cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.9810164.v1
title: WGS performance metrics for the congruently/non-congruently classified samples between array/WGS and original coverage and downsampled WGS-derived data

description: This file contains WGS performance metrics for all the samples (n = 67). The data was derived using the CollectWgsMetrics tool from Picard tools (https://broadinstitute.github.io/picard/). The performance metrics include PCT_EXC_MAPQ, representing the fraction of aligned bases that were filtered out because they were in reads with low mapping quality and PCF_EXC_BASEQ, representing the fraction of aligned bases that were filtered out because they were of low base quality. The Type column indicates whether the sample relates to the tumour or normal tissue of a given donor. The Congruency column indicates whether a given sample was congruently (con) v/s non-congruently classified (ncon) classified between original and downsampled WGS data. The Metric column indicates the WGS performance metric of interest. The value column provides the numerical value of the WGS performance metric of interest for the tumour or normal sample of a particular donor.<br>
DOI: 10.6084/m9.figshare.9809729
title: MOESM8 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 8. Source code for training the HBA and HBD models and two example molecules.
DOI: 10.6084/m9.figshare.9809729.v1
title: MOESM8 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 8. Source code for training the HBA and HBD models and two example molecules.
DOI: 10.6084/m9.figshare.9809978.v2
title: HRD score and HRD score components matrix for downsampled (30X) WGS data

description: This file contains the HRD scores and HRD score components (HRD-LOH, LST and NtAI) for the downsampled (30X) WGS-derived data.
DOI: 10.6084/m9.figshare.9809978.v1
title: HRD score and HRD score components matrix for downsampled (30X) WGS data

description: This file contains the HRD scores and HRD score components (HRD-LOH, LST and NtAI) for the downsampled (30X) WGS-derived data.
DOI: 10.6084/m9.figshare.9809720
title: MOESM7 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 5. HBD complexes database.
DOI: 10.6084/m9.figshare.9809714
title: MOESM5 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 3. HBD database.
DOI: 10.6084/m9.figshare.9809717
title: MOESM6 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 4. HBA complexes database.
DOI: 10.6084/m9.figshare.9809711
title: MOESM2 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 2. HBA database.
DOI: 10.6084/m9.figshare.9809720.v1
title: MOESM7 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 5. HBD complexes database.
DOI: 10.6084/m9.figshare.9809711.v1
title: MOESM2 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 2. HBA database.
DOI: 10.6084/m9.figshare.9809714.v1
title: MOESM5 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 3. HBD database.
DOI: 10.6084/m9.figshare.9809717.v1
title: MOESM6 of Machine learning models for hydrogen bond donor and acceptor strengths using large and diverse training data generated by first-principles interaction free energies

description: Additional file 4. HBA complexes database.
DOI: 10.6084/m9.figshare.9809621
title: Additional file 9: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S6. Complete list of all tetramer positive hits detected for neoantigens and viral epitopes for all patients in the current study. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.9809615
title: Additional file 8: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S5. Neoantigen and virus epitope hits detected for patient 3. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.9809621.v1
title: Additional file 9: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S6. Complete list of all tetramer positive hits detected for neoantigens and viral epitopes for all patients in the current study. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.9809606
title: Additional file 7: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S4. Complete list of tetramer hits for CD8+ T cells and information on additional metrics that were monitored for each hit. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.9809597
title: Additional file 6: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S3. List of antibodies, their clone information and heavy metal tags used in the staining panel for CyTOF. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.9809606.v1
title: Additional file 7: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S4. Complete list of tetramer hits for CD8+ T cells and information on additional metrics that were monitored for each hit. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.9809597.v1
title: Additional file 6: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S3. List of antibodies, their clone information and heavy metal tags used in the staining panel for CyTOF. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.9809582
title: Additional file 4: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S1. Patient characteristics and list of PBMC samples selected for the current analysis from the POPLAR trial. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.9809588
title: Additional file 5: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S2. Tab 1, Number of neoantigen and viral specific tetramers generated for each patient sample. Tab 2, Complete list of peptides used to generate tetramers with their corresponding HLA alleles and predicted binding affinity. (XLSX 41 kb)
DOI: 10.6084/m9.figshare.9809582.v1
title: Additional file 4: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S1. Patient characteristics and list of PBMC samples selected for the current analysis from the POPLAR trial. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.9809588.v1
title: Additional file 5: of Late-differentiated effector neoantigen-specific CD8+ T cells are enriched in peripheral blood of non-small cell lung carcinoma patients responding to atezolizumab treatment

description: Table S2. Tab 1, Number of neoantigen and viral specific tetramers generated for each patient sample. Tab 2, Complete list of peptides used to generate tetramers with their corresponding HLA alleles and predicted binding affinity. (XLSX 41 kb)
DOI: 10.6084/m9.figshare.9809549
title: Additional file 1: of Bacillus sp. probiotic supplementation diminish the Escherichia coli F4ac infection in susceptible weaned pigs by influencing the intestinal immune response, intestinal microbiota and blood metabolomics

description: Table S1. List of the quantified metabolites using the MS/MS targeted analysis. (CSV 18 kb)
DOI: 10.6084/m9.figshare.9809549.v1
title: Additional file 1: of Bacillus sp. probiotic supplementation diminish the Escherichia coli F4ac infection in susceptible weaned pigs by influencing the intestinal immune response, intestinal microbiota and blood metabolomics

description: Table S1. List of the quantified metabolites using the MS/MS targeted analysis. (CSV 18 kb)
DOI: 10.6084/m9.figshare.9809501
title: MOESM3 of Real-time algorithm for Poissonian noise reduction in low-dose fluoroscopy: performance evaluation

description: Additional file 3. The NVCA Matlab routineÂ function. It produces the NVCA-filtered sequence, requiring as inputs the raw fluoroscopy sequence, the spatial (N) and temporal (K) filter dimensions, the noise coefficients (A and B) and the F value.
DOI: 10.6084/m9.figshare.9809501.v1
title: MOESM3 of Real-time algorithm for Poissonian noise reduction in low-dose fluoroscopy: performance evaluation

description: Additional file 3. The NVCA Matlab routineÂ function. It produces the NVCA-filtered sequence, requiring as inputs the raw fluoroscopy sequence, the spatial (N) and temporal (K) filter dimensions, the noise coefficients (A and B) and the F value.
DOI: 10.6084/m9.figshare.9809456
title: Additional file 3: of Impact of transition to a subterranean lifestyle on morphological disparity and integration in talpid moles (Mammalia, Talpidae)

description: Phylogenetic tree calibration data. (XLSX 31 kb)
DOI: 10.6084/m9.figshare.9809456.v1
title: Additional file 3: of Impact of transition to a subterranean lifestyle on morphological disparity and integration in talpid moles (Mammalia, Talpidae)

description: Phylogenetic tree calibration data. (XLSX 31 kb)
DOI: 10.6084/m9.figshare.9809444
title: Additional file 1: of Impact of transition to a subterranean lifestyle on morphological disparity and integration in talpid moles (Mammalia, Talpidae)

description: Sampling details. (XLSX 54 kb)
DOI: 10.6084/m9.figshare.9809444.v1
title: Additional file 1: of Impact of transition to a subterranean lifestyle on morphological disparity and integration in talpid moles (Mammalia, Talpidae)

description: Sampling details. (XLSX 54 kb)
DOI: 10.6084/m9.figshare.9809414
title: MOESM2 of Mitochondrial DNA variation of the ruffed grouse (Bonasa umbellus)

description: Additional file 2. Nucleotide Sequences Used for Analyses. This spreadsheet contains the complete sequences of the 100 individual ruffed grouse plus the outgroup taxon used in this study. Individual subspecies are cross-referenced, and individual sequences representing the 19 haplotypes used for TableÂ 1 and Figs.Â 1 and 2 are identified.
DOI: 10.6084/m9.figshare.9809414.v1
title: MOESM2 of Mitochondrial DNA variation of the ruffed grouse (Bonasa umbellus)

description: Additional file 2. Nucleotide Sequences Used for Analyses. This spreadsheet contains the complete sequences of the 100 individual ruffed grouse plus the outgroup taxon used in this study. Individual subspecies are cross-referenced, and individual sequences representing the 19 haplotypes used for TableÂ 1 and Figs.Â 1 and 2 are identified.
DOI: 10.6084/m9.figshare.9809402
title: MOESM2 of Construction of gene causal regulatory networks using microarray data with the coefficient of intrinsic dependence

description: Additional file 2: Table S1. The list of 122 bHLH-related probess in the microarray. The ones recognize the G-box in their targets’ promoter regions (Gonzalez 2015) are classified as the ‘Source’ genes; the ones containing G-box sequences in their promoter regions are classified as the ‘Target’ genes. ‘in.degree’ is the number of directed edge(s) using the probe as the target; ‘out.degree’ is the number of directed edge(s) using the probe as the source; ‘total.degree’ = ’in.degree’ + ’out.degree’. Table S2. The resulting sub-networks for bHLH source probes.
DOI: 10.6084/m9.figshare.9809402.v1
title: MOESM2 of Construction of gene causal regulatory networks using microarray data with the coefficient of intrinsic dependence

description: Additional file 2: Table S1. The list of 122 bHLH-related probess in the microarray. The ones recognize the G-box in their targets’ promoter regions (Gonzalez 2015) are classified as the ‘Source’ genes; the ones containing G-box sequences in their promoter regions are classified as the ‘Target’ genes. ‘in.degree’ is the number of directed edge(s) using the probe as the target; ‘out.degree’ is the number of directed edge(s) using the probe as the source; ‘total.degree’ = ’in.degree’ + ’out.degree’. Table S2. The resulting sub-networks for bHLH source probes.
DOI: 10.6084/m9.figshare.9809387
title: Additional file 2: of dnAQET: a framework to compute a consolidated metric for benchmarking quality of de novo assemblies

description: Table S1. The model coefficients for human chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the hg38 build of the human genome chromosomes. Table S2. The model coefficients for chimpanzee chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the panTro6 build of the chimpanzee genome chromosomes. Table S3. The model coefficients for mouse chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the mm10 build of the mouse genome chromosomes. Table S4. The model coefficients for rat chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the rn6 build of the rat genome chromosomes. Table S5. The model coefficients for zebrafish chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the danRer11 build of the zebrafish genome chromosomes. Table S6. Computed QUAST-LG metrics for human reference genome builds. Table S7. Computed QUAST-LG metrics for mouse reference genome builds. Table S8. Computed QUAST-LG metrics for rat reference genome builds. Table S9. Computed QUAST-LG metrics for chimpanzee reference genome builds. Table S10. Computed QUAST-LG metrics for zebrafish reference genome builds. Table S11. Computed QUAST-LG metrics, z-scores of the metrics, the rankings based on the z-scores and finally the Pearson Correlation coefficients of these rankings when compared to the summed z-score based ranking (i.e., the ground truth) for NA24835 assemblies. (XLSX 52 kb)
DOI: 10.6084/m9.figshare.9809387.v1
title: Additional file 2: of dnAQET: a framework to compute a consolidated metric for benchmarking quality of de novo assemblies

description: Table S1. The model coefficients for human chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the hg38 build of the human genome chromosomes. Table S2. The model coefficients for chimpanzee chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the panTro6 build of the chimpanzee genome chromosomes. Table S3. The model coefficients for mouse chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the mm10 build of the mouse genome chromosomes. Table S4. The model coefficients for rat chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the rn6 build of the rat genome chromosomes. Table S5. The model coefficients for zebrafish chrosomomes. The table displays the coefficients for the length, the relocation threshold and the intercept for the linear regression models obtained from the danRer11 build of the zebrafish genome chromosomes. Table S6. Computed QUAST-LG metrics for human reference genome builds. Table S7. Computed QUAST-LG metrics for mouse reference genome builds. Table S8. Computed QUAST-LG metrics for rat reference genome builds. Table S9. Computed QUAST-LG metrics for chimpanzee reference genome builds. Table S10. Computed QUAST-LG metrics for zebrafish reference genome builds. Table S11. Computed QUAST-LG metrics, z-scores of the metrics, the rankings based on the z-scores and finally the Pearson Correlation coefficients of these rankings when compared to the summed z-score based ranking (i.e., the ground truth) for NA24835 assemblies. (XLSX 52 kb)
DOI: 10.6084/m9.figshare.9809324
title: Additional file 3: of CytoConverter: a web-based tool to convert karyotypes to genomic coordinates

description: Table output generated by CytoConverter from sample input from Additional file 2. (TXT 56 kb)
DOI: 10.6084/m9.figshare.9809324.v1
title: Additional file 3: of CytoConverter: a web-based tool to convert karyotypes to genomic coordinates

description: Table output generated by CytoConverter from sample input from Additional file 2. (TXT 56 kb)
DOI: 10.6084/m9.figshare.9809312
title: Additional file 2: of CytoConverter: a web-based tool to convert karyotypes to genomic coordinates

description: Sample table containing karyotypes for 943 pediatric patients from the TARGET (“Therapeutically Applicable Research To Generate Effective Treatments”; [10]) project. (TXT 54 kb)
DOI: 10.6084/m9.figshare.9809312.v1
title: Additional file 2: of CytoConverter: a web-based tool to convert karyotypes to genomic coordinates

description: Sample table containing karyotypes for 943 pediatric patients from the TARGET (“Therapeutically Applicable Research To Generate Effective Treatments”; [10]) project. (TXT 54 kb)
DOI: 10.6084/m9.figshare.9809285
title: Additional file 9: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S5. Expression patterns of C2H2-zinc finger genes at various developmental stages in G. hirsutum (TM-1) were measured by RNA-seq. (XLSX 49 kb)
DOI: 10.6084/m9.figshare.9809285.v1
title: Additional file 9: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S5. Expression patterns of C2H2-zinc finger genes at various developmental stages in G. hirsutum (TM-1) were measured by RNA-seq. (XLSX 49 kb)
DOI: 10.6084/m9.figshare.9809270
title: Additional file 6: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S2. List of 386 C2HC2-zinc finger genes in upland cotton and their proteins sequence features including, proteins length, molecular weight and subcellular positions. (XLSX 23 kb)
DOI: 10.6084/m9.figshare.9809276
title: Additional file 7: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S3. Synonymous substitution rates (Ks) and non-synonymous substitution rates (Ka) are represented for each orthologous gene pairs between upland cotton and their ancestral diploid cotton, G. arboreum (A2) and G. raimondii (D5). (XLSX 35 kb)
DOI: 10.6084/m9.figshare.9809270.v1
title: Additional file 6: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S2. List of 386 C2HC2-zinc finger genes in upland cotton and their proteins sequence features including, proteins length, molecular weight and subcellular positions. (XLSX 23 kb)
DOI: 10.6084/m9.figshare.9809276.v1
title: Additional file 7: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S3. Synonymous substitution rates (Ks) and non-synonymous substitution rates (Ka) are represented for each orthologous gene pairs between upland cotton and their ancestral diploid cotton, G. arboreum (A2) and G. raimondii (D5). (XLSX 35 kb)
DOI: 10.6084/m9.figshare.9809261
title: Additional file 5: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S1. Location, annotation and protein domains of C2H2-zinc finger genes in cotton genomes. (XLSX 54 kb)
DOI: 10.6084/m9.figshare.9809261.v1
title: Additional file 5: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S1. Location, annotation and protein domains of C2H2-zinc finger genes in cotton genomes. (XLSX 54 kb)
DOI: 10.6084/m9.figshare.9809216
title: Additional file 10: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S6. Expression patterns of C2H2-zinc finger genes at two stages of cotton fiber development in Ligon-lintless-1 and wild-type (WT) were measured by RNA-seq. (XLSX 38 kb)
DOI: 10.6084/m9.figshare.9809216.v1
title: Additional file 10: of Genome-wide analysis of cotton C2H2-zinc finger transcription factor family and their expression analysis during fiber development

description: Table S6. Expression patterns of C2H2-zinc finger genes at two stages of cotton fiber development in Ligon-lintless-1 and wild-type (WT) were measured by RNA-seq. (XLSX 38 kb)
DOI: 10.6084/m9.figshare.9809213
title: Additional file 1: of The JAK2/STAT3/CCND2 Axis promotes colorectal Cancer stem cell persistence and radioresistance

description: Consisting of Supplementary Material and Methods, Supplementary Tables S1-S14, and Supplementary Figure legends. (ZIP 758 kb)
DOI: 10.6084/m9.figshare.9809213.v1
title: Additional file 1: of The JAK2/STAT3/CCND2 Axis promotes colorectal Cancer stem cell persistence and radioresistance

description: Consisting of Supplementary Material and Methods, Supplementary Tables S1-S14, and Supplementary Figure legends. (ZIP 758 kb)
DOI: 10.6084/m9.figshare.9809165
title: Additional file 5: of Understanding the molecular mechanisms underlying graft success in grapevine

description: List of DEGs between combinations and between time points. (XLSX 592 kb)
DOI: 10.6084/m9.figshare.9809162
title: Additional file 4: of Understanding the molecular mechanisms underlying graft success in grapevine

description: MicroRNAs selected for qPCR analysis, their annotated potential targets, and respective functions. (XLSX 75 kb)
DOI: 10.6084/m9.figshare.9809165.v1
title: Additional file 5: of Understanding the molecular mechanisms underlying graft success in grapevine

description: List of DEGs between combinations and between time points. (XLSX 592 kb)