain at least three levels of analyses. Whole-network metrics summarize general organizational features (properties or relationships) of the entire network, while node-level metrics summarize similar organization features but considering individual nodes at the time. The network- and node-level metrics build upon the primary pairwise relationships in the model. As with many analyses, sometimes there are interesting differences at one level that disappear in the summary at another level of analysis. We illustrate this phenomenon with ecosystem network models, where nodes are trophic compartments and pairwise relationships are flows of organic carbon, such as when a predator eats a prey. For this demonstration, we analysed a time-series of 16 models of a lake planktonic food web that describes carbon exchanges within an autumn cyanobacteria bloom and compared the ecological conclusions drawn from the three levels of analysis based on inter-time-step comparisons. A general pattern in our analyses was that the closer the levels are in hierarchy (node versus network, or flow versus node level), the more they tend to align in their conclusions. Our analyses suggest that selecting the appropriate level of analysis, and above all regularly using multiple levels, may be a critical analytical decision.This article is part of the special issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.
DOI: 10.6084/m9.figshare.11665536
title: Immune function in wheatears from Migrating birds rapidly increase constitutive immune function during stopover

description: Original data as used in the analyses
DOI: 10.6084/m9.figshare.11665536.v1
title: Immune function in wheatears from Migrating birds rapidly increase constitutive immune function during stopover

description: Original data as used in the analyses
DOI: 10.6084/m9.figshare.11665515
title: MOESM6 of Pcdhβ deficiency affects hippocampal CA1 ensemble activity and contextual fear discrimination

description: Additional file 6 Table S1. Tables of statistical values. P-values by statistical analysis of all figures and additional files.
DOI: 10.6084/m9.figshare.11665515.v1
title: MOESM6 of Pcdhβ deficiency affects hippocampal CA1 ensemble activity and contextual fear discrimination

description: Additional file 6 Table S1. Tables of statistical values. P-values by statistical analysis of all figures and additional files.
DOI: 10.6084/m9.figshare.11665461
title: MOESM7 of Differential expression of IDA (INFLORESCENCE DEFICIENT IN ABSCISSION)-like genes in Nicotiana benthamiana during corolla abscission, stem growth and water stress

description: Additional file 7: Solanaceae IDA-like and HAE-like gene families.xlsx. The DNA and protein sequences, as well as the localization of the sequences in the genomes in SolGenomics and the sequence IDs are contained in this file.
DOI: 10.6084/m9.figshare.11665461.v1
title: MOESM7 of Differential expression of IDA (INFLORESCENCE DEFICIENT IN ABSCISSION)-like genes in Nicotiana benthamiana during corolla abscission, stem growth and water stress

description: Additional file 7: Solanaceae IDA-like and HAE-like gene families.xlsx. The DNA and protein sequences, as well as the localization of the sequences in the genomes in SolGenomics and the sequence IDs are contained in this file.
DOI: 10.6084/m9.figshare.11665455
title: MOESM5 of 3’Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

description: Additional file 5. Supplemental Material Primer Sequences. A list of all oligo-nucleotides employed in this study, using sequence conventions as outlined by IDT, Inc.
DOI: 10.6084/m9.figshare.11665455.v1
title: MOESM5 of 3’Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

description: Additional file 5. Supplemental Material Primer Sequences. A list of all oligo-nucleotides employed in this study, using sequence conventions as outlined by IDT, Inc.
DOI: 10.6084/m9.figshare.11665446
title: MOESM4 of 3’Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

description: Additional file 4: Table S3. A Gene Ontology analysis of the pathways ranked by p-value represented by the DEGs detected by TruSeq in the Wild-Type vs. GFAP-IL6 mouse model.
DOI: 10.6084/m9.figshare.11665446.v1
title: MOESM4 of 3’Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

description: Additional file 4: Table S3. A Gene Ontology analysis of the pathways ranked by p-value represented by the DEGs detected by TruSeq in the Wild-Type vs. GFAP-IL6 mouse model.
DOI: 10.6084/m9.figshare.11665443
title: MOESM5 of Differential expression of IDA (INFLORESCENCE DEFICIENT IN ABSCISSION)-like genes in Nicotiana benthamiana during corolla abscission, stem growth and water stress

description: Additional file 5: Gene expression raw and final processed data.xlsx.
DOI: 10.6084/m9.figshare.11665437
title: MOESM3 of 3’Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

description: Additional file 3: Table S2. A Gene Ontology analysis of the pathways ranked by p-value represented by the DEGs detected by 3’Pool-seq in the Wild-Type vs. GFAP-IL6 mouse model.
DOI: 10.6084/m9.figshare.11665443.v1
title: MOESM5 of Differential expression of IDA (INFLORESCENCE DEFICIENT IN ABSCISSION)-like genes in Nicotiana benthamiana during corolla abscission, stem growth and water stress

description: Additional file 5: Gene expression raw and final processed data.xlsx.
DOI: 10.6084/m9.figshare.11665437.v1
title: MOESM3 of 3’Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

description: Additional file 3: Table S2. A Gene Ontology analysis of the pathways ranked by p-value represented by the DEGs detected by 3’Pool-seq in the Wild-Type vs. GFAP-IL6 mouse model.
DOI: 10.6084/m9.figshare.11665428
title: MOESM2 of 3’Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

description: Additional file 2: Table S1. A per-sample overview of sequencing metric details that were used to construct Table 1 of the main manuscript.
DOI: 10.6084/m9.figshare.11665428.v1
title: MOESM2 of 3’Pool-seq: an optimized cost-efficient and scalable method of whole-transcriptome gene expression profiling

description: Additional file 2: Table S1. A per-sample overview of sequencing metric details that were used to construct Table 1 of the main manuscript.
DOI: 10.6084/m9.figshare.11665353
title: MOESM3 of IL-1-conferred gene expression pattern in ERα+ BCa and AR+ PCa cells is intrinsic to ERα− BCa and AR− PCa cells and promotes cell survival

description: Additional file 3: Table S1. Gene expression and ontology data. The “Table Legend” tab is a description of each worksheet tab. Each worksheet tab contains the gene expression data, IPA analysis, or GOrilla analysis described in the paper.
DOI: 10.6084/m9.figshare.11665353.v1
title: MOESM3 of IL-1-conferred gene expression pattern in ERα+ BCa and AR+ PCa cells is intrinsic to ERα− BCa and AR− PCa cells and promotes cell survival

description: Additional file 3: Table S1. Gene expression and ontology data. The “Table Legend” tab is a description of each worksheet tab. Each worksheet tab contains the gene expression data, IPA analysis, or GOrilla analysis described in the paper.
DOI: 10.6084/m9.figshare.11665245
title: MOESM1 of Pathological complete response due to a prolonged time interval between preoperative chemoradiation and surgery in locally advanced rectal cancer: analysis from the German StuDoQ|Rectalcarcinoma registry

description: Additional file 1: Table S1. All participating hospitals and surgical directors who contributed patient data to the StuDoQ|ColonCancer registry.
DOI: 10.6084/m9.figshare.11665245.v1
title: MOESM1 of Pathological complete response due to a prolonged time interval between preoperative chemoradiation and surgery in locally advanced rectal cancer: analysis from the German StuDoQ|Rectalcarcinoma registry

description: Additional file 1: Table S1. All participating hospitals and surgical directors who contributed patient data to the StuDoQ|ColonCancer registry.
DOI: 10.6084/m9.figshare.11665227
title: MOESM4 of Effect of rodent density on tick and tick-borne pathogen populations: consequences for infectious disease risk

description: Additional file 4: Table S1. Daily temperature data from September 2012 to December 2015 collected from the nearest weather station (Deelen, KNMI, the Netherlands). Text S1. Primers and probes for detection of B. microti and S. ixodetis, and qPCR protocol. Table S2. Density of nymphs and number of analyzed nymphs for microorganisms per treatment, month and year. Table S3. Density of rodents and number of analyzed individuals for microorganisms per rodent species, treatment, month and year. Table S4. Prevalences of tick-borne microorganisms in rodents and nymphs. Table S5. All tested models for prediction of density of nymphs (DON), nymphal infection prevalence (NIP), and density of infected nymphs (DIN). Table S6. Full equations for the best fitting models for prediction of density of nymphs (DON), nymphal infection prevalence (NIP), and density of infected nymphs (DIN).
DOI: 10.6084/m9.figshare.11665227.v1
title: MOESM4 of Effect of rodent density on tick and tick-borne pathogen populations: consequences for infectious disease risk

description: Additional file 4: Table S1. Daily temperature data from September 2012 to December 2015 collected from the nearest weather station (Deelen, KNMI, the Netherlands). Text S1. Primers and probes for detection of B. microti and S. ixodetis, and qPCR protocol. Table S2. Density of nymphs and number of analyzed nymphs for microorganisms per treatment, month and year. Table S3. Density of rodents and number of analyzed individuals for microorganisms per rodent species, treatment, month and year. Table S4. Prevalences of tick-borne microorganisms in rodents and nymphs. Table S5. All tested models for prediction of density of nymphs (DON), nymphal infection prevalence (NIP), and density of infected nymphs (DIN). Table S6. Full equations for the best fitting models for prediction of density of nymphs (DON), nymphal infection prevalence (NIP), and density of infected nymphs (DIN).
DOI: 10.6084/m9.figshare.11665209
title: MOESM2 of Core transcriptional regulatory circuits in prion diseases

description: Additional file 2: Table S1. Previously reported differential expression of 883 genes during the progression of prion diseases. Table S2. GO Biological Processes enriched by EU, LU, and DN genes. Table S3. 114 major TFs and previously reported associations with prion or other neurodegenerative diseases. Table S4. Representative cellular processes associated with prion diseases. Table S5. Motif7 - 6329 subnetworks and Motif10 - 533 subnetworks. Table S6. GOBPs regulated by TF pairs that could be operative in microglia and OPC.
DOI: 10.6084/m9.figshare.11665209.v1
title: MOESM2 of Core transcriptional regulatory circuits in prion diseases

description: Additional file 2: Table S1. Previously reported differential expression of 883 genes during the progression of prion diseases. Table S2. GO Biological Processes enriched by EU, LU, and DN genes. Table S3. 114 major TFs and previously reported associations with prion or other neurodegenerative diseases. Table S4. Representative cellular processes associated with prion diseases. Table S5. Motif7 - 6329 subnetworks and Motif10 - 533 subnetworks. Table S6. GOBPs regulated by TF pairs that could be operative in microglia and OPC.
DOI: 10.6084/m9.figshare.11665194
title: MOESM1 of Residual feed intake divergence during the preweaning period is associated with unique hindgut microbiome and metabolome profiles in neonatal Holstein heifer calves

description: Additional file 1: Figure S1. Phyla level taxonomic distribution in hindgut samples at birth in most-efficient (M-eff) and least-efficient (L-eff) heifer calves. Figure S2. Non-metric multidimensional scaling (NMDS) plot of fecal microbiome profiles during the preweaning period in least-efficient (L-eff, n = 13) or most-efficient (M-eff, n = 13) heifer calves at (A) day 14, (B) day 28, and (C) day 42 of age. Figure S3. Phyla level taxonomic distribution in hindgut samples during the preweaning period at day 14, 28 and 42 of age in most-efficient (M-eff) and least-efficient (L-eff) heifer calves. Figure S4. Upregulated hindgut metabolites in M-eff heifer calves at birth strongly influencing metabolome discrimination between most-efficient (M-eff, n = 13) and least-efficient (L-eff, n = 13) heifer calves assessed by partial least square discriminant analysis (PLS-DA)l. Figure S5. Downregulated hindgut metabolites in M-eff heifer calves at birth strongly influencing metabolome discrimination between most-efficient (M-eff, n = 13) and least-efficient (L-eff, n = 13) heifer calves assessed by partial least square discriminant analysis (PLS-DA). Figure S6. Scores plot of partial least square discriminant analysis (PLS-DA) for hindgut metabolome profiles during the preweaning period in least-efficient (L-eff, n = 13) or most-efficient (M-eff, n = 13) heifer calves at (A) day 14, (B) day 28, and (C) day 42 of age. Figure S7. Upregulated hindgut metabolites in M-eff heifer calves during the preweaning period strongly influencing metabolome discrimination between most-efficient (M-eff, n = 13) and least-efficient (L-eff, n = 13) heifer calves assessed by partial least square discriminant analysis (PLS-DA). Figure S8. Downregulated hindgut metabolites in M-eff heifer calves during the preweaning period strongly influencing metabolome discrimination between most-efficient (M-eff, n = 13) and least-efficient (L-eff, n = 13) heifer calves assessed by partial least square discriminant analysis (PLS-DA)
DOI: 10.6084/m9.figshare.11665194.v1
title: MOESM1 of Residual feed intake divergence during the preweaning period is associated with unique hindgut microbiome and metabolome profiles in neonatal Holstein heifer calves

description: Additional file 1: Figure S1. Phyla level taxonomic distribution in hindgut samples at birth in most-efficient (M-eff) and least-efficient (L-eff) heifer calves. Figure S2. Non-metric multidimensional scaling (NMDS) plot of fecal microbiome profiles during the preweaning period in least-efficient (L-eff, n = 13) or most-efficient (M-eff, n = 13) heifer calves at (A) day 14, (B) day 28, and (C) day 42 of age. Figure S3. Phyla level taxonomic distribution in hindgut samples during the preweaning period at day 14, 28 and 42 of age in most-efficient (M-eff) and least-efficient (L-eff) heifer calves. Figure S4. Upregulated hindgut metabolites in M-eff heifer calves at birth strongly influencing metabolome discrimination between most-efficient (M-eff, n = 13) and least-efficient (L-eff, n = 13) heifer calves assessed by partial least square discriminant analysis (PLS-DA)l. Figure S5. Downregulated hindgut metabolites in M-eff heifer calves at birth strongly influencing metabolome discrimination between most-efficient (M-eff, n = 13) and least-efficient (L-eff, n = 13) heifer calves assessed by partial least square discriminant analysis (PLS-DA). Figure S6. Scores plot of partial least square discriminant analysis (PLS-DA) for hindgut metabolome profiles during the preweaning period in least-efficient (L-eff, n = 13) or most-efficient (M-eff, n = 13) heifer calves at (A) day 14, (B) day 28, and (C) day 42 of age. Figure S7. Upregulated hindgut metabolites in M-eff heifer calves during the preweaning period strongly influencing metabolome discrimination between most-efficient (M-eff, n = 13) and least-efficient (L-eff, n = 13) heifer calves assessed by partial least square discriminant analysis (PLS-DA). Figure S8. Downregulated hindgut metabolites in M-eff heifer calves during the preweaning period strongly influencing metabolome discrimination between most-efficient (M-eff, n = 13) and least-efficient (L-eff, n = 13) heifer calves assessed by partial least square discriminant analysis (PLS-DA)
DOI: 10.6084/m9.figshare.11665173
title: MOESM2 of Low levels of HIV-1 drug resistance mutations in patients who achieved viral re-suppression without regimen switch: a retrospective study

description: Additional file 2. Study Database. Unlinked database without personal identifiable data.
DOI: 10.6084/m9.figshare.11665173.v1
title: MOESM2 of Low levels of HIV-1 drug resistance mutations in patients who achieved viral re-suppression without regimen switch: a retrospective study

description: Additional file 2. Study Database. Unlinked database without personal identifiable data.
DOI: 10.6084/m9.figshare.11665131
title: MOESM1 of Profiling of the muscle-specific dystroglycan interactome reveals the role of Hippo signaling in muscular dystrophy and age-dependent muscle atrophy

description: Additional file 1: Data S1. Original mass spectrometry data of Dg interactors in muscles.
DOI: 10.6084/m9.figshare.11665131.v1
title: MOESM1 of Profiling of the muscle-specific dystroglycan interactome reveals the role of Hippo signaling in muscular dystrophy and age-dependent muscle atrophy

description: Additional file 1: Data S1. Original mass spectrometry data of Dg interactors in muscles.
DOI: 10.6084/m9.figshare.11665083
title: MOESM6 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 6 Blast2GO annotation of the 28,027 genes identified in the genome of C. gigas.
DOI: 10.6084/m9.figshare.11665083.v1
title: MOESM6 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 6 Blast2GO annotation of the 28,027 genes identified in the genome of C. gigas.
DOI: 10.6084/m9.figshare.11665074
title: MOESM5 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 5. List of DEGs specifics to the RF48 oyster family. This table presents the Log2 fold change of each CGI differentially expressed (significant) only in the the RF48 oyster family compared to the three susceptible families (SF11, SF14 and SF15), the Blast results, the enriched functional categories and details of each comparison (Log2 fold change, p-value, GO categories and number of reads).
DOI: 10.6084/m9.figshare.11665074.v1
title: MOESM5 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 5. List of DEGs specifics to the RF48 oyster family. This table presents the Log2 fold change of each CGI differentially expressed (significant) only in the the RF48 oyster family compared to the three susceptible families (SF11, SF14 and SF15), the Blast results, the enriched functional categories and details of each comparison (Log2 fold change, p-value, GO categories and number of reads).
DOI: 10.6084/m9.figshare.11665062
title: MOESM4 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 4. List of DEGs specifics to the RF23 oyster family. This table presents the Log2 fold change of each CGI differentially expressed (significant) only in the the RF23 oyster family compared to the three susceptible families (SF11, SF14 and SF15), the Blast results, the enriched functional categories and details of each comparison (Log2 fold change, p-value, GO categories and number of reads).
DOI: 10.6084/m9.figshare.11665062.v1
title: MOESM4 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 4. List of DEGs specifics to the RF23 oyster family. This table presents the Log2 fold change of each CGI differentially expressed (significant) only in the the RF23 oyster family compared to the three susceptible families (SF11, SF14 and SF15), the Blast results, the enriched functional categories and details of each comparison (Log2 fold change, p-value, GO categories and number of reads).
DOI: 10.6084/m9.figshare.11665050
title: MOESM3 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 3. List of DEGs specifics to the RF21 oyster family. This table presents the Log2 fold change of each CGI differentially expressed (significant) only in the the RF21 oyster family compared to the three susceptible families (SF11, SF14 and SF15), the Blast results, the enriched functional categories and details of each comparison (Log2 fold change, p-value, GO categories and number of reads).
DOI: 10.6084/m9.figshare.11665050.v1
title: MOESM3 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 3. List of DEGs specifics to the RF21 oyster family. This table presents the Log2 fold change of each CGI differentially expressed (significant) only in the the RF21 oyster family compared to the three susceptible families (SF11, SF14 and SF15), the Blast results, the enriched functional categories and details of each comparison (Log2 fold change, p-value, GO categories and number of reads).
DOI: 10.6084/m9.figshare.11665038
title: MOESM2 of Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

description: Additional file 2. List of DEGs shared by at least two resistant families. This table presents the Log2 fold change of each CGI differentially expressed (significant) in the three resistant oyster families (RF21, RF23 and RF48) compared to the three susceptible families (SF11, SF14 and SF15), the Blast results, the enriched functional categories and details of each comparison (Log2 fold change, p-value and number of reads).