cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7980545.v1
title: Additional file 3: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S3. Detailed report of the de novo assemblies. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.7980524
title: Additional file 18: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S12. Validation set. Primer pair for eight validation transcripts aligned with original homeolog-specific RNA-Seq data. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.7980533.v1
title: Additional file 1: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S1. Durum wheat accessions description and RNA-Seq data. Accession name, pedigree, accession feature and the constitutor for the 13 varieties used for RNA sequencing and SNP discovery are reported along with the associated sequencing yields for each of the three sampled tissues. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.7980518
title: Additional file 17 of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S11 Significant differential expression between homoeolog genes. Under the GLM fit analysis, lines in green/brown represent genes with concordant/discordant homoeolog expression in phased blocks within the same gene. (XLSX 1605 kb)
DOI: 10.6084/m9.figshare.7980524.v1
title: Additional file 18: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S12. Validation set. Primer pair for eight validation transcripts aligned with original homeolog-specific RNA-Seq data. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.7980518.v1
title: Additional file 17 of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S11 Significant differential expression between homoeolog genes. Under the GLM fit analysis, lines in green/brown represent genes with concordant/discordant homoeolog expression in phased blocks within the same gene. (XLSX 1605 kb)
DOI: 10.6084/m9.figshare.7980494
title: Additional file 14: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S10. Unique proteins matching with T. durum transcripts. Unique proteins matching with T. durum transcripts divided by plant species. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.7980494.v1
title: Additional file 14: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S10. Unique proteins matching with T. durum transcripts. Unique proteins matching with T. durum transcripts divided by plant species. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.7980485
title: Additional file 13: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S9. Annotation Statistics. Annotation statistics for the Svevo RNA-seq transcriptome assembly divided into high and low confidence annotation. Annotations with either BioMart or BAR+. Gene Ontology (GO) computed with Blast2GO (B2GO). Three bottom lines from Blast2GO reports. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.7980485.v1
title: Additional file 13: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S9. Annotation Statistics. Annotation statistics for the Svevo RNA-seq transcriptome assembly divided into high and low confidence annotation. Annotations with either BioMart or BAR+. Gene Ontology (GO) computed with Blast2GO (B2GO). Three bottom lines from Blast2GO reports. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.7980473
title: Additional file 11: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S8. Transcriptomes of the plant species used for BLASTx. Plant species from Ensembl Plants used for BLASTx alignment of transcripts, to infer functional annotation. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.7980473.v1
title: Additional file 11: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S8. Transcriptomes of the plant species used for BLASTx. Plant species from Ensembl Plants used for BLASTx alignment of transcripts, to infer functional annotation. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.7980464
title: Additional file 10: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S7. List of Svevo private contigs with GO annotation derived from BLASTn comparison between Svevo and Kronos contigs. (XLSX 338 kb)
DOI: 10.6084/m9.figshare.7980464.v1
title: Additional file 10: of Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

description: Table S7. List of Svevo private contigs with GO annotation derived from BLASTn comparison between Svevo and Kronos contigs. (XLSX 338 kb)
DOI: 10.15129/7ec1bd50-bdaf-4225-b300-10f875f1f4ae
title: Data for: "Unexpected Nickel Complex Speciation Unlocks Alternative Pathways for the Reactions of Alkyl Halides with dppf-Nickel(0)"

description: This dataset contains: NMR spectroscopic data for the characterisation of compounds and for the time-resolved kinetic study of their reactions; and GC-FID data for related reactions. The former is provided in Bruker Topspin format but the 'fid' file can be opened using any third party NMR processing software. GC-FID data are provided in PDF format because the raw data are in a proprietary format, but the PDF data provide the raw data that was used for calculations and to draw conclusions in the study.
DOI: 10.6084/m9.figshare.7980212
title: STEM Night at Daniel Butler Elementary

description: I volunteered to lead a table and my son's elementary school STEM night. My friend Meghan and I worked together to run our station. Two people were enough to run both sides smoothly, but a third would have been great especially for bathroom breaks and water refills (were talking CONSTANTLY). On one side of the table we had a stereo dissecting microscope and LED light source set up. We had the students looking at dead flies stuck to the bottom of a petri dish with double stick tape. On one side of the dish were two males and females mounted on their sides and backs. On the other side of the dish were some examples of different phenotypes. White eyes, bar eyes, curly wings, etc. This station also had a laminated diagram showing the similarities and differences between males and females. On the second side of the table I had brought 4 bottles of wild type flies from our lab. The bottles were about 2 weeks old, so the students could see all parts of the life cycle in one vessel. The plugs were taped down VERY WELL. I also had laminated handouts showing the life cycle of the fly as well as the similarities in body systems between humans and fruit flies. I think the students were engaged with both parts of our station. Some were very excited just to be looking through a microscope at ANYTHING. They enjoyed looking at flies but also at their fingernails and at the DNA they made at the strawberry DNA extraction station next door. Some kids found it tricky to see through the scope, but asking them to try looking through with just one eye was helpful. There was a range of reactions to the bottles of flies from completely disgusted to bored to fascinated. Both of the laminated sheets showing the life cycle and the similarities between flies and humans were extremely useful to help the kids visualize in a different way what they were seeing in the bottles and through the scope. This also led us to conversations about how we can use flies to study human bodies and human diseases, like ALS and Alzheimer's. We received incredibly positive feedback from the organizers and from the parents, especially about the part where we were very clear with the kids that “yes, we are scientists” and “Oh absolutely women can be scientists. ANYONE can be a scientist.” I think the students enjoyed our station even though they didn't have a physical object the made like some of the other stations. The parents who were accompanying some of the younger kids also seemed interested and had great questions. Oh, yeah, we had a TON of great questions from the students. Some wanted even more information to share with their friends, especially about how we can study human diseases using Drosophila as a model organism.
DOI: 10.6084/m9.figshare.7980212.v2
title: STEM Night at Daniel Butler Elementary

description: I volunteered to lead a table and my son's elementary school STEM night. My friend Meghan and I worked together to run our station. Two people were enough to run both sides smoothly, but a third would have been great especially for bathroom breaks and water refills (were talking CONSTANTLY). On one side of the table we had a stereo dissecting microscope and LED light source set up. We had the students looking at dead flies stuck to the bottom of a petri dish with double stick tape. On one side of the dish were two males and females mounted on their sides and backs. On the other side of the dish were some examples of different phenotypes. White eyes, bar eyes, curly wings, etc. This station also had a laminated diagram showing the similarities and differences between males and females. On the second side of the table I had brought 4 bottles of wild type flies from our lab. The bottles were about 2 weeks old, so the students could see all parts of the life cycle in one vessel. The plugs were taped down VERY WELL. I also had laminated handouts showing the life cycle of the fly as well as the similarities in body systems between humans and fruit flies. I think the students were engaged with both parts of our station. Some were very excited just to be looking through a microscope at ANYTHING. They enjoyed looking at flies but also at their fingernails and at the DNA they made at the strawberry DNA extraction station next door. Some kids found it tricky to see through the scope, but asking them to try looking through with just one eye was helpful. There was a range of reactions to the bottles of flies from completely disgusted to bored to fascinated. Both of the laminated sheets showing the life cycle and the similarities between flies and humans were extremely useful to help the kids visualize in a different way what they were seeing in the bottles and through the scope. This also led us to conversations about how we can use flies to study human bodies and human diseases, like ALS and Alzheimer's. We received incredibly positive feedback from the organizers and from the parents, especially about the part where we were very clear with the kids that “yes, we are scientists” and “Oh absolutely women can be scientists. ANYONE can be a scientist.” I think the students enjoyed our station even though they didn't have a physical object the made like some of the other stations. The parents who were accompanying some of the younger kids also seemed interested and had great questions. Oh, yeah, we had a TON of great questions from the students. Some wanted even more information to share with their friends, especially about how we can study human diseases using Drosophila as a model organism.
DOI: 10.6084/m9.figshare.7980176
title: Supplementary files for transcriptome profiling of induced susceptibility effects on soybean- soybean aphid interaction

description: This dataset consists of two Excel spreadsheet files in <b>.xlsx</b> format, a Supplementary File and Table S1 in <b>.docx</b> format. The image files are in <b>.tiff </b>format. The data were generated as part of a study which used RNA sequencing to generate transcriptional datasets for transcriptome profiling of induced susceptibility effects on soybean- soybean aphid (Hemiptera: Aphididae) interaction.<br>The data consists of the following files:Supplementary file 1: Methodology description<br>Table S1: Statistics of the transcriptomic data using RNA-seq pipeline used in this study.<br>Figure S1: A flow chart representing experimental methods.<br>Figure S2: A flow chart showing the RNA-seq data analysis pipeline.<br>Figure S3: The hierarchical clustering of top 3,000 variable genes.<br>Figure S4: The correlation between the samples using the top 75% genes.<br>Figure S5: Quality metrics of G. max sequencing data. (a) Mean quality scores per position. (b) Per sequence quality scores. (c) GC content distribution. (d) Read length distribution<br>Data File 21: The transformed transcript abundance counts for all the samples.<br>Data File 22: The hierarchical clustering of top 3,000 variable genes.<br><br><br><br><br>
DOI: 10.6084/m9.figshare.7980284.v1
title: Transcriptomic profiles of 33 opium poppy samples in different tissues, growth phases, and cultivars

description: Supplementary tables from this study, including raw data of the major BIAs contents in one Kilogram dry leaves in different germplasm lines at filling stag.
DOI: 10.6084/m9.figshare.7980212.v1
title: Daniel Butler Elementary STEM Night

description: I volunteered to lead a table and my son's elementary school STEM night. My friend Meghan and I worked together to run our station. Two people were enough to run both sides smoothly, but a third would have been great especially for bathroom breaks and water refills (were talking CONSTANTLY). On one side of the table we had a stereo dissecting microscope and LED light source set up. We had the students looking at dead flies stuck to the bottom of a petri dish with double stick tape. On one side of the dish were two males and females mounted on their sides and backs. On the other side of the dish were some examples of different phenotypes. White eyes, bar eyes, curly wings, etc. This station also had a laminated diagram showing the similarities and differences between males and females. On the second side of the table I had brought 4 bottles of wild type flies from our lab. The bottles were about 2 weeks old, so the students could see all parts of the life cycle in one vessel. The plugs were taped down VERY WELL. I also had laminated handouts showing the life cycle of the fly as well as the similarities in body systems between humans and fruit flies. I think the students were engaged with both parts of our station. Some were very excited just to be looking through a microscope at ANYTHING. They enjoyed looking at flies but also at their fingernails and at the DNA they made at the strawberry DNA extraction station next door. Some kids found it tricky to see through the scope, but asking them to try looking through with just one eye was helpful. There was a range of reactions to the bottles of flies from completely disgusted to bored to fascinated. Both of the laminated sheets showing the life cycle and the similarities between flies and humans were extremely useful to help the kids visualize in a different way what they were seeing in the bottles and through the scope. This also led us to conversations about how we can use flies to study human bodies and human diseases, like ALS and Alzheimer's. We received incredibly positive feedback from the organizers and from the parents, especially about the part where we were very clear with the kids that “yes, we are scientists” and “Oh absolutely women can be scientists. ANYONE can be a scientist.” I think the students enjoyed our station even though they didn't have a physical object the made like some of the other stations. The parents who were accompanying some of the younger kids also seemed interested and had great questions. Oh, yeah, we had a TON of great questions from the students. Some wanted even more information to share with their friends, especially about how we can study human diseases using Drosophila as a model organism.
DOI: 10.6084/m9.figshare.7980113
title: Winokur_2019_ZIKV_individualtiters.csv

description: Individual Zika virus RNA titers for mosquito bodies, legs and wings, and saliva over time at 4 temperatures.
DOI: 10.6084/m9.figshare.7980113.v1
title: Winokur_2019_ZIKV_individualtiters.csv

description: Individual Zika virus RNA titers for mosquito bodies, legs and wings, and saliva over time at 4 temperatures.
DOI: 10.6084/m9.figshare.7980107
title: Interactive effects of spruce budworm and moose herbivory on balsam fir recruitment and regeneration

description: This fileset includes R code and data used to investigate the impacts of spruce budworm and moose herbivory on balsam fir recruitment and regeneration in Terra Nova National Park, NL, Canada.<br>
DOI: 10.6084/m9.figshare.7980107.v1
title: Interactive effects of spruce budworm and moose herbivory on balsam fir recruitment and regeneration

description: This fileset includes R code and data used to investigate the impacts of spruce budworm and moose herbivory on balsam fir recruitment and regeneration in Terra Nova National Park, NL, Canada.<br>
DOI: 10.6084/m9.figshare.7980176.v2
title: Supplementary Files for Transcriptome Profiling of induced susceptibility effects on soybean- soybean aphid interactions

description: This dataset consists of two Excel spreadsheet files in <b>.xlsx</b> format, a Supplementary File and Table S1 in <b>.docx</b> format. The image files are in <b>.tiff </b>format. The data were generated as part of a study which used RNA sequencing to generate transcriptional datasets for transcriptome profiling of induced susceptibility effects on soybean- soybean aphid (Hemiptera: Aphididae) interactions<br>The data consists of the following files:Supplementary File 1: Methodology description<br>Table S1: Statistics of the transcriptomic data using RNA-seq pipeline used in this study.<br>Figure S1: A flow chart representing experimental methods.<br>Figure S2: A flow chart showing the RNA-seq data analysis pipeline.<br>Figure S3: The hierarchical clustering of top 3,000 variable genes.<br>Figure S4: The correlation between the samples using the top 75% genes.<br>Figure S5: Quality metrics of G. max sequencing data. (a) Mean quality scores per position. (b) Per sequence quality scores. (c) GC content distribution. (d) Read length distribution<br>Data File 12: The transformed transcript abundance counts for all the samples.<br>Data File 13: The hierarchical clustering of top 3,000 variable genes.<br><br><br><br><br>
DOI: 10.6084/m9.figshare.7980080
title: condensed_species_NCBI v1.0.1

description: The condensed_species.csv dataset is the second data product from the data merger workflow. The trait data are mapped and aggregated to NCBI species level.
DOI: 10.6084/m9.figshare.7980176.v3
title: Supplementary Files for Transcriptome Profiling of induced susceptibility effects on soybean- soybean aphid interaction

description: This dataset consists of two Excel spreadsheet files in <b>.xlsx</b> format, a Supplementary File and Table S1 in <b>.docx</b> format. The image files are in <b>.tiff </b>format. The data were generated as part of a study which used RNA sequencing to generate transcriptional datasets for transcriptome profiling of induced susceptibility effects on soybean- soybean aphid (Hemiptera: Aphididae) interaction.<br>The data consists of the following files:Supplementary File 1: Methodology description<br>Table S1: Statistics of the transcriptomic data using RNA-seq pipeline used in this study.<br>Figure S1: A flow chart representing experimental methods.<br>Figure S2: A flow chart showing the RNA-seq data analysis pipeline.<br>Figure S3: The hierarchical clustering of top 3,000 variable genes.<br>Figure S4: The correlation between the samples using the top 75% genes.<br>Figure S5: Quality metrics of G. max sequencing data. (a) Mean quality scores per position. (b) Per sequence quality scores. (c) GC content distribution. (d) Read length distribution<br>Data File 12: The transformed transcript abundance counts for all the samples.<br>Data File 13: The hierarchical clustering of top 3,000 variable genes.<br><br><br><br><br>
DOI: 10.6084/m9.figshare.7980068
title: condensed_traits_NCBI v1.0.1

description: The condensed_traits.csv dataset is the first data product from the data merger workflow. It include species and strains, and the raw are in their clean, but raw, form. Use the NCBI taxonomy.
DOI: 10.6084/m9.figshare.7980176.v4
title: Supplementary files for transcriptome profiling of induced susceptibility effects on soybean- soybean aphid interaction

description: This dataset consists of two Excel spreadsheet files in <b>.xlsx</b> format, a Supplementary File and Table S1 in <b>.docx</b> format. The image files are in <b>.tiff </b>format. The data were generated as part of a study which used RNA sequencing to generate transcriptional datasets for transcriptome profiling of induced susceptibility effects on soybean- soybean aphid (Hemiptera: Aphididae) interaction.<br>The data consists of the following files:Supplementary File 1: Methodology description<br>Table S1: Statistics of the transcriptomic data using RNA-seq pipeline used in this study.<br>Figure S1: A flow chart representing experimental methods.<br>Figure S2: A flow chart showing the RNA-seq data analysis pipeline.<br>Figure S3: The hierarchical clustering of top 3,000 variable genes.<br>Figure S4: The correlation between the samples using the top 75% genes.<br>Figure S5: Quality metrics of G. max sequencing data. (a) Mean quality scores per position. (b) Per sequence quality scores. (c) GC content distribution. (d) Read length distribution<br>Data File 12: The transformed transcript abundance counts for all the samples.<br>Data File 13: The hierarchical clustering of top 3,000 variable genes.<br><br><br><br><br>
DOI: 10.6084/m9.figshare.7980062
title: dataset

description: question answering dataset
DOI: 10.17608/k6.auckland.7979942
title: Supplemental information for Sander et al., Transcriptional profiling of the zebrafish proximal tubule

description: The hepatocyte nuclear factor 1 beta (Hnf1b) transcription factor is a key regulator of kidney tubule formation and is associated with a syndrome of renal cysts and early onset diabetes. To further our understanding of Hnf1b in the developing zebrafish kidney, we have performed RNA-Seq of proximal tubules from hnf1b-deficient larvae. This analysis revealed an enrichment of gene transcripts encoding transporters of the solute carrier (SLC) superfamily, including multiple members of the slc2 and slc5 glucose transporters. An investigation of the expression of slc2a1a, slc2a2, slc5a2, as well as a poorly studied glucose/mannose transporter encoded by slc5a9, revealed that these genes undergo dynamic spatiotemporal changes during tubule formation and maturation. A comparative analysis of zebrafish SLC genes with those expressed in mouse proximal tubules showed a substantial overlap at the level of gene families, indicating a high degree of functional conservation between zebrafish and mammalian proximal tubules. Taken together, our findings are consistent with a role for Hnf1b as a critical determinant of proximal tubule transport function by acting upstream of a large number of SLC genes and validate the zebrafish as a physiologically relevant model of the mammalian proximal tubule.<br><br>