cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13719160.v1
title: Additional file 17 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 17. Lists of overrepresented transcription factor binding sites (TFBSs) in genes downregulated in GE1-hepatocellular carcinoma (HCC). Significantly down regulated genes in GE1-HCC (n=10) versus NT (n=17) samples with mean fold change (FC) ≤ -2 and P ≤ 0.01 (Additional file 4) were used as an input gene list for bioinformatics analyses. Promoter sequences of the co-regulated in tumours genes (“Yes” set) and the control gene set (“No” set) were searched for potential transcription factor binding sites (TFBSs) using the MATCHTM tool and TRANSFAC® library of positional weight matrices. The frequencies of TFBSs in the “Yes” gene set and “No” gene set were identified, and the ratio of “Yes” versus “No” was calculated. Yes/No ratio &gt; 1 indicates overrepresentation of TFBSs in the co-regulated genes and suggests potential involvement of the corresponding transcription factor in regulation of the observed expression changes.
DOI: 10.6084/m9.figshare.13719145.v1
title: Additional file 12 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 12. Master regulator molecules of genes upregulated in GE2-hepatocellular carcinoma (HCC). Significantly up regulated genes in GE2-HCC (n=13) versus NT (n=17) samples with mean fold change (FC) ≥ 2 and false discovery rate (FDR) ≤ 0.05 were identified (Additional file 5) and used as an input gene list for bioinformatics analyses. Master regulator molecules in the signal transduction pathways, at a distance of up to 10 steps upstream of the dysregulated genes, were identified using the curated database of pathways and protein interactions TRANSPATH®.
DOI: 10.6084/m9.figshare.13719163
title: Additional file 18 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 18. Lists of overrepresented transcription factor binding sites (TFBSs) in genes downregulated in GE2-hepatocellular carcinoma (HCC). Significantly down regulated genes in GE2-HCC (n=13) versus NT (n=17) samples with mean fold change (FC) ≤ -2 and false discovery rate (FDR) ≤ 0.05 (Additional file 5) were used as an input gene list for bioinformatics analyses. Promoter sequences of the co-regulated in tumours genes (“Yes” set) and the control gene set (“No” set) were searched for potential transcription factor binding sites (TFBSs) using the MATCHTM tool and TRANSFAC® library of positional weight matrices. The frequencies of TFBSs in the “Yes” gene set and “No” gene set were identified, and the ratio of “Yes” versus “No” was calculated. Yes/No ratio &gt; 1 indicates overrepresentation of TFBSs in the co-regulated genes and suggests potential involvement of the corresponding transcription factor in regulation of the observed expression changes.
DOI: 10.6084/m9.figshare.13719163.v1
title: Additional file 18 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 18. Lists of overrepresented transcription factor binding sites (TFBSs) in genes downregulated in GE2-hepatocellular carcinoma (HCC). Significantly down regulated genes in GE2-HCC (n=13) versus NT (n=17) samples with mean fold change (FC) ≤ -2 and false discovery rate (FDR) ≤ 0.05 (Additional file 5) were used as an input gene list for bioinformatics analyses. Promoter sequences of the co-regulated in tumours genes (“Yes” set) and the control gene set (“No” set) were searched for potential transcription factor binding sites (TFBSs) using the MATCHTM tool and TRANSFAC® library of positional weight matrices. The frequencies of TFBSs in the “Yes” gene set and “No” gene set were identified, and the ratio of “Yes” versus “No” was calculated. Yes/No ratio &gt; 1 indicates overrepresentation of TFBSs in the co-regulated genes and suggests potential involvement of the corresponding transcription factor in regulation of the observed expression changes.
DOI: 10.6084/m9.figshare.13719166
title: Additional file 1 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 1. Clinicopathological data of the patients with liver carcinoma used in the study.
DOI: 10.6084/m9.figshare.13719166.v1
title: Additional file 1 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 1. Clinicopathological data of the patients with liver carcinoma used in the study.
DOI: 10.6084/m9.figshare.13719169
title: Additional file 2 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 2. Differentially expressed probe sets in hepatocellular carcinoma (HCC) versus non-tumourous (NT) tissues. Unpaired Welch’s t-test was performed using gene expression microarray data from 23 HCC and 17 NT samples. The probe sets differentially expressed in the HCC group (n = 23) versus the NT group (n = 17) showing a mean absolute fold change (FC) ≥ 2, with a false discovery rate (FDR) ≤ 0.05, were selected and used for hierarchical cluster analysis and principal component analysis.
DOI: 10.6084/m9.figshare.13719169.v1
title: Additional file 2 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 2. Differentially expressed probe sets in hepatocellular carcinoma (HCC) versus non-tumourous (NT) tissues. Unpaired Welch’s t-test was performed using gene expression microarray data from 23 HCC and 17 NT samples. The probe sets differentially expressed in the HCC group (n = 23) versus the NT group (n = 17) showing a mean absolute fold change (FC) ≥ 2, with a false discovery rate (FDR) ≤ 0.05, were selected and used for hierarchical cluster analysis and principal component analysis.
DOI: 10.6084/m9.figshare.13719175
title: Additional file 4 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 4. List of differentially expressed probe sets in GE1-hepatocellular carcinoma (HCC) versus non-tumourous (NT) tissues. Unpaired Welch’s t-test was performed using gene expression microarray data from GE1-HCC (n=10) and NT (n=17) samples. The probe sets demonstrating expression changes in the GE1-HCC group versus the NT group with a mean absolute fold change (FC) ≥ 2 and P ≤ 0.01 were selected and used for further bioinformatic analyses.
DOI: 10.6084/m9.figshare.13719178
title: Additional file 5 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 5. List of differentially expressed probe sets in 13 GE2-hepatocellular carcinoma (HCC) versus 17 non-tumourous (NT) tissues. Unpaired Welch’s t-test was performed using gene expression microarray data from GE2-HCC (n=13) and NT (n=17) samples. The probe sets demonstrating expression change in the GE2-HCC group versus the NT group with a mean absolute fold change (FC) ≥ 2 and false discovery rate (FDR) ≤ 0.05 were selected and used for further bioinformatics analyses.
DOI: 10.6084/m9.figshare.13719175.v1
title: Additional file 4 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 4. List of differentially expressed probe sets in GE1-hepatocellular carcinoma (HCC) versus non-tumourous (NT) tissues. Unpaired Welch’s t-test was performed using gene expression microarray data from GE1-HCC (n=10) and NT (n=17) samples. The probe sets demonstrating expression changes in the GE1-HCC group versus the NT group with a mean absolute fold change (FC) ≥ 2 and P ≤ 0.01 were selected and used for further bioinformatic analyses.
DOI: 10.6084/m9.figshare.13719181
title: Additional file 6 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 6. List of differentially expressed probe sets in 13 GE2-hepatocellular carcinoma (HCC) versus 10 GE1-HCC samples. Unpaired Welch’s t-test was performed using gene expression microarray data from GE2-HCC (n=13) and GE1-HCC (n=10) samples. The probe sets that expression change in the GE2-HCC group versus the GE1-HCC group showed mean absolute fold change (FC) ≥ 2 and false discovery rate (FDR) ≤ 0.05 were selected.
DOI: 10.6084/m9.figshare.13719181.v1
title: Additional file 6 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 6. List of differentially expressed probe sets in 13 GE2-hepatocellular carcinoma (HCC) versus 10 GE1-HCC samples. Unpaired Welch’s t-test was performed using gene expression microarray data from GE2-HCC (n=13) and GE1-HCC (n=10) samples. The probe sets that expression change in the GE2-HCC group versus the GE1-HCC group showed mean absolute fold change (FC) ≥ 2 and false discovery rate (FDR) ≤ 0.05 were selected.
DOI: 10.6084/m9.figshare.13719178.v1
title: Additional file 5 of Gene networks and transcriptional regulators associated with liver cancer development and progression

description: Additional file 5. List of differentially expressed probe sets in 13 GE2-hepatocellular carcinoma (HCC) versus 17 non-tumourous (NT) tissues. Unpaired Welch’s t-test was performed using gene expression microarray data from GE2-HCC (n=13) and NT (n=17) samples. The probe sets demonstrating expression change in the GE2-HCC group versus the NT group with a mean absolute fold change (FC) ≥ 2 and false discovery rate (FDR) ≤ 0.05 were selected and used for further bioinformatics analyses.
DOI: 10.6084/m9.figshare.14091240.v1
title: Additional file 10 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 10. Mapping DMRs to 4 Mb upstream and downstream of the list of imprinted, predicted, conflicting, and provisional imprinted genes.
DOI: 10.6084/m9.figshare.14091243.v1
title: Additional file 11 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 11. Mapping of DMRs to the reported MAE genes by Savova et al.
DOI: 10.6084/m9.figshare.14091240
title: Additional file 10 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 10. Mapping DMRs to 4 Mb upstream and downstream of the list of imprinted, predicted, conflicting, and provisional imprinted genes.
DOI: 10.6084/m9.figshare.14091258
title: Additional file 3 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 3. Contains table of true- and false-positives using different quality thresholds for Clair and Clair+SNVoter.
DOI: 10.6084/m9.figshare.14091243
title: Additional file 11 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 11. Mapping of DMRs to the reported MAE genes by Savova et al.
DOI: 10.6084/m9.figshare.14091258.v1
title: Additional file 3 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 3. Contains table of true- and false-positives using different quality thresholds for Clair and Clair+SNVoter.
DOI: 10.6084/m9.figshare.14091261
title: Additional file 4 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 4. Contains average of methylation at known and novel ICRs from Court et al. and Joshi et al.
DOI: 10.6084/m9.figshare.14091261.v1
title: Additional file 4 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 4. Contains average of methylation at known and novel ICRs from Court et al. and Joshi et al.
DOI: 10.6084/m9.figshare.14091264
title: Additional file 5 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 5. Contains DMRs found in each sample.
DOI: 10.6084/m9.figshare.14091267.v1
title: Additional file 6 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 6. List of genes studied by Carrel and Willard, Cotton et al., and Tukiainen et al. for genic XCI.
DOI: 10.6084/m9.figshare.14091270
title: Additional file 7 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 7. Mapping of DMRs on chromosome X for NA19240 run 1 to the list of genes studied through XCI.
DOI: 10.6084/m9.figshare.14091264.v1
title: Additional file 5 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 5. Contains DMRs found in each sample.
DOI: 10.6084/m9.figshare.14091267
title: Additional file 6 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 6. List of genes studied by Carrel and Willard, Cotton et al., and Tukiainen et al. for genic XCI.
DOI: 10.6084/m9.figshare.14091270.v1
title: Additional file 7 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 7. Mapping of DMRs on chromosome X for NA19240 run 1 to the list of genes studied through XCI.
DOI: 10.6084/m9.figshare.14091273
title: Additional file 8 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 8. Mapping of autosomal DMRs to known and novel ICRs.
DOI: 10.6084/m9.figshare.14091273.v1
title: Additional file 8 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 8. Mapping of autosomal DMRs to known and novel ICRs.
DOI: 10.6084/m9.figshare.14091276
title: Additional file 9 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 9. List of imprinted, predicted, conflicting, and provisional imprinted genes from GeneImprint ( http://www.geneimprint.com/ ) and the catalog of human imprinted gene ( http://igc.otago.ac.nz/home.html ) database.
DOI: 10.6084/m9.figshare.14091276.v1
title: Additional file 9 of Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase

description: Additional file 9. List of imprinted, predicted, conflicting, and provisional imprinted genes from GeneImprint ( http://www.geneimprint.com/ ) and the catalog of human imprinted gene ( http://igc.otago.ac.nz/home.html ) database.
DOI: 10.6084/m9.figshare.14091279.v1
title: Additional file 1 of Access to chronic medicines: patients’ preferences for a last kilometre medicine delivery service in Cape Town, South Africa

description: Additional file 1.
DOI: 10.6084/m9.figshare.14091279
title: Additional file 1 of Access to chronic medicines: patients’ preferences for a last kilometre medicine delivery service in Cape Town, South Africa

description: Additional file 1.
DOI: 10.6084/m9.figshare.14091291
title: Additional file 2 of A scoping review of studies using observational data to optimise dynamic treatment regimens

description: Additional file 2. Extracted data for individual studies.
DOI: 10.6084/m9.figshare.14091291.v1
title: Additional file 2 of A scoping review of studies using observational data to optimise dynamic treatment regimens

description: Additional file 2. Extracted data for individual studies.
DOI: 10.6084/m9.figshare.14091361
title: Additional file 10 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 9: Figure S11. Normalized activities for the different phosphoproteins and experimental conditions for the BT20 cell line.
DOI: 10.6084/m9.figshare.14091361.v1
title: Additional file 10 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 9: Figure S11. Normalized activities for the different phosphoproteins and experimental conditions for the BT20 cell line.
DOI: 10.6084/m9.figshare.14091364.v1
title: Additional file 11 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 10: Figure S12. Normalized activities for the different phosphoproteins and experimental conditions for the HCC38 cell line.
DOI: 10.6084/m9.figshare.14091367
title: Additional file 12 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 11: Figure S13. Normalized activities for the different phosphoproteins and experimental conditions for the MCF7 cell line.
DOI: 10.6084/m9.figshare.14091370
title: Additional file 13 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 12: Figure S14. Normalized activities for the different phosphoproteins and experimental conditions for the SKBR3 cell line.
DOI: 10.6084/m9.figshare.14091364
title: Additional file 11 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 10: Figure S12. Normalized activities for the different phosphoproteins and experimental conditions for the HCC38 cell line.
DOI: 10.6084/m9.figshare.14091370.v1
title: Additional file 13 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 12: Figure S14. Normalized activities for the different phosphoproteins and experimental conditions for the SKBR3 cell line.
DOI: 10.6084/m9.figshare.14091367.v1
title: Additional file 12 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 11: Figure S13. Normalized activities for the different phosphoproteins and experimental conditions for the MCF7 cell line.
DOI: 10.6084/m9.figshare.14091382
title: Additional file 3 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 2: Figure S4. Driver script for the modeling of cell signalling with Dynamic Bayesian Networks. The file contains the Matlab commands to reproduce the analysis with the FALCON toolbox.
DOI: 10.6084/m9.figshare.14091382.v1
title: Additional file 3 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 2: Figure S4. Driver script for the modeling of cell signalling with Dynamic Bayesian Networks. The file contains the Matlab commands to reproduce the analysis with the FALCON toolbox.
DOI: 10.6084/m9.figshare.14091385
title: Additional file 4 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 3: Figure S5. Matlab workspace containing the raw analysis results.
DOI: 10.6084/m9.figshare.14091394.v1
title: Additional file 6 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 5: Figure S7. Summary spreadsheet containing the optimal parameter values obtained by the FALCON analysis.
DOI: 10.6084/m9.figshare.14091385.v1
title: Additional file 4 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 3: Figure S5. Matlab workspace containing the raw analysis results.
DOI: 10.6084/m9.figshare.14091391
title: Additional file 5 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 4: Figure S6. Network definition for the post-regularization model.
DOI: 10.6084/m9.figshare.14091391.v1
title: Additional file 5 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 4: Figure S6. Network definition for the post-regularization model.
DOI: 10.6084/m9.figshare.14091394
title: Additional file 6 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 5: Figure S7. Summary spreadsheet containing the optimal parameter values obtained by the FALCON analysis.
DOI: 10.6084/m9.figshare.14091397
title: Additional file 7 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 6: Figure S8. Summary spreadsheet containing the node values for different network states under the optimal parametrization.
DOI: 10.6084/m9.figshare.14091397.v1
title: Additional file 7 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 6: Figure S8. Summary spreadsheet containing the node values for different network states under the optimal parametrization.
DOI: 10.6084/m9.figshare.14091400
title: Additional file 8 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 7: Figure S9. Prior Knowledge network definition. The list of interactions specifies the topology of the signalling network used for the FALCON analysis.
DOI: 10.6084/m9.figshare.14091400.v1
title: Additional file 8 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 7: Figure S9. Prior Knowledge network definition. The list of interactions specifies the topology of the signalling network used for the FALCON analysis.
DOI: 10.6084/m9.figshare.14091403
title: Additional file 9 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 8: Figure S10. Constraints for the edge regularization. This empty file is used during the analysis to inform the algorithm that no prior information is used for constraining the regularization of the network model.
DOI: 10.6084/m9.figshare.14091403.v1
title: Additional file 9 of L-plastin Ser5 phosphorylation is modulated by the PI3K/SGK pathway and promotes breast cancer cell invasiveness

description: Additional file 8: Figure S10. Constraints for the edge regularization. This empty file is used during the analysis to inform the algorithm that no prior information is used for constraining the regularization of the network model.
DOI: 10.6084/m9.figshare.14091412
title: Additional file 1 of Stalagmite evidence for East Asian winter monsoon variability and 18O-depleted surface water in the Japan Sea during the last glacial period

description: Additional file 1.
DOI: 10.6084/m9.figshare.14091412.v1
title: Additional file 1 of Stalagmite evidence for East Asian winter monsoon variability and 18O-depleted surface water in the Japan Sea during the last glacial period

description: Additional file 1.
DOI: 10.6084/m9.figshare.14091432
title: Additional file 4 of Identification and functional analysis of the SARS-COV-2 nucleocapsid protein

description: Additional file 4: Supplementary file 1. The sequence data of Mass Spectrometry Analysis.
DOI: 10.5281/zenodo.4556465
title: Prediagnosis reports for studying edge-cloud communication

description: (Simulated) Prediagnosis reports generated from the testbed shared at https://github.com/Frmillar/NutriEvaluator
DOI: 10.5281/zenodo.4556464
title: Prediagnosis reports for studying edge-cloud communication

description: (Simulated) Prediagnosis reports generated from the testbed shared at https://github.com/Frmillar/NutriEvaluator