cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10635517
title: Dimethylsulfoniopropionate-derived compound concentrations, volatile organic compound concentrations, and microorganism abundances over diel cycles in the tropical ocean and in a coral back reef lagoon of Moorea (French Polynesia)

description: These data belong in the paper: 

Marta Masdeu-Navarro, Jean-François Mangot, Lei Xue, Miguel Cabrera-Brufau, DavidJ. Kieber, Pablo Rodríguez-Ros, Stephanie G. Gardner, Kristin Bergauer, Gerhard J. Herndl, Cèlia Marrasé and Rafel Simó (2024). Diel variation of seawater volatile organic compounds, DMSP-related compounds, and microbial plankton inside and outside a tropical coral reef ecosystem. Frontiers in Marine Science.

Concentrations of DMSP, acrylate, DMSO, DMS, DMDS, COS, CS2, isoprene, CH3I, CH2ClI, CH2Br2 and CHBr3 in seawater samples at two sampling sites, one inside (named BR) and one outside (named OO), of the northern coral reef of Mo'orea, French Polynesia. Along with the afore mentioned compounds, the data set contains abundances of heterotrophic prokaryotes, Prochlorococcus, Synechococcus, picoeukaryotes and nanoeukaryotes as determined by flow cytometry, as well as concentrations of nutrients, chlorophyll a, DOC, DON, POC and FDOM. The data set is subdivided into two data sets, one per sampling site, each being composed of a time series of measurements done every 6h over a period of 36h. All samples were collected in April 2018.
DOI: 10.6084/m9.figshare.22626349.v1
title: Additional file 1 of Alternative signal pathways underly fertilization and egg activation in a fish with contrasting modes of spawning

description: Supplementary Material 1
DOI: 10.6084/m9.figshare.23682310.v1
title: Additional file 4 of The representative COVID-19 cohort Munich (KoCo19): from the beginning of the pandemic to the Delta virus variant

description: Additional file 4: Table S1. Non-response mechanism at the different follow-ups using complete cases and indicator of missingness for income.
DOI: 10.6084/m9.figshare.23682268
title: Additional file 2 of Transfer of patient’s peripheral blood mononuclear cells (PBMCs) disrupts blood–brain barrier and induces anti-NMDAR encephalitis: a study of novel humanized PBMC mouse model

description: Additional file 2. The demographic and clinical characteristics of the subjects were collected.
DOI: 10.6084/m9.figshare.23682276.v1
title: Additional file 2 of BMP4 upregulates glycogen synthesis through the SMAD/SLC2A1 (GLUT1) signaling axis in hepatocellular carcinoma (HCC) cells

description: Additional file 2: Fig. S1. The original images of WB in Figs. 2, 3, 5 and 6. Fig. S2. A The expression of BMP4 and SLC2A1 in Lo2, Huh7, MHCC 97H, HepG2 and Hep3B were assessed by Western blotting. B Huh7 and HepG2 were infected with Ad-B4, Ad-GFP, Ad-siB4 or Ad-RFP, respectively, and fluorescence images were taken at 36h. C Huh7 and HepG2 were infected with Ad-B4, Ad-GFP, Ad-siB4 or Ad-RFP respectively, and TqPCR analysis was used to evaluate the expression of SLC2A1, SLC2A2, SLC2A3 and SLC2A4 at 24h and 48h. “**” P &lt; 0.01, “*” P &lt; 0.05, Ad-B4 group vs Ad-GFP group, Ad-siB4 group vs Ad-RFP group. D Huh7 and HepG2 were treated with 1μm BAY-876 or equal volume DMSO respectively, and TqPCR analysis was used to evaluate the expression of SLC2A1, SLC2A2, SLC2A3 and SLC2A4 at 36h. “**” P &lt; 0.01, “*” P &lt; 0.05, BAY-876 group vs DMSO group. Fig. S3. The graphic abstract of this research.
DOI: 10.13012/b2idb-2952208_v1
title: Data for SuperFine, DACTAL, and BeeTLe

description: This page provides the data for SuperFine, DACTAL, and BeeTLe publications.
- Swenson, M. Shel, et al. "SuperFine: fast and accurate supertree estimation." Systematic biology 61.2 (2012): 214.
- Nguyen, Nam, Siavash Mirarab, and Tandy Warnow. "MRL and SuperFine+ MRL: new supertree methods." Algorithms for Molecular Biology 7 (2012): 1-13.
- Neves, Diogo Telmo, et al. "Parallelizing superfine." Proceedings of the 27th Annual ACM Symposium on Applied Computing. 2012.
- Nelesen, Serita, et al. "DACTAL: divide-and-conquer trees (almost) without alignments." Bioinformatics 28.12 (2012): i274-i282.
- Liu, Kevin, and Tandy Warnow. "Treelength optimization for phylogeny estimation." PLoS One 7.3 (2012): e33104.
DOI: 10.25549/usctheses-ouc11290956
title: Microsoft Word - $ASQ84657_supp_undefined_B400B3BA-BA36-11E0-B4CA-1270D352ABB1.docx
DOI: 10.25549/usctheses-ouc11290994
title: Microsoft Word - $ASQ113852_supp_D78130F6-0394-11E1-B134-A0373012225A.doc
DOI: 10.6084/m9.figshare.25189145
title: SOAsR incubation

description: The data describes the As speciation and sulfate production during SOAsR incubtaion with FK tailings.
DOI: 10.6084/m9.figshare.25189145.v1
title: SOAsR incubation

description: The data describes the As speciation and sulfate production during SOAsR incubtaion with FK tailings.
DOI: 10.17630/01de2c09-14e0-4e59-8111-d53f3e18c531
title: Compositional persistence in a multicyclic network of synthetic replicators (dataset)
DOI: 10.5281/zenodo.10216500
title: Database Food Projects: Universidad de Valencia & Ministerio de Ciencia y Tecnología

description: Database Food Projects Ministerio and Universidad de Valencia
DOI: 10.5281/zenodo.10216499
title: Database Food Projects: Universidad de Valencia & Ministerio de Ciencia y Tecnología

description: Database Food Projects Ministerio and Universidad de Valencia
DOI: 10.6084/m9.figshare.23682310
title: Additional file 4 of The representative COVID-19 cohort Munich (KoCo19): from the beginning of the pandemic to the Delta virus variant

description: Additional file 4: Table S1. Non-response mechanism at the different follow-ups using complete cases and indicator of missingness for income.
DOI: 10.17630/c556bd9b-f995-4c74-a645-606ef2eb5621
title: Data of Upconverting nanorockers for intracellular viscosity measurements during chemotherapy
DOI: 10.5281/zenodo.10629264
title: Bundling Genetic and Financial Technologies for More Resilient and Productive Small-scale Farmers in Africa

description: "Bundling Genetic and Financial Technologies for More Resilient and Productive Small-scale Farmers in Africa" replication package including raw data and code to create all results in paper.
DOI: 10.5281/zenodo.10629265
title: Bundling Genetic and Financial Technologies for More Resilient and Productive Small-scale Farmers in Africa

description: "Bundling Genetic and Financial Technologies for More Resilient and Productive Small-scale Farmers in Africa" replication package including raw data and code to create all results in paper.
DOI: 10.6084/m9.figshare.20012363.v1
title: Additional file 3 of Associations between sleep duration, sleep quality, and weight status in Chinese children and adolescents

description: Additional file 3:
DOI: 10.17630/957f7438-c036-4884-b809-7be82b0bc865
title: Advanced 3D Monte Carlo Algorithms for Biophotonic and Medical Applications (thesis data)

description: Data and code produced or used as part of my PhD. See individual readmes for more information on each datase/codet.
DOI: 10.6084/m9.figshare.20012363
title: Additional file 3 of Associations between sleep duration, sleep quality, and weight status in Chinese children and adolescents

description: Additional file 3:
DOI: 10.6084/m9.figshare.23682330
title: Additional file 3 of Identification of residues critical for the extension of Munc18-1 domain 3a

description: Additional file 3. The individual data values for Fig. 1C, F, 2A-C, 3C, 4C, E, 5B, D, S1, S2, S3B, S4A-D.
DOI: 10.6084/m9.figshare.23682330.v1
title: Additional file 3 of Identification of residues critical for the extension of Munc18-1 domain 3a

description: Additional file 3. The individual data values for Fig. 1C, F, 2A-C, 3C, 4C, E, 5B, D, S1, S2, S3B, S4A-D.
DOI: 10.6084/m9.figshare.22626530.v1
title: Additional file 1 of Transcriptomics and metabolomics analysis of L-phenylalanine overproduction in Escherichia coli

description: Additional file 1: Table S1. The significantly differentially expressed genes screened based on KEGG pathway analysis (X16 vs. X24). Table S2. The significantly differentially expressed genes screened based on KEGG pathway analysis (X24 vs. X48). Table S3. Relative abundances of intracellular metabolites at different fermentation time in an L-Phe overproducing E. coli.
DOI: 10.6084/m9.figshare.12672468.v1
title: Additional file 1 of Integrated small RNA and Degradome sequencing provide insights into salt tolerance in sesame (Sesamum indicum L.)

description: Additional file 1: Table S1. Summary of small RNA sequencing data generated from 18 small RNA libraries. Table S2. Details of identified miRNAs (known and novel) and their precursors. Table S3. Summary of degradome sequencing data. Table S4. List of miRNA targets identified in sesame by degradome sequencing. Table S5. The expression patterns of miRNAs and their target genes in ST and SS genotype responses to salt stress. Table S6. Correlation analysis between the expression profiles of miRNAs and their target genes. Table S7. Primers used in this study.
DOI: 10.6084/m9.figshare.7429610
title: On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis

description: We introduce a nonparametric method for estimating non-Gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the Gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the Gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12672480
title: Additional file 3 of Standardising care in the ICU: a protocol for a scoping review of tools used to improve care delivery

description: Additional file 3. Date extraction document.
DOI: 10.6084/m9.figshare.23682361
title: Additional file 5 of Stable maternal proteins underlie distinct transcriptome, translatome, and proteome reprogramming during mouse oocyte-to-embryo transition

description: Additional file 5: Table S4. Defined up- and down-regulated proteins, RPFs, and mRNAs between each of the two consecutive stages. Related to Figure 5A.
DOI: 10.6084/m9.figshare.23682361.v1
title: Additional file 5 of Stable maternal proteins underlie distinct transcriptome, translatome, and proteome reprogramming during mouse oocyte-to-embryo transition

description: Additional file 5: Table S4. Defined up- and down-regulated proteins, RPFs, and mRNAs between each of the two consecutive stages. Related to Figure 5A.
DOI: 10.6084/m9.figshare.23682352
title: Additional file 2 of Stable maternal proteins underlie distinct transcriptome, translatome, and proteome reprogramming during mouse oocyte-to-embryo transition

description: Additional file 2: Table S1. The processed proteomics data in this study.
DOI: 10.6084/m9.figshare.23682355
title: Additional file 3 of Stable maternal proteins underlie distinct transcriptome, translatome, and proteome reprogramming during mouse oocyte-to-embryo transition

description: Additional file 3: Table S2. The high-confidence proteomics data and the matched Ribo-seq and RNA-seq data.
DOI: 10.17630/74dd1b0a-1ed2-4d93-aeb0-128182fe7bed
title: Perovzalates: a family of perovskite-related oxalates
DOI: 10.6084/m9.figshare.23682352.v1
title: Additional file 2 of Stable maternal proteins underlie distinct transcriptome, translatome, and proteome reprogramming during mouse oocyte-to-embryo transition

description: Additional file 2: Table S1. The processed proteomics data in this study.
DOI: 10.6084/m9.figshare.20012378
title: Additional file 2 of The genomic and transcriptome characteristics of lung adenocarcinoma patients with previous breast cancer

description: Additional file 2: Supplementary Fig. 2. Results of somatic cell copy number variation analysis for patient QY (A) and ZXH (B).
DOI: 10.6084/m9.figshare.20012375.v1
title: Additional file 1 of The genomic and transcriptome characteristics of lung adenocarcinoma patients with previous breast cancer

description: Additional file 1: Supplementary Fig. 1. Principal component analysis of 18 patients (A) and cluster analysis of differentially expressed genes in 14 patients (B).
DOI: 10.25549/usctheses-c18-220791
title: In-Service Education Of Teachers In Small Unified School Districts
DOI: 10.6084/m9.figshare.20012378.v1
title: Additional file 2 of The genomic and transcriptome characteristics of lung adenocarcinoma patients with previous breast cancer

description: Additional file 2: Supplementary Fig. 2. Results of somatic cell copy number variation analysis for patient QY (A) and ZXH (B).
DOI: 10.6084/m9.figshare.7429727
title: Additional file 9: of STON2 negatively modulates stem-like properties in ovarian cancer cells via DNMT1/MUC1 pathway

description: Table S5. Association of MUC1 expression with clinicopathological characteristics in patients with ovarian cancer (nÂ =â 165). (XLSX 11 kb)
DOI: 10.6084/m9.figshare.7429727.v1
title: Additional file 9: of STON2 negatively modulates stem-like properties in ovarian cancer cells via DNMT1/MUC1 pathway

description: Table S5. Association of MUC1 expression with clinicopathological characteristics in patients with ovarian cancer (nÂ =â 165). (XLSX 11 kb)
DOI: 10.6084/m9.figshare.7429739.v1
title: Additional file 9: of NmeCas9 is an intrinsically high-fidelity genome-editing platform

description: Table S7. Primer sequences used for on- and off-target deep sequencing analysis for all genomic editing sites analyzed by GUIDE-seq. (XLSX 28 kb)
DOI: 10.14473/csda/nxi0v9/n1udhz
title: D_V1409.pdf

description: Dotazník
DOI: 10.14473/csda/nxi0v9/ijsel9
title: TI_V1409.pdf

description: Technická informace
DOI: 10.14473/csda/nxi0v9/znrtss
title: PR02_V1409.pdf

description: Občané o možnostech a motivaci ke studiu na vysokých školách - září 2014. Tisková zpráva CVVM.
DOI: 10.5281/zenodo.7973922
title: SWECO25: Vegetation (vege)

description: The vegetation category (SWECO25 v1.0.0) contains the "copernicus" and "nfi" datasets. 

The copernicus dataset describes the dominant leaf type. After reprojecting and resampling the “High Resolution Layer: Dominant Leaf Type” (DLT) source data (EEA, 2018) to the SWECO25 grid, we generated individual layers for the two available categories (coniferous and deciduous). We provided the binary maps for (0 or 1) for each of them and computed 13 focal statistics layers by applying a cell-level function calculating the average percentage cover value for a given category in a circular moving window of 13 radii ranging from 25m to 5km. Final values were rounded and multiplied by 100.

The nfi dataset describes the height of the vegetation canopy. After reprojecting and resampling the source data (Ginzler, 2021) to the SWECO25 grid with three resampling schemes (maximum, minimum, and median values), we generated and provided the three individual layers. In addition, for each of them, we provided 13 focal statistics layers obtained by applying a cell-level function calculating the average canopy height value in a circular moving window of 13 radii ranging from 25m to 5km. This dataset includes a total of 42 layers. Final values were rounded and multiplied by 100.

The detailed list of layers available is provided in SWECO25_datalayers_details_vege.csv and includes information on the category, dataset, variable name (long), variable name (short), period, sub-period, start year, end year, attribute, radii, unit, and path.

References:

European Environment Agency [EEA]. Copernicus Land Monitoring Service - High Resolution Layer Forest. (Copenhagen, Denmark, 2018).

Ginzler, C. Vegetation Height Model (National Forest Inventory). (Birmensdorf, Switzerland, 2021)
description: We gratefully acknowledge financial support through the Action Plan of the Swiss Biodiversity Strategy by the Federal Office for the Environment (FOEN) for financing the ValPar.CH and SwissCatchment projects. All the institutions and contributors who made the input data freely available are gratefully acknowledged.
DOI: 10.6084/m9.figshare.7429724
title: Additional file 8: of STON2 negatively modulates stem-like properties in ovarian cancer cells via DNMT1/MUC1 pathway

description: Table S4. Association of STON2 expression with clinicopathological characteristics in patients with ovarian cancer (nÂ =â 165). (XLSX 11 kb)
DOI: 10.6084/m9.figshare.7429739
title: Additional file 9: of NmeCas9 is an intrinsically high-fidelity genome-editing platform

description: Table S7. Primer sequences used for on- and off-target deep sequencing analysis for all genomic editing sites analyzed by GUIDE-seq. (XLSX 28 kb)
DOI: 10.6084/m9.figshare.7429610.v1
title: On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis

description: We introduce a nonparametric method for estimating non-Gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the Gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the Gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis. Supplementary materials for this article are available online.
DOI: 10.14473/csda/nxi0v9/ctliop
title: PR05_V1409.pdf

description: Důvěra vrcholným politikům - září 2014. Tisková zpráva CVVM.
DOI: 10.14473/csda/nxi0v9/waubrl
title: PR12_V1409.pdf

description: Oblíbené typy restauračních zařízení v roce 2014. Tisková zpráva CVVM.
DOI: 10.6084/m9.figshare.22626370
title: Additional file 1 of The putative methyltransferase LaeA regulates mycelium growth and cellulase production in Myceliophthora thermophila

description: Additional file 1: Table S1. Primers used in this study. Table S2. The profiles of RNA-seq reads mapped to the genome of M. thermophila and the differential expression analysis. Table S3. Genes showing significantly differential transcriptional levels in strain ∆laeA on glucose compared to the wild-type strain. Table S4. KEGG analysis of the 337 genes with up-regulated expression levels in strain ∆laeA on glucose. Table S5. Transcriptional profile of genes involved in metabolic pathway in M. thermophila. Table S6. Transcription factors showing significantly differential transcriptional levels in strain ∆laeA on glucose as compared to the wild-type strain. Table S7. Genes showing significantly differential transcriptional levels in strains Δcre-1, Δgrf-1, Δgrf-2, and Δgrf-3 on glucose compared to the wild-type strain. Table S8. KEGG analysis of genes showing significantly up-regulated transcriptional levels in all strains (∆cre-1, Δgrf-1, Δgrf-2, and Δgrf-3), compared to the wild type. Table S9. The analysis of H3K9 methylation level in ΔlaeA compared to WT by ChIP-seq. Table S10. Genes showing significantly differential transcriptional levels in strain ΔlaeA on Avicel for 2 d compared to the WT strain and functional category analysis of the genes expressed more highly in strain ΔlaeA (p values &lt; 0.005). Table S11. Genes showing significantly differential transcriptional levels in strain ΔlaeA on Avicel for 4 d compared to the WT strain and functional category analysis of the genes expressed more highly in strain ΔlaeA (p values &lt; 0.05). Table S12. Transcriptional levels of CAZyme genes in strain ΔlaeA on Avicel for 2d and 4 d. Table S13. Transcriptomic profiles of the genes related to the secondary metabolism in the strain ΔlaeA when response to Avicel.
DOI: 10.6084/m9.figshare.22626370.v1
title: Additional file 1 of The putative methyltransferase LaeA regulates mycelium growth and cellulase production in Myceliophthora thermophila

description: Additional file 1: Table S1. Primers used in this study. Table S2. The profiles of RNA-seq reads mapped to the genome of M. thermophila and the differential expression analysis. Table S3. Genes showing significantly differential transcriptional levels in strain ∆laeA on glucose compared to the wild-type strain. Table S4. KEGG analysis of the 337 genes with up-regulated expression levels in strain ∆laeA on glucose. Table S5. Transcriptional profile of genes involved in metabolic pathway in M. thermophila. Table S6. Transcription factors showing significantly differential transcriptional levels in strain ∆laeA on glucose as compared to the wild-type strain. Table S7. Genes showing significantly differential transcriptional levels in strains Δcre-1, Δgrf-1, Δgrf-2, and Δgrf-3 on glucose compared to the wild-type strain. Table S8. KEGG analysis of genes showing significantly up-regulated transcriptional levels in all strains (∆cre-1, Δgrf-1, Δgrf-2, and Δgrf-3), compared to the wild type. Table S9. The analysis of H3K9 methylation level in ΔlaeA compared to WT by ChIP-seq. Table S10. Genes showing significantly differential transcriptional levels in strain ΔlaeA on Avicel for 2 d compared to the WT strain and functional category analysis of the genes expressed more highly in strain ΔlaeA (p values &lt; 0.005). Table S11. Genes showing significantly differential transcriptional levels in strain ΔlaeA on Avicel for 4 d compared to the WT strain and functional category analysis of the genes expressed more highly in strain ΔlaeA (p values &lt; 0.05). Table S12. Transcriptional levels of CAZyme genes in strain ΔlaeA on Avicel for 2d and 4 d. Table S13. Transcriptomic profiles of the genes related to the secondary metabolism in the strain ΔlaeA when response to Avicel.
DOI: 10.14473/csda/nxi0v9/hucfbi
title: PR07_V1409.pdf

description: Důvěra některým institucím veřejného života v září 2014. Tisková zpráva CVVM.
DOI: 10.6084/m9.figshare.22626530
title: Additional file 1 of Transcriptomics and metabolomics analysis of L-phenylalanine overproduction in Escherichia coli

description: Additional file 1: Table S1. The significantly differentially expressed genes screened based on KEGG pathway analysis (X16 vs. X24). Table S2. The significantly differentially expressed genes screened based on KEGG pathway analysis (X24 vs. X48). Table S3. Relative abundances of intracellular metabolites at different fermentation time in an L-Phe overproducing E. coli.
DOI: 10.14473/csda/nxi0v9/hbltqo
title: PR06_V1409.pdf

description: Postoj české veřejnosti k dění na Ukrajině – září 2014. Tisková zpráva CVVM.
DOI: 10.6084/m9.figshare.12672468
title: Additional file 1 of Integrated small RNA and Degradome sequencing provide insights into salt tolerance in sesame (Sesamum indicum L.)

description: Additional file 1: Table S1. Summary of small RNA sequencing data generated from 18 small RNA libraries. Table S2. Details of identified miRNAs (known and novel) and their precursors. Table S3. Summary of degradome sequencing data. Table S4. List of miRNA targets identified in sesame by degradome sequencing. Table S5. The expression patterns of miRNAs and their target genes in ST and SS genotype responses to salt stress. Table S6. Correlation analysis between the expression profiles of miRNAs and their target genes. Table S7. Primers used in this study.
DOI: 10.6084/m9.figshare.22634332
title: Clone of: TF-C Pretrain EMG

description: Original data: https://figshare.com/articles/dataset/TF-C_Pretrain_EMG/19930250