cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25392/leicester.data.7976873.v2
title: Images Of Research 2018

description: <b>Images Of Research 2018 Winners:</b> Martha Papadopoulou – ‘One picture – two worlds’ - Judges' Prize Winner Mandi Jamalian Hamedani – ‘In search for inner peace’ - Katherine May People's Choice Winner Olga Yegorova – ‘ “Ni Una Menos, ni una muerta más!” fighting for the lives of Bolivian women’ - Judges' Prize Runner-up Kate Gooch and Georgine Barkham-Perry – ‘Finding Hope in a Hopeless Place’ - People's Choice Runner-up <b>Images Of Research 2018 successful submissions:</b> Abbey Ellis – ‘Something’s Missing’ Emily Castells – ‘Fast-Paced Study in Respiratory Research’ Andrew Blain – ‘Inside the Dish’ Aude Cumont – ‘Army of Mushrooms, by Disinfection Mushrooms’ Ben Parsons – ‘Holey Prayers’ Thomas Newman – ‘Big Sky, Big Future’ Diyana Kasimon – ‘Unity in Diversity’ Jan Vandeburie – ‘Reading Between the Lines’ Philip Evans – ‘Andromeda’s revenge’ John Goodwin – ‘Return to Winston Parva: Sex and Violence at the ‘Regal’’ Yogini Chudasama – ‘Secrets to Living Longer’ Eleni Ganiti – ‘Contemporary Art?’ Emily Richardson – ‘Cellular Fireworks’ Seth O'Neill – ‘Achille's Heat’ Padraig Donnelly – ‘Peering into Jupiter's Atmosphere from Earth’ Colin Hyde – ‘In the midst of life we are in death’ Georgina Lockton – ‘Researching Vehicle Automation in 1960s Britain’ Jan Oliver Ringert and José Miguel Rojas – ‘DriverLeics’ Amy Van Allen – ‘Life in the Andes’ Eva Krockow – ‘Line Up and Take Note’ Yewande Okuleye – ‘Hemp Seeds in Safe Hands’Rod Moore - 'Vaping'
DOI: 10.25392/leicester.data.7976873.v1
title: Images Of Research 2018

description: <b>Images Of Research 2018 Winners:</b> Martha Papadopoulou – ‘One picture – two worlds’ - Judges' Prize Winner Mandi Jamalian Hamedani – ‘In search for inner peace’ - Katherine May People's Choice Winner Olga Yegorova – ‘ “Ni Una Menos, ni una muerta más!” fighting for the lives of Bolivian women’ - Judges' Prize Runner-up Kate Gooch and Georgine Barkham-Perry – ‘Finding Hope in a Hopeless Place’ - People's Choice Runner-up <b>Images Of Research 2018 successful submissions:</b> Abbey Ellis – ‘Something’s Missing’ Emily Castells – ‘Fast-Paced Study in Respiratory Research’ Andrew Blain – ‘Inside the Dish’ Aude Cumont – ‘Army of Mushrooms, by Disinfection Mushrooms’ Ben Parsons – ‘Holey Prayers’ Thomas Newman – ‘Big Sky, Big Future’ Diyana Kasimon – ‘Unity in Diversity’ Jan Vandeburie – ‘Reading Between the Lines’ Philip Evans – ‘Andromeda’s revenge’ John Goodwin – ‘Return to Winston Parva: Sex and Violence at the ‘Regal’’ Yogini Chudasama – ‘Secrets to Living Longer’ Eleni Ganiti – ‘Contemporary Art?’ Emily Richardson – ‘Cellular Fireworks’ Seth O'Neill – ‘Achille's Heat’ Padraig Donnelly – ‘Peering into Jupiter's Atmosphere from Earth’ Colin Hyde – ‘In the midst of life we are in death’ Georgina Lockton – ‘Researching Vehicle Automation in 1960s Britain’ Jan Oliver Ringert and José Miguel Rojas – ‘DriverLeics’ Amy Van Allen – ‘Life in the Andes’ Eva Krockow – ‘Line Up and Take Note’ Yewande Okuleye – ‘Hemp Seeds in Safe Hands’
DOI: 10.6084/m9.figshare.7976855
title: Dataset 1 from Detecting genetic interactions using parallel evolution in experimental populations

description: Eukaryotic genomes contain thousands of genes organized into complex and interconnected genetic interaction networks. Most of our understanding of how genetic variation affects these networks comes from quantitative-trait loci mapping and from the systematic analysis of double deletion (or knockdown) mutants, primarily in the yeast <i>Saccharomyces cerevisiae</i>. Evolve and re-sequence experiments are an alternative approach for identifying novel functional variants and genetic interactions, particularly between non-loss of function mutations. These experiments leverage natural selection to obtain genotypes with functionally important variants and positive genetic interactions. However, no systematic methods for detecting genetic interactions in these data are yet available. Here, we introduce a computational method based on the idea that variants in genes that interact will co-occur in evolved genotypes more often than expected by chance. We apply this method to a previously published yeast experimental evolution dataset. We find that genetic targets of selection are distributed non-uniformly among evolved genotypes, indicating that genetic interactions had a significant effect on evolutionary trajectories. We identify individual gene pairs with a statistically significant genetic interaction score. The strongest interaction is between genes <i>TRK1</i> and <i>PHO84</i>, genes that have not been reported to interact in previous systematic studies. Our work demonstrates that leveraging parallelism in experimental evolution is useful for identifying genetic interactions that have escaped detection by other methods.This article is part of the theme issue ‘Convergent evolution in the genomics era: new insights and directions’.
DOI: 10.6084/m9.figshare.7976855.v1
title: Dataset 1 from Detecting genetic interactions using parallel evolution in experimental populations

description: Eukaryotic genomes contain thousands of genes organized into complex and interconnected genetic interaction networks. Most of our understanding of how genetic variation affects these networks comes from quantitative-trait loci mapping and from the systematic analysis of double deletion (or knockdown) mutants, primarily in the yeast <i>Saccharomyces cerevisiae</i>. Evolve and re-sequence experiments are an alternative approach for identifying novel functional variants and genetic interactions, particularly between non-loss of function mutations. These experiments leverage natural selection to obtain genotypes with functionally important variants and positive genetic interactions. However, no systematic methods for detecting genetic interactions in these data are yet available. Here, we introduce a computational method based on the idea that variants in genes that interact will co-occur in evolved genotypes more often than expected by chance. We apply this method to a previously published yeast experimental evolution dataset. We find that genetic targets of selection are distributed non-uniformly among evolved genotypes, indicating that genetic interactions had a significant effect on evolutionary trajectories. We identify individual gene pairs with a statistically significant genetic interaction score. The strongest interaction is between genes <i>TRK1</i> and <i>PHO84</i>, genes that have not been reported to interact in previous systematic studies. Our work demonstrates that leveraging parallelism in experimental evolution is useful for identifying genetic interactions that have escaped detection by other methods.This article is part of the theme issue ‘Convergent evolution in the genomics era: new insights and directions’.
DOI: 10.6084/m9.figshare.7976777
title: Classifying and analysis of random composites using structural sums feature vector - supplementary material from Classifying and analysis of random composites using structural sums feature vector. 22 October 2018 25 March 2019

description: The package containing the data and the code associated with the paper devoted to the application of the structural sums feature vector in classifying and analysis of random structures.
DOI: 10.6084/m9.figshare.7976777.v1
title: Classifying and analysis of random composites using structural sums feature vector - supplementary material from Classifying and analysis of random composites using structural sums feature vector. 22 October 2018 25 March 2019

description: The package containing the data and the code associated with the paper devoted to the application of the structural sums feature vector in classifying and analysis of random structures.
DOI: 10.6084/m9.figshare.12875226.v1
title: Additional file 2 of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file 2:Genomic nucleotide sequences 8-kb upstream of the translation start site for 5169 pairs of human-mouse orthologs. The genomic nucleotide sequences 8-kb upstream of the translation start site are shown for 5169 pairs of human-mouse orthologs together with the corresponding gene symbols and gene IDs. (ZIP 11 MB)
DOI: 10.6084/m9.figshare.12875232
title: Additional file 4 of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file 4:Alignments of conserved blocks for 5169 human-mouse orthologs with conserved TFBSs. The location and motif information for 386237 TFBSs are displayed in a character-based alignment-embedded layout. Each file name stands for a gene symbol and the file contains the alignments of conserved blocks with TFBS information for the corresponding gene. Each alignment is not interleaved. The graphical alignments with TFBS information for the 5169 human-mouse ortholog pairs are provided in a browsable format at our website http://genet.med.kagawa-u.ac.jp/pub/HMO_5169/List.htm , together with the character-based alignments with TFBSs and raw sequences contained in Additional files 4 and 2 respectively. (ZIP 17 MB)
DOI: 10.6084/m9.figshare.12875232.v1
title: Additional file 4 of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file 4:Alignments of conserved blocks for 5169 human-mouse orthologs with conserved TFBSs. The location and motif information for 386237 TFBSs are displayed in a character-based alignment-embedded layout. Each file name stands for a gene symbol and the file contains the alignments of conserved blocks with TFBS information for the corresponding gene. Each alignment is not interleaved. The graphical alignments with TFBS information for the 5169 human-mouse ortholog pairs are provided in a browsable format at our website http://genet.med.kagawa-u.ac.jp/pub/HMO_5169/List.htm , together with the character-based alignments with TFBSs and raw sequences contained in Additional files 4 and 2 respectively. (ZIP 17 MB)
DOI: 10.6084/m9.figshare.12875235.v1
title: Additional file 5 of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file 5:Transcriptional connection matrix M. The transcriptional targeting of the 82 TFs to the 5169 genes is shown as a matrix M in which Mij = 1 if TF j targets gene i and Mij = 0 in the absence of such targeting. Each TF i is designated with an official gene symbol in a column and each target gene j is designated by an NCBI Entrez Gene ID. (CSV 862 KB)
DOI: 10.6084/m9.figshare.12875250.v3
title: Additional file of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development
DOI: 10.6084/m9.figshare.12875226
title: Additional file 2 of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file 2:Genomic nucleotide sequences 8-kb upstream of the translation start site for 5169 pairs of human-mouse orthologs. The genomic nucleotide sequences 8-kb upstream of the translation start site are shown for 5169 pairs of human-mouse orthologs together with the corresponding gene symbols and gene IDs. (ZIP 11 MB)
DOI: 10.6084/m9.figshare.12875250.v5
title: Additional file of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development
DOI: 10.6084/m9.figshare.12875250.v6
title: Additional file of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development
DOI: 10.6084/m9.figshare.12875235
title: Additional file 5 of Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development

description: Additional file 5:Transcriptional connection matrix M. The transcriptional targeting of the 82 TFs to the 5169 genes is shown as a matrix M in which Mij = 1 if TF j targets gene i and Mij = 0 in the absence of such targeting. Each TF i is designated with an official gene symbol in a column and each target gene j is designated by an NCBI Entrez Gene ID. (CSV 862 KB)
DOI: 10.6084/m9.figshare.12875265
title: Additional file 5 of Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing

description: Additional file 5: FASTA file of the 6 reference sequences. The six reference DNA sequences used in this analysis are found in the corresponding FASTA file. They correspond to the control DNA fragments of type I provided with 454 GS-FLX Titanium sequencing kits. As such, the polymorphism displayed by the sequences corresponds purely to sequencing errors. (FAS 3 KB)
DOI: 10.6084/m9.figshare.12875265.v1
title: Additional file 5 of Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing

description: Additional file 5: FASTA file of the 6 reference sequences. The six reference DNA sequences used in this analysis are found in the corresponding FASTA file. They correspond to the control DNA fragments of type I provided with 454 GS-FLX Titanium sequencing kits. As such, the polymorphism displayed by the sequences corresponds purely to sequencing errors. (FAS 3 KB)
DOI: 10.6084/m9.figshare.12875268.v1
title: Additional file 6 of Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing

description: Additional file 6: Raw data sequences from 454 GS-FLX Titanium sequencing. This file contains three archives, including the raw FASTA files for each sequencing run. (RAR 2 MB)
DOI: 10.6084/m9.figshare.12875280.v6
title: Additional file of Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing

description: Additional file of Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing
DOI: 10.6084/m9.figshare.12875280.v5
title: Additional file of Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing

description: Additional file of Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing
DOI: 10.18112/openneuro.ds002634.v2.0.1
title: Project_larynx
DOI: 10.6084/m9.figshare.12875268
title: Additional file 6 of Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing

description: Additional file 6: Raw data sequences from 454 GS-FLX Titanium sequencing. This file contains three archives, including the raw FASTA files for each sequencing run. (RAR 2 MB)
DOI: 10.17633/rd.brunel.7976567
title: Pressure, flow and vessel diameter measurements in flexible tubes for the determination of local wave speed: impact of reflected waves.

description: Please see the data description file attached: data description_FINAL.pdf<br>This dataset provides the raw data of pressure, flow and vessel diameter measured simultaneously along flexible long tubes. This experiment was designed to investigate the impact of proximity to reflection sites on wave speed, which was calculated using the following techniques; PU-loop, lnDU-loop, PD<sup>2</sup>-loop, QA-loop, sum of the squares and the characteristic impedance. The results have been published in: http://dx.doi.org/10.1016/j.jbiomech.2013.10.007<br><br>
DOI: 10.17633/rd.brunel.7976567.v1
title: Pressure, flow and vessel diameter measurements in flexible tubes for the determination of local wave speed: impact of reflected waves.

description: Please see the data description file attached: data description_FINAL.pdf<br>This dataset provides the raw data of pressure, flow and vessel diameter measured simultaneously along flexible long tubes. This experiment was designed to investigate the impact of proximity to reflection sites on wave speed, which was calculated using the following techniques; PU-loop, lnDU-loop, PD<sup>2</sup>-loop, QA-loop, sum of the squares and the characteristic impedance. The results have been published in: http://dx.doi.org/10.1016/j.jbiomech.2013.10.007<br><br>
DOI: 10.6084/m9.figshare.7976564
title: Supplementary Material for: Genetic Polymorphisms Associated with Idiopathic Short Stature and First-Year Response to Growth Hormone Treatment

description: <b><i>Background/Aims:</i></b> The term idiopathic short stature (ISS) describes short stature of unknown, but likely polygenic, etiology. This study aimed to identify genetic polymorphisms associated with the ISS phenotype, and with growth response to supplemental GH. <b><i>Methods:</i></b> Using a case-control analysis we compared the prevalence of “tall” versus “short” alleles at 52 polymorphic loci (17 in growth-related candidate genes, 35 identified in prior genome-wide association studies of adult height) in 94 children with ISS followed in the Genetics and Neuroendocrinology of Short Stature International Study, versus 143 controls from the Fels Longitudinal Study. <b><i>Results:</i></b> Four variants were nominally associated with ISS using a genotypic model, confirmed by a simultaneous confident inference approach: compared with controls children with ISS had lower odds of “tall” alleles (odds ratio, 95% CI) for <i>GHR</i> (0.52, 0.29–0.96); rs2234693/ESR1 (0.50, 0.25–0.98); rs967417/BMP2 (0.39, 0.17–0.93), and rs4743034/ZNF462 (0.40, 0.18–0.89). Children with ISS also had lower odds of the “tall” allele (A) at the <i>IGFBP3</i> –202 promoter polymorphism (rs2855744; 0.40, 0.20–0.80) in the simultaneous confident inference analysis. A significant association with 1st-year height SD score increase during GH treatment was observed with rs11205277, located near 4 known genes: <i>MTMR11</i>,<i> SV2A</i>,<i> HIST2H2AA3</i>,<i></i> and<i> SF3B4</i>; the latter, in which heterozygous mutations occur in Nager acrofacial dysostosis, appears the most relevant gene. <b><i>Conclusions:</i></b> In children with ISS we identified associations with “short” alleles at a number of height-related loci. In addition, a polymorphic variant located near <i>SF3B4</i> was associated with the GH treatment response in our cohort. The findings in our small study warrant further investigation.
DOI: 10.6084/m9.figshare.7976564.v1
title: Supplementary Material for: Genetic Polymorphisms Associated with Idiopathic Short Stature and First-Year Response to Growth Hormone Treatment

description: <b><i>Background/Aims:</i></b> The term idiopathic short stature (ISS) describes short stature of unknown, but likely polygenic, etiology. This study aimed to identify genetic polymorphisms associated with the ISS phenotype, and with growth response to supplemental GH. <b><i>Methods:</i></b> Using a case-control analysis we compared the prevalence of “tall” versus “short” alleles at 52 polymorphic loci (17 in growth-related candidate genes, 35 identified in prior genome-wide association studies of adult height) in 94 children with ISS followed in the Genetics and Neuroendocrinology of Short Stature International Study, versus 143 controls from the Fels Longitudinal Study. <b><i>Results:</i></b> Four variants were nominally associated with ISS using a genotypic model, confirmed by a simultaneous confident inference approach: compared with controls children with ISS had lower odds of “tall” alleles (odds ratio, 95% CI) for <i>GHR</i> (0.52, 0.29–0.96); rs2234693/ESR1 (0.50, 0.25–0.98); rs967417/BMP2 (0.39, 0.17–0.93), and rs4743034/ZNF462 (0.40, 0.18–0.89). Children with ISS also had lower odds of the “tall” allele (A) at the <i>IGFBP3</i> –202 promoter polymorphism (rs2855744; 0.40, 0.20–0.80) in the simultaneous confident inference analysis. A significant association with 1st-year height SD score increase during GH treatment was observed with rs11205277, located near 4 known genes: <i>MTMR11</i>,<i> SV2A</i>,<i> HIST2H2AA3</i>,<i></i> and<i> SF3B4</i>; the latter, in which heterozygous mutations occur in Nager acrofacial dysostosis, appears the most relevant gene. <b><i>Conclusions:</i></b> In children with ISS we identified associations with “short” alleles at a number of height-related loci. In addition, a polymorphic variant located near <i>SF3B4</i> was associated with the GH treatment response in our cohort. The findings in our small study warrant further investigation.
DOI: 10.6084/m9.figshare.7976528
title: mass spectrometry, ELISA, western blotting and immunoassay data

description: Supplement Table 1: list of proteins co-precipitated with TRKB.Supplement Table 2: list of interactions disrupted by fluoxetine.figure 1: in vivo WB/ELISA, CABS docking, AP2M:peptide ELISAfigure 2: in vitro/vivo WB/ELISA, surface TRKBfigure 3: in vitro/ex vivo ELISA, validation with siAP2Mfigure 4: in vitro ELISA/immunostaininganti TRKB validation: lysates from MG87 cells expressing TRKA or TRKB.
DOI: 10.6084/m9.figshare.7976528.v1
title: mass spectrometry data

description: Table 1: list of proteins co-precipitated with TRKB.Table 2: list of interactions disrupted by fluoxetine.
DOI: 10.6084/m9.figshare.7976528.v2
title: mass spectrometry, ELISA, western blotting and immunoassay data

description: Table 1: list of proteins co-precipitated with TRKB.Table 2: list of interactions disrupted by fluoxetine.figure 1: in vivo WB/ELISA, CABS docking, AP2M:peptide ELISAfigure 2: in vitro/vivo WB/ELISA, surface TRKBfigure 3: in vitro/ex vivo ELISAfigure 4: in vitro ELISA/immunostaining
DOI: 10.6084/m9.figshare.12875316.v4
title: Additional file of Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources

description: Additional file of Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources
DOI: 10.6084/m9.figshare.12875316.v3
title: Additional file of Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources

description: Additional file of Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources
DOI: 10.6084/m9.figshare.12875289.v1
title: Additional file 1 of Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources

description: Additional file 1:Lists of affected genes during different responses to mastitis infection. Complete lists of affected genes and corresponding "Combined Effective Significances (CES)" identified with pointillist for the 4 main responses to mastitis (I) overall response, (II) early stage response, (III) late stage response, (IV) cattle-specific response, as well as the two additional time dependent responses (V) early specific and (VI) late specific. (XLS 268 KB)
DOI: 10.6084/m9.figshare.12875292
title: Additional file 2 of Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources

description: Additional file 2:Lists of all affected canonical pathways and corresponding affected genes. Complete lists of affected canonical pathways (p &lt; 0.05) and corresponding affected genes identified with IPA for the meta-analysis combinations (I) overall response, (II) early stage response, (III) late stage response, (IV) cattle-specific response, (V) early specific response and (VI) late specific response, as well as for the common affected genes between the 4 meta-analysis responses (I) to (IV) (Figure 3, n = 92). The identified canonical pathways are listed from the lowest to the highest p-value. An asterisk indicates that the pathway approached statistical significance (0.05