cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12109716
title: Additional file 5 of Comparative transcriptomic analysis of global gene expression mediated by (p) ppGpp reveals common regulatory networks in Pseudomonas syringae

description: Additional file 5: Table S8. List of differentially expressed genes (DEGs) related to type III secretion system (T3SS) and type VI secretion system (T6SS). Table S9. List of DEGs related to cell motility, division, and exopolysaccharides (EPS). Table S10. List of DEGs related to DNA replication, RNA processes and ribosomal protein biosynthesis. Table S11. List of DEGs related to nucleotide, amino acid and fatty acid metabolism. Table S12. List of DEGs related to coenzyme and carbon metabolism. Table S13. List of DEGs related to signal transduction and transcription.
DOI: 10.6084/m9.figshare.12109566
title: Additional file 2 of From pairs of most similar sequences to phylogenetic best matches

description: Additional file 2. This archive contains the simulated data set comprising 2000 species and gene tree scenarios (trees.zip), the current version of the AsymmeTree package (v0.0.5) for the simulation of such weighted scenarios. Moreover, the Python scripts for the generation and analysis of sequence data are supplied (see README.txt for more details).
DOI: 10.6084/m9.figshare.12109566.v1
title: Additional file 2 of From pairs of most similar sequences to phylogenetic best matches

description: Additional file 2. This archive contains the simulated data set comprising 2000 species and gene tree scenarios (trees.zip), the current version of the AsymmeTree package (v0.0.5) for the simulation of such weighted scenarios. Moreover, the Python scripts for the generation and analysis of sequence data are supplied (see README.txt for more details).
DOI: 10.6084/m9.figshare.16305597.v1
title: Additional file 1 of Cirbp-PSD95 axis protects against hypobaric hypoxia-induced aberrant morphology of hippocampal dendritic spines and cognitive deficits

description: Additional file 1. Raw data used for quantified analyses of Figure 1–6.
DOI: 10.6084/m9.figshare.12113898
title: Processed_Datasets.zip

description: Processed Datasets associated with the study entitled "Expression based biomarkers and models to classify early and late stage samples of Papillary Thyroid Carcinoma"<b><i></i></b><br>
DOI: 10.6084/m9.figshare.23648265
title: Phenotypic characteristics and genetic diversity of new broccoli (Brassica oleracea var. italica Plenck) varieties in China

description: ABSTRACT Due to its high nutritional value, broccoli (Brassica oleracea var. italica Plenck) is one of the most popular vegetables worldwide. This study assessed 36 phenotypic characteristics of 111 broccoli varieties to understand the phenotypic diversity of new broccoli varieties and improve their breeding speed with advantages and characteristics in China, including 108 new varieties and three varieties of common knowledge. The genetic diversity, the principal component, and the cluster of phenotypic characteristics of broccoli varieties were further investigated. The results showed that the coefficients of variation of 36 characteristics ranged between 11.18 % and 94.99 %, with their diversity index between 0.26 and 1.82. The 111 broccoli varieties were further classified into eight groups, primarily attributed to the differences in phenotypic characteristics, including curd weight, main stem thickness, plant development degree, plant height, and anthocyanin coloration. The cumulative contribution rate of the first five principal components reached 81.186 %, corresponding to 12 representative phenotypic traits. The analysis indicated that the phenotypic characteristics of broccoli were rich in diversity, especially for several characteristics appreciated by the market, such as weight, curd firmness, and anthocyanin coloration. This study revealed the basic information on the genetic diversity of new broccoli varieties in China from 2017 to 2019 and provided potential breeding strategies for broccoli to meet diverse market demands.
DOI: 10.6084/m9.figshare.23648265.v1
title: Phenotypic characteristics and genetic diversity of new broccoli (Brassica oleracea var. italica Plenck) varieties in China

description: ABSTRACT Due to its high nutritional value, broccoli (Brassica oleracea var. italica Plenck) is one of the most popular vegetables worldwide. This study assessed 36 phenotypic characteristics of 111 broccoli varieties to understand the phenotypic diversity of new broccoli varieties and improve their breeding speed with advantages and characteristics in China, including 108 new varieties and three varieties of common knowledge. The genetic diversity, the principal component, and the cluster of phenotypic characteristics of broccoli varieties were further investigated. The results showed that the coefficients of variation of 36 characteristics ranged between 11.18 % and 94.99 %, with their diversity index between 0.26 and 1.82. The 111 broccoli varieties were further classified into eight groups, primarily attributed to the differences in phenotypic characteristics, including curd weight, main stem thickness, plant development degree, plant height, and anthocyanin coloration. The cumulative contribution rate of the first five principal components reached 81.186 %, corresponding to 12 representative phenotypic traits. The analysis indicated that the phenotypic characteristics of broccoli were rich in diversity, especially for several characteristics appreciated by the market, such as weight, curd firmness, and anthocyanin coloration. This study revealed the basic information on the genetic diversity of new broccoli varieties in China from 2017 to 2019 and provided potential breeding strategies for broccoli to meet diverse market demands.
DOI: 10.6084/m9.figshare.19451436.v1
title: Additional file 13 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 13: Table S19. RT-qPCR primer sequences of TSGs in the current study.
DOI: 10.6084/m9.figshare.19451448.v1
title: Additional file 1 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 1: Table S1. Sample information and classification of tissue samples from beef cattle in this study. Table S2. The summary of raw reads, clean reads and the total mapped read rate. Table S3. Assemble the transcript statistics of each sample with the merged transcripts file. Table S4. Comparing the transcript assembly with reference annotation. Table S5. The relationship between the predicted transcript and reference annotated files.
DOI: 10.6084/m9.figshare.19451430.v1
title: Additional file 11 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 11: Table S14. Tissue-specific module transcription factor analysis. Table S15. Cross-species conservation of HKGs, TSGs, HUBGs and full genes set. Table S16. The expression level of cattle full genes set, HKGs, TSGs and HUBGs in mammals. Table S17. Identification of DEGs between beef and dairy cattle. Table S18. Functional annotation (for Top10) and pathway enrichment (for Top10) analysis of DEGs identified in six tissues between beef and dairy cattle.
DOI: 10.6084/m9.figshare.19451407.v1
title: Additional file 1 of Diagnostic performance of the metagenomic next-generation sequencing in lung biopsy tissues in patients suspected of having a local pulmonary infection

description: Additional file 1. Details about 76 cases diagnosed with a pulmonary infectious disease.
DOI: 10.6084/m9.figshare.12109701
title: Additional file 3 of Comparative transcriptomic analysis of global gene expression mediated by (p) ppGpp reveals common regulatory networks in Pseudomonas syringae

description: Additional file 3: Table S3. List of homologues and unique genes via comparative analysis of PstDC3000 and PssB728a genomes. Table S4. List of homologues genes in both PstDC3000 and PssB728a regulated by (p) ppGpp in a similar way. Table S5. List of homologues genes in both PstDC3000 and PssB728a inversely regulated by (p)ppGpp.
DOI: 10.6084/m9.figshare.19451407
title: Additional file 1 of Diagnostic performance of the metagenomic next-generation sequencing in lung biopsy tissues in patients suspected of having a local pulmonary infection

description: Additional file 1. Details about 76 cases diagnosed with a pulmonary infectious disease.
DOI: 10.6084/m9.figshare.12109701.v1
title: Additional file 3 of Comparative transcriptomic analysis of global gene expression mediated by (p) ppGpp reveals common regulatory networks in Pseudomonas syringae

description: Additional file 3: Table S3. List of homologues and unique genes via comparative analysis of PstDC3000 and PssB728a genomes. Table S4. List of homologues genes in both PstDC3000 and PssB728a regulated by (p) ppGpp in a similar way. Table S5. List of homologues genes in both PstDC3000 and PssB728a inversely regulated by (p)ppGpp.
DOI: 10.6084/m9.figshare.19451448
title: Additional file 1 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 1: Table S1. Sample information and classification of tissue samples from beef cattle in this study. Table S2. The summary of raw reads, clean reads and the total mapped read rate. Table S3. Assemble the transcript statistics of each sample with the merged transcripts file. Table S4. Comparing the transcript assembly with reference annotation. Table S5. The relationship between the predicted transcript and reference annotated files.
DOI: 10.6084/m9.figshare.19451436
title: Additional file 13 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 13: Table S19. RT-qPCR primer sequences of TSGs in the current study.
DOI: 10.6084/m9.figshare.19451454.v1
title: Additional file 3 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 3: Table S6. The expression levels of 32 HKGs across 51 tissues.
DOI: 10.6084/m9.figshare.19451442
title: Additional file 15 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 15: Table S20. Summary of shared TSG identified in this study and previous studies.
DOI: 10.6084/m9.figshare.19451460.v1
title: Additional file 5 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 5: Table S7. Tissue specific genes (TSGs) and tissue-specific transcripts (TSTs) identified based on stringent criteria.
DOI: 10.6084/m9.figshare.19451472.v1
title: Additional file 9 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 9: Table S9. The identified functional modules using dynamic cutting method. Table S10. Tissue-specific modules detection and hub genes screening. Table S11. Tissue-specific module gene function annotation (Top10). Table S12. The intramodular connectivity for con-expression analysis calculated for each gene. Table S13. The identified Hub gene in tissue-specific module (Top5%).
DOI: 10.6084/m9.figshare.19451454
title: Additional file 3 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 3: Table S6. The expression levels of 32 HKGs across 51 tissues.
DOI: 10.6084/m9.figshare.19451466
title: Additional file 7 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 7: Table S8. Tissue specific gene (TSG) function annotation (Top5) and pathway enrichment (Top5).
DOI: 10.6084/m9.figshare.19451430
title: Additional file 11 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 11: Table S14. Tissue-specific module transcription factor analysis. Table S15. Cross-species conservation of HKGs, TSGs, HUBGs and full genes set. Table S16. The expression level of cattle full genes set, HKGs, TSGs and HUBGs in mammals. Table S17. Identification of DEGs between beef and dairy cattle. Table S18. Functional annotation (for Top10) and pathway enrichment (for Top10) analysis of DEGs identified in six tissues between beef and dairy cattle.
DOI: 10.6084/m9.figshare.19451466.v1
title: Additional file 7 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 7: Table S8. Tissue specific gene (TSG) function annotation (Top5) and pathway enrichment (Top5).
DOI: 10.6084/m9.figshare.16829947
title: Additional file 8 of Direct comparisons of efficacy and safety between actinomycin-D and methotrexate in women with low-risk gestational trophoblastic neoplasia: a meta-analysis of randomized and high-quality non-randomized studies

description: Additional file 8: Table S1. Results of Begg’s adjusted rank correlation test and Egger’s test for adverse events.
DOI: 10.6084/m9.figshare.19451460
title: Additional file 5 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 5: Table S7. Tissue specific genes (TSGs) and tissue-specific transcripts (TSTs) identified based on stringent criteria.
DOI: 10.6084/m9.figshare.19451472
title: Additional file 9 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 9: Table S9. The identified functional modules using dynamic cutting method. Table S10. Tissue-specific modules detection and hub genes screening. Table S11. Tissue-specific module gene function annotation (Top10). Table S12. The intramodular connectivity for con-expression analysis calculated for each gene. Table S13. The identified Hub gene in tissue-specific module (Top5%).
DOI: 10.6084/m9.figshare.19451442.v1
title: Additional file 15 of Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

description: Additional file 15: Table S20. Summary of shared TSG identified in this study and previous studies.
DOI: 10.6084/m9.figshare.6679712.v1
title: Additional file 3: of Mapping QTLs for water-use efficiency reveals the potential candidate genes involved in regulating the trait in apple under drought stress

description: Table S2. List of genetic and physical map location of 10,172 SNP markers and their genotyping data among 350Â F1 seedlings. (XLSX 169 kb)
DOI: 10.6084/m9.figshare.12109716.v1
title: Additional file 5 of Comparative transcriptomic analysis of global gene expression mediated by (p) ppGpp reveals common regulatory networks in Pseudomonas syringae

description: Additional file 5: Table S8. List of differentially expressed genes (DEGs) related to type III secretion system (T3SS) and type VI secretion system (T6SS). Table S9. List of DEGs related to cell motility, division, and exopolysaccharides (EPS). Table S10. List of DEGs related to DNA replication, RNA processes and ribosomal protein biosynthesis. Table S11. List of DEGs related to nucleotide, amino acid and fatty acid metabolism. Table S12. List of DEGs related to coenzyme and carbon metabolism. Table S13. List of DEGs related to signal transduction and transcription.
DOI: 10.6084/m9.figshare.19451548.v1
title: Additional file 4 of An integrated omics analysis reveals the gene expression profiles of maize, castor bean, and rapeseed for seed oil biosynthesis

description: Additional file 4:Table S3.Primer sequences for qRT-PCR verification in this study.
DOI: 10.6084/m9.figshare.19451548
title: Additional file 4 of An integrated omics analysis reveals the gene expression profiles of maize, castor bean, and rapeseed for seed oil biosynthesis

description: Additional file 4:Table S3.Primer sequences for qRT-PCR verification in this study.
DOI: 10.6084/m9.figshare.16829993
title: Additional file 3 of Circular RNA NEK6 contributes to the development of non-small-cell lung cancer by competitively binding with miR-382-5p to elevate BCAS2 expression at post-transcriptional level

description: Additional file 3: Table 1. Sequences of primers and reaction condition
DOI: 10.14459/2024mp1734393
title: Research data Management policy for large CRC projects.

description: This research data management policy was created for large Collaborative Research Centres (CRC). Research workloads in such centres are usually distributed in projects and work packages where each workload could be hosted by multiple institutions. And those institutions may geographically be located at distinct locations. While participating researchers come from different domains. In such projects researchers use and generate heterogeneous, large amount of data which ranges from surveys, lab experiments, simulations, data models to software code and hardware design as well as real world objects etc. It is expected that researches comply with modern scientific practices e.g. FAIR principles, Open Science and Reproducibility.
In order to align with highest standards of research and research data management practices this policy document outlines the definition of research data, platform and information infrastructure, roles and responsibilities of the participants, types of research publications, file formats to communicate research outcomes and initial metadata standard etc. Accompanying appendices contain information about data migration, use cases of DMP and workflow for publication. This policy has been implemented for the work of TRR277 AMC (a CRC funded by German Research Council (DFG)) since 2021. The draft version 0.5.0 dated February 25, 2021 is being published in its actual document form.
This policy document contains information relating to AMC specific settings e.g. participants, information infrastructure. It may be adopted by the target groups by altering that information based on their own settings and preferences. Open data/ Open science practices are also assumed in line with the parent and supplementary policies which could be defined and enforced by the stake holders e.g. funding agency, research group/ centre, community, publisher, industry partner etc.
DOI: 10.21947/2287629
title: Meteorological Tower / Raw Data

description: This dataset contains meteorological tower (MET) measurements from Engie.
DOI: 10.21227/qf94-3b65
title: sEMG for gesture recognition

description: They are a combination of 8 finger gestures and 3 wrist gestures. The 8 finger motions include fist, extension of all fingers, extension of thumb finger, extension of index finger, extension of thumb and index finger, extension of little finger, 3-fingers pinch, and 5-fingers pinch . And the 3 wrist motions are wrist extension, wrist flexion and wrist relaxation. 8-channel sEMG and 1-inertial measurement unit (IMU) were recorded by a self-developed device. The sampling frequency of sEMG and inertial signal was 1000Hz. Twenty right-handed healthy subjects (ten males and ten females) between 18 and 30 years of age from Xi’an Jiao-tong University with no neuromuscular disorders, upper limb motor dysfunction and no strenuous exercise within 24 hours participated in the experiment.
DOI: 10.6084/m9.figshare.25158287
title: wos提取.xlsx

description: In this study, the Web of Science (WOS) database was used to analyze 781 research articles about the impact of cultural capital on college students. The quantitative analysis looked at time distribution, author and institution sources, high-frequency keywords, keyword co-occurrence network, and high-frequency keyword clustering. The analysis’ findings indicate that the main research directions in this field are the reproduction and flow of cultural capital against the backdrop of education internationalization, the relationship between the development of college students’ careers and cultural capital, and the connection between the cultural capital of underprivileged classes, ethnic minorities, and special groups and educational equity. Future study in this area may focus heavily on the development of community cultural wealth, which is comprised of many forms of cultural capital, on equity of higher education throughout the course of micro-culture interaction ceremonies.
DOI: 10.6084/m9.figshare.19451458
title: Additional file 2 of The repertoire of testicular extracellular vesicle cargoes and their involvement in inter-compartmental communication associated with spermatogenesis

description: Additional file 2: Table S1. List of proteins identified in testicular EVs.
DOI: 10.6084/m9.figshare.19451458.v1
title: Additional file 2 of The repertoire of testicular extracellular vesicle cargoes and their involvement in inter-compartmental communication associated with spermatogenesis

description: Additional file 2: Table S1. List of proteins identified in testicular EVs.
DOI: 10.6084/m9.figshare.19451464
title: Additional file 4 of The repertoire of testicular extracellular vesicle cargoes and their involvement in inter-compartmental communication associated with spermatogenesis

description: Additional file 4: Table S3. List of small RNAs identified in testicular EVs.
DOI: 10.6084/m9.figshare.19451470.v1
title: Additional file 6 of The repertoire of testicular extracellular vesicle cargoes and their involvement in inter-compartmental communication associated with spermatogenesis

description: Additional file 6: Table S5. Individual data values. Individual data values available of experiments performed where n&lt;6.
DOI: 10.6084/m9.figshare.19451467.v1
title: Additional file 5 of The repertoire of testicular extracellular vesicle cargoes and their involvement in inter-compartmental communication associated with spermatogenesis

description: Additional file 5: Table S4. Oligo information.
DOI: 10.5281/zenodo.15550
title: Md Simulation Trajectory And Related Files For Dppc Bilayer (Gafflipid, Gromacs 4.5)

description: Equilibrated DPPC lipid bilayer simulation ran with Gromacs 4.5, GAFFlipid force field (http://dx.doi.org/10.1039/C2SM26007G), 50ns, T=323K, 72 DPPC molecules, 2197 water molecules. This data is ran for the nmrlipids.blospot.fi project. More details from nmrlipids.blospot.fi and https://github.com/NMRLipids/nmrlipids.blogspot.fi. If data is used, please cite nmrlipids.blogspot.fi project and the original publication of the parameters: Dickson et al. Soft Matter, 2012,8, 9617-9627 http://dx.doi.org/10.1039/C2SM26007G.
DOI: 10.25919/5f1e392541a9e
title: Parkes observations for project P1050 semester 2020APRS_23

description: This is a request for observing time for the initial follow-up of pulsar discoveries from the re-processing of the low-latitude Galactic plane section of the HTRU survey (P630). We have now completed a first pass re-processing of the 60 % of the survey with GPU based coherent acceleration search and template bank search pipelines, and have discovered potential 54 previously unknown pulsars. Interesting science can usually only be derived from a new pulsar after confirmation and a follow-up timing campaign is carried out. One year of initial timing is the minimum timespan required to fully characterise any newly-discovered pulsars, essential for deriving pulsar parameters such as the characteristic age, magnetic field strength, spin-down rate, as well as to detect any unexpected behaviour of the pulsar which might result from emission instabilities. This follow-up and timing project is necessary for following up on any interesting pulsar systems discovered from the HTRU Galactic plane survey. Since all of the pulsars on the observing list here are being followed-up for the first time, they will produce completely new and exciting results. In addition, this timing project will enable a large-scale examination of the Galactic plane pulsar population, exploring the true boundaries of pulsar parameter space.