cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25345/c58p5vd5x
title: MassIVE MSV000089477 - pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level enabling the functional exploration of site-specific glycosylation
title: Interpreting large-scale glycoproteomic data for intact glycopeptide identification has been tremendously advanced by software tools. However, software tools for quantitative analysis of intact glycopeptides remain lagging behind, which greatly hinders exploring the differential expression and functions of site-specific glycosylation in organisms. Here, we report pGlycoQuant, a generic software tool for quantitative intact glycopeptide analysis, supporting both primary and tandem mass spectrometry quantitation for multiple quantitative strategies. pGlycoQuant advances in glycopeptide evidence matching through applying a deep learning model that reduces missing values for glycopeptide quantification by over 60% compared with Byologic, MSFragger-Glyco and Skyline, as well as an optional function of Match-In-Run (MIR) algorithm for more quantitative coverage of glycopeptides, thus greatly expanding the quantitative function of several powerful search engines, currently including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. The pGlycoQuant-based site-specific N-glycoproteomic study conducted here quantifies 6435 intact N-glycopeptides in three hepatocellular carcinoma cell lines with different metastatic potentials and, together with in vitro molecular biology experiments, illustrates core fucosylation at site 979 of the L1 cell adhesion molecule (L1CAM) as a potential regulator of HCC metastasis. pGlycoQuant is freely available at https://github.com/Power-Quant/pGlycoQuant/releases. We have demonstrated pGlycoQuant to be a powerful tool for the quantitative analysis of site-specific glycosylation and the exploration of potential glycosylation-related biomarker candidates, and we expect further applications in glycoproteomic studies.
DOI: 10.25451/flinders.19770379.v1
title: Bacillus carbohydrate metabolism Protvec model

description: Protvec model trained using 8,743 sequences from the Genome Taxonomy Database (GTDB). Sequenbces were filtered to remove sequences containing 'X', sequences shorter than 30 amino acids and sequences longer than 1024 amino acids. <br> Training used a vector size of 100 and a context size of 25.
DOI: 10.6084/m9.figshare.19769146
title: raw data.zip

description: raw data for some of the images included in the article
DOI: 10.6084/m9.figshare.19769146.v2
title: raw data.zip

description: raw data for some of the images included in the article
DOI: 10.6084/m9.figshare.19769146.v1
title: raw data.zip

description: raw data for some of the images included in the article
DOI: 10.6084/m9.figshare.19770970
title: Untitled IteSilicon accumulation suppresses arbuscular mycorrhizal fungal colonisation in the model grass Brachypodium distachyon m

description: Dataset for the paper: <strong>Silicon accumulation suppresses arbuscular mycorrhizal fungal colonisation in the model grass </strong><em><strong>Brachypodium distachyon</strong></em><strong> </strong>
DOI: 10.6084/m9.figshare.19770970.v1
title: Untitled IteSilicon accumulation suppresses arbuscular mycorrhizal fungal colonisation in the model grass Brachypodium distachyon m

description: Dataset for the paper: <strong>Silicon accumulation suppresses arbuscular mycorrhizal fungal colonisation in the model grass </strong><em><strong>Brachypodium distachyon</strong></em><strong> </strong>
DOI: 10.34740/kaggle/dsv/3108403
title: Fitbit Fitness Data
DOI: 10.6084/m9.figshare.19770994
title: Data Availability Statement.xlsx

description: Phenology and phyllochron of seven strawberry cultivars grown in substrate and greenhouse in the Brazilian subtropics
DOI: 10.6084/m9.figshare.19770994.v1
title: Data Availability Statement.xlsx

description: Phenology and phyllochron of seven strawberry cultivars grown in substrate and greenhouse in the Brazilian subtropics
DOI: 10.6084/m9.figshare.14958030
title: Fig2_retro_cells

description: Fig. 2d,e,j,i <br>
DOI: 10.6084/m9.figshare.14958030.v1
title: Fig2_retro_cells

description: Fig. 2d,e,j,i <br>
DOI: 10.6084/m9.figshare.14958027
title: Fig2_ccmatrix

description: Fig. 2b,c,f,g
DOI: 10.6084/m9.figshare.14958027.v1
title: Fig2_ccmatrix

description: Fig. 2b,c,f,g
DOI: 10.6084/m9.figshare.14958021
title: Fig1_ccmatrix

description: Fig. 1f-i <br>
DOI: 10.6084/m9.figshare.14958021.v1
title: Fig1_ccmatrix

description: Fig. 1f-i <br>
DOI: 10.14457/cu.the.2000.486
title: Effect of compatibilizers on the mechanical properties of HDPE/starch blends
DOI: 10.14457/cu.the.2000.487
title: Effect of external silane donors on Ziegler-Natta catalyst for polymerization of propylene
DOI: 10.14457/cu.the.2000.488
title: Effect of triblock copolymer on drop breakup and coalescence of immiscible blends
DOI: 10.14457/cu.the.2000.489
title: Process evaluation of implementation in accordance with the model for diabetes mellitus prevention and control in Yasothon province
DOI: 10.6084/m9.figshare.19767658
title: Source data for "Molecular Basis and Role of Siglec-7 Ligand Expression on Chronic Lymphocytic Leukemia B Cells" (doi: 10.3389/fimmu.2022.840388)

description: Source data for "Molecular Basis and Role of Siglec-7 Ligand Expression on Chronic Lymphocytic Leukemia B Cells" (doi: 10.3389/fimmu.2022.840388)
DOI: 10.6084/m9.figshare.19767658.v1
title: Source data for "Molecular Basis and Role of Siglec-7 Ligand Expression on Chronic Lymphocytic Leukemia B Cells" (doi: 10.3389/fimmu.2022.840388)

description: Source data for "Molecular Basis and Role of Siglec-7 Ligand Expression on Chronic Lymphocytic Leukemia B Cells" (doi: 10.3389/fimmu.2022.840388)
DOI: 10.5281/zenodo.6534147
title: A benchmark dataset of diurnal- and seasonal-scale radiation, heat and CO2 fluxes in a typical East Asian monsoon region

description: A benchmark dataset include 30-min meteorology and eddy flux variables at four sites with two typical surface types (i.e., SX-cropland, DT-cropland, XZ-suburb, and DS-suburb) in the Yangtze River Delta of China.<br> SX-cropland: 15 Jul 2015–24 Apr 2019<br> DT-cropland: 1 Dec 2014–30 Nov 2017<br> XZ-suburb: 27 Mar 2014–22 Jan 2017<br> DS-suburb: 16 Apr 2011–1 Jan 2019
DOI: 10.5281/zenodo.6552257
title: Phase 1 (onsite) data

description: This folder refers to my thesis entitled "Crossmodal correspondences: different modes, common codes? Investigating musical engagement with an Ecological cognitive approach."
DOI: 10.5281/zenodo.6534146
title: A benchmark dataset of diurnal- and seasonal-scale radiation, heat and CO2 fluxes in a typical East Asian monsoon region

description: A benchmark dataset include 30-min meteorology and eddy flux variables at four sites with two typical surface types (i.e., SX-cropland, DT-cropland, XZ-suburb, and DS-suburb) in the Yangtze River Delta of China.<br> SX-cropland: 15 Jul 2015–24 Apr 2019<br> DT-cropland: 1 Dec 2014–30 Nov 2017<br> XZ-suburb: 27 Mar 2014–22 Jan 2017<br> DS-suburb: 16 Apr 2011–1 Jan 2019
DOI: 10.6084/m9.figshare.19581643
title: The relationship between cost and the recommendation, refusal, and discontinuation of treatment for chronic myeloid leukemia and multiple myeloma in Japan: a cross-sectional exploratory survey

description: This study aimed to ascertain the number of patients with chronic myelogenous leukemia (CML) and transplant-ineligible patients with multiple myeloma (MM) not recommended by their physicians for optimal drug treatment or who refuse, discontinue, reduce, or skip treatment owing to cost in Japan. A cross-sectional survey was conducted among hematologists, hematologic oncologists, and oncologists in Japan treating ≥1 patient with CML or ≥5 transplant-ineligible patients with MM per year. A total of 212 physicians participated: 105 treating patients with CML and 107 treating transplant-ineligible patients with MM. While treatment cost did not lead to non-optimal treatment most patients, physicians reported that they recommended non-optimal treatment to 6.53% of their patients with CML and 1.41% of their transplant-ineligible patients with MM, that 1.51 and 0.35% of their patients, respectively, refused treatment and that 1.97 and 0.71% discontinued treatment owing to treatment cost. However, no significant differences in the effect of treatment cost on recommendation, discontinuation, refusal, or reduction of treatment were observed. Non-recommendation of optimal treatment owing to treatment cost was most common for third-line CML and fourth-line transplant-ineligible MM treatment. Discontinuation due to treatment cost was most common in third-line treatment for both. Our results show that non-optimal treatment due to treatment cost occurs among some physicians in Japan for patients with CML and transplant-ineligible patients with MM, but it may be limited to a small percentage of patients. Further research is needed to identify the drivers of treatment decisions for physicians and patients, including those involving treatment cost.
DOI: 10.6084/m9.figshare.19581643.v1
title: The relationship between cost and the recommendation, refusal, and discontinuation of treatment for chronic myeloid leukemia and multiple myeloma in Japan: a cross-sectional exploratory survey

description: This study aimed to ascertain the number of patients with chronic myelogenous leukemia (CML) and transplant-ineligible patients with multiple myeloma (MM) not recommended by their physicians for optimal drug treatment or who refuse, discontinue, reduce, or skip treatment owing to cost in Japan. A cross-sectional survey was conducted among hematologists, hematologic oncologists, and oncologists in Japan treating ≥1 patient with CML or ≥5 transplant-ineligible patients with MM per year. A total of 212 physicians participated: 105 treating patients with CML and 107 treating transplant-ineligible patients with MM. While treatment cost did not lead to non-optimal treatment most patients, physicians reported that they recommended non-optimal treatment to 6.53% of their patients with CML and 1.41% of their transplant-ineligible patients with MM, that 1.51 and 0.35% of their patients, respectively, refused treatment and that 1.97 and 0.71% discontinued treatment owing to treatment cost. However, no significant differences in the effect of treatment cost on recommendation, discontinuation, refusal, or reduction of treatment were observed. Non-recommendation of optimal treatment owing to treatment cost was most common for third-line CML and fourth-line transplant-ineligible MM treatment. Discontinuation due to treatment cost was most common in third-line treatment for both. Our results show that non-optimal treatment due to treatment cost occurs among some physicians in Japan for patients with CML and transplant-ineligible patients with MM, but it may be limited to a small percentage of patients. Further research is needed to identify the drivers of treatment decisions for physicians and patients, including those involving treatment cost.
DOI: 10.6084/m9.figshare.19692012.v1
title: Table S2 from Phagocytosis of exogenous bacteria by gill epithelial cells in the deep-sea symbiotic mussel <i>Bathymodiolus japonicus</i>

description: Proportion of gill cells with internalised fluorescence-labelled bacteria among the examined cells.
DOI: 10.6084/m9.figshare.19692012
title: Table S2 from Phagocytosis of exogenous bacteria by gill epithelial cells in the deep-sea symbiotic mussel <i>Bathymodiolus japonicus</i>

description: Proportion of gill cells with internalised fluorescence-labelled bacteria among the examined cells.
DOI: 10.6084/m9.figshare.19692015
title: Table S1 from Phagocytosis of exogenous bacteria by gill epithelial cells in the deep-sea symbiotic mussel <i>Bathymodiolus japonicus</i>

description: nternalized bacterial cell densities (mean number per cm2) of live Escherichia coli (LEc) and dead Vibrio tubiashii (DVt) in gill cells and haemocytes in the mantle haemocoel after 24 h of bacterial exposure experiments.
DOI: 10.6084/m9.figshare.19692015.v1
title: Table S1 from Phagocytosis of exogenous bacteria by gill epithelial cells in the deep-sea symbiotic mussel <i>Bathymodiolus japonicus</i>

description: nternalized bacterial cell densities (mean number per cm2) of live Escherichia coli (LEc) and dead Vibrio tubiashii (DVt) in gill cells and haemocytes in the mantle haemocoel after 24 h of bacterial exposure experiments.
DOI: 10.6084/m9.figshare.19692018
title: Table S3 from Phagocytosis of exogenous bacteria by gill epithelial cells in the deep-sea symbiotic mussel <i>Bathymodiolus japonicus</i>

description: Number of internalised Alexa Fluor® 488-conjugated Escherichia coli (AEc) and AEcs within acidified vacuoles in one mm3 of a gill piece after incubation for 0, 2, 12, and 24 h.
DOI: 10.6084/m9.figshare.19692018.v1
title: Table S3 from Phagocytosis of exogenous bacteria by gill epithelial cells in the deep-sea symbiotic mussel <i>Bathymodiolus japonicus</i>

description: Number of internalised Alexa Fluor® 488-conjugated Escherichia coli (AEc) and AEcs within acidified vacuoles in one mm3 of a gill piece after incubation for 0, 2, 12, and 24 h.
DOI: 10.6084/m9.figshare.14945095
title: Additional file 1 of Genome wide association study of agronomic and seed traits in a world collection of proso millet (Panicum miliaceum L.)

description: Additional file 1: Supplementary Table 1. Summary of accessions used in this study. The table reports the sample name, the type of material and geographic information on its origin. Accession ID and name report the international identifiers of the sample as reported in the USDA passport information. Supplementary Table 2. Overview of RAD sequencing data produced and alignment to the reference sequence. For each sample, the table reports the total amount of reads passing the quality threshold, the total amount of reads mapped on the genome, and the ratio of the two. Supplementary Table 3. GWAS Summary data. For each SNP, the table reports the chromosome and position on the reference genome. For each trait-SNP combination, the table reports the p-value of the association and estimated effect. Trait names are coded as in the main text.
DOI: 10.6084/m9.figshare.14945095.v1
title: Additional file 1 of Genome wide association study of agronomic and seed traits in a world collection of proso millet (Panicum miliaceum L.)

description: Additional file 1: Supplementary Table 1. Summary of accessions used in this study. The table reports the sample name, the type of material and geographic information on its origin. Accession ID and name report the international identifiers of the sample as reported in the USDA passport information. Supplementary Table 2. Overview of RAD sequencing data produced and alignment to the reference sequence. For each sample, the table reports the total amount of reads passing the quality threshold, the total amount of reads mapped on the genome, and the ratio of the two. Supplementary Table 3. GWAS Summary data. For each SNP, the table reports the chromosome and position on the reference genome. For each trait-SNP combination, the table reports the p-value of the association and estimated effect. Trait names are coded as in the main text.
DOI: 10.6084/m9.figshare.14945098.v1
title: Additional file 2 of Genome wide association study of agronomic and seed traits in a world collection of proso millet (Panicum miliaceum L.)

description: Additional file 2: Supplementary Figure S1. Representative photos for proso millet seeds color classes characterized in this study. Supplementary Figure S2. Boxplots of seed trait distribution across geographical regions. Differences were analyzed using ANOVA. Supplementary Figure S3. Phenotypic and molecular analysis of proso millet accessions. (A) Principal component analysis of phenotypic diversity of seed traits and agronomic traits. (B) Phylogenetic tree derived from SNPs data. (C) Principal component analysis derived from SNPs data. Different symbols indicate type of genetic materials as shown in the legend. Supplementary Figure S4. Phenotypic diversity in the collection as reported by PC1, PC2, and PC3. Different colors on and symbols on the panels indicate region of origin and type of genetic materials as in Fig. 2 and Supplementary Figure S3. Supplementary Figure S5. PCA scores and vectors loadings for seed and agronomic traits. Percent of variance explained by each axis (PC1 = Dim1, PC2 = Dim2) is indicated in the axis titles. Vector color represents the total contribution of a given variable on the first two dimensions according to legend to the right. Supplementary Figure S6. Genotypic diversity in the collection as reported by PC1, PC2, and PCA3. Different colors on and symbols on the panels indicate region of origin and type of genetic materials as in Fig. 2 and Supplementary Figure S3. Supplementary Figure S7. Manhattan plots for GWAS on seed trait and agronomic traits. The plot shows individual SNPs across all chromosomes (x-axis) and -log10 P value of each SNP association (y-axis). The different colors indicate the 18 chromosomes of proso millet. The horizontal line shows the multiple testing threshold according to a stringent Bonferroni method. Note that different Manhattan plots are reported to different y-axis scales corresponding to the highest significance for each GWAS. Supplementary Figure S8. Quantile–Quantile (Q–Q) plots for FarmCPU model showing distribution of estimated versus observed -log10 (P) values for seed trait and agronomic traits.
DOI: 10.6084/m9.figshare.14945098
title: Additional file 2 of Genome wide association study of agronomic and seed traits in a world collection of proso millet (Panicum miliaceum L.)

description: Additional file 2: Supplementary Figure S1. Representative photos for proso millet seeds color classes characterized in this study. Supplementary Figure S2. Boxplots of seed trait distribution across geographical regions. Differences were analyzed using ANOVA. Supplementary Figure S3. Phenotypic and molecular analysis of proso millet accessions. (A) Principal component analysis of phenotypic diversity of seed traits and agronomic traits. (B) Phylogenetic tree derived from SNPs data. (C) Principal component analysis derived from SNPs data. Different symbols indicate type of genetic materials as shown in the legend. Supplementary Figure S4. Phenotypic diversity in the collection as reported by PC1, PC2, and PC3. Different colors on and symbols on the panels indicate region of origin and type of genetic materials as in Fig. 2 and Supplementary Figure S3. Supplementary Figure S5. PCA scores and vectors loadings for seed and agronomic traits. Percent of variance explained by each axis (PC1 = Dim1, PC2 = Dim2) is indicated in the axis titles. Vector color represents the total contribution of a given variable on the first two dimensions according to legend to the right. Supplementary Figure S6. Genotypic diversity in the collection as reported by PC1, PC2, and PCA3. Different colors on and symbols on the panels indicate region of origin and type of genetic materials as in Fig. 2 and Supplementary Figure S3. Supplementary Figure S7. Manhattan plots for GWAS on seed trait and agronomic traits. The plot shows individual SNPs across all chromosomes (x-axis) and -log10 P value of each SNP association (y-axis). The different colors indicate the 18 chromosomes of proso millet. The horizontal line shows the multiple testing threshold according to a stringent Bonferroni method. Note that different Manhattan plots are reported to different y-axis scales corresponding to the highest significance for each GWAS. Supplementary Figure S8. Quantile–Quantile (Q–Q) plots for FarmCPU model showing distribution of estimated versus observed -log10 (P) values for seed trait and agronomic traits.
DOI: 10.34808/06bs-9e90
title: AITP - AI Thermal Pedestrians Dataset

description: AITP is a pedestrian detection dataset consisting of 9178 annotated thermal images. The training set contains 7801 images on which15448 pedestrians were labeled.  The test set has 1377 images on which 2731 objects were marked. All images are in PNG file format (120x160) captured with FLIR Lepton Thermal Camera on the streets of Gdańsk, Poland. All pedestrians were manually annotated. Annotations are stored in PASCAL and YOLO formats.
DOI: 10.34740/kaggle/dsv/3643627
title: Russian Invasion of Ukraine
DOI: 10.6084/m9.figshare.19180667
title: Supplementary Material for: Genetic Analyses of Enamel Hypoplasia in Multiethnic Cohorts

description: Enamel hypoplasia causes reduction in the thickness of affected enamel and is one of the most common dental anomalies. This defect is caused by environmental and/or genetic factors that interfere with tooth formation, emphasizing the importance of investigating enamel hypoplasia on an epidemiological and genetic level. A genome-wide association of enamel hypoplasia was performed in multiple cohorts, overall comprising 7,159 individuals ranging in age from 7-82 years. Mixed-models were used to test for genetic association while simultaneously accounting for relatedness and genetic population structure. Meta-analysis was then performed. More than 5 million single-nucleotide polymorphisms were tested in individual cohorts. Analyses of the individual cohorts and meta-analysis identified association signals close to genome-wide significance (P &lt; 510-8), and many suggestive association signals (510-8 &lt; P &lt; 510-6) near genes with plausible roles in tooth/enamel development. The strongest association signal (P = 1.5710-9) was observed near BMP2K in one of the individual cohorts. Additional suggestive signals were observed near genes with plausible roles in tooth development in the meta-analysis, such as SLC4A4 which can influence enamel hypoplasia. Additional human genetic studies are needed to replicate these results and functional studies in model systems are needed to validate our findings.
DOI: 10.5281/zenodo.6546492
title: Dataset for Dynamic Analysis of Quantum Annealing Programs

description: Quantum software engineering is emerging as a relevant field as it deals with the challenges of producing the new quantum software, whose adoption is increasing progressively. One of those challenges is how quantum software is migrated, how it operates in combination with classical software, or how it should be maintained. In this context this research focuses on reverse engineering of quantum annealing software to facilitates its integration in hybrid software systems. Quantum annealing software has gained a certain market penetration, demonstrating a good performance for optimization problems. While there are some preliminary reverse engineering techniques for gate-based quantum software, there is no reverse engineering techniques to discover the underlying optimization problem definitions (Hamiltonians functions to be minimized). Problem definitions are, in turn, dynamically defined through classical software, and can evolve over time, which make it difficult its accurate comprehension and abstract representation. Thereby, this paper presents a dynamic analysis technique for D-Wave (python) programs for reversing Hamiltonians expressions, that are additionally represented according to the Knowledge Discovery Metamodel. Due to the usage of this standard, the reversed Hamiltonians can be represented in combination with other parts of classical-quantum software systems. In order to facilitates its adoption, the proposed technique has been empirically validated through a case study with 27 D-Wave programs that demonstrates the effectiveness and efficiency. This dataset includes measures derived from that case study.