cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7012643.v1
title: Time series seasonal adjustment using regularized singular value decomposition

description: We propose a new seasonal adjustment method based on the Regularized Singular Value Decomposition (RSVD) of the matrix obtained by reshaping the seasonal time series data. The method is flexible enough to capture two kinds of seasonality: the fixed seasonality that does not change over time and the time-varying seasonality that varies from one season to another. RSVD represents the time-varying seasonality by a linear combination of several seasonal patterns. The right singular vectors capture multiple seasonal patterns, and the corresponding left singular vectors capture the magnitudes of those seasonal patterns and how they change over time. By assuming the time-varying seasonal patterns change smoothly over time, the RSVD uses penalized least squares with a roughness penalty to effectively extract the left singular vectors. The proposed method applies to seasonal time series data with a stationary or nonstationary non-seasonal component. The method also has a variant that can handle the case that an abrupt change (i.e., break) may occur in the magnitudes of seasonal patterns. Our proposed method compares favorably with the state-of-art X-13ARIMA-SEATS program on both simulated and real data examples.
DOI: 10.6084/m9.figshare.7012643.v3
title: Time Series Seasonal Adjustment Using Regularized Singular Value Decomposition

description: We propose a new seasonal adjustment method based on the Regularized Singular Value Decomposition (RSVD) of the matrix obtained by reshaping the seasonal time series data. The method is flexible enough to capture two kinds of seasonality: the fixed seasonality that does not change over time and the time-varying seasonality that varies from one season to another. RSVD represents the time-varying seasonality by a linear combination of several seasonal patterns. The right singular vectors capture multiple seasonal patterns, and the corresponding left singular vectors capture the magnitudes of those seasonal patterns and how they change over time. By assuming the time-varying seasonal patterns change smoothly over time, the RSVD uses penalized least squares with a roughness penalty to effectively extract the left singular vectors. The proposed method applies to seasonal time-series data with a stationary or nonstationary nonseasonal component. The method also has a variant that can handle the case that an abrupt change (i.e., break) may occur in the magnitudes of seasonal patterns. Our proposed method compares favorably with the state-of-art X-13ARIMA-SEATS program on both simulated and real data examples.
DOI: 10.6084/m9.figshare.11731002.v2
title: Transcription of lncRNA <i>ACoS-AS1</i> is essential to <i>trans</i>-splicing between <i>SlPsy1</i> and <i>ACoS-AS1</i> that causes yellow fruit in tomato

description: Phytoene synthase (PSY) has been considered as an important regulatory enzyme in carotenoids biosynthesis pathway. Previous study finds that the yellow fruit in <i>Solanum lycopersicum</i> var. <i>cerasiforme</i> accession PI 114490 is caused by loss-of-function of SlPSY1 due to <i>trans</i>-splicing between <i>SlPsy1</i> and an unknown gene transcribed from neighbour opposite strand DNA of <i>SlPsy1</i>. The genomic DNA sequences of <i>SlPsy1</i> between red and yellow-fruited tomato lines have one single-nucleotide polymorphism (SNP) in the fourth intron and one SSR in the intergenic region. In the current study, the cause of <i>trans</i>-splicing event was further investigated. The data showed that the previously defined unknown gene was a putative long non-coding RNA <i>ACoS-AS1</i> with three variants in many yellow-fruited tomato lines. The intronic SNP and intergenic SSR were tightly associated with <i>trans</i>-splicing event <i>SlPsy1-ACoS-AS1</i>. However, transgenic tomato lines carrying the genomic DNA of <i>SlPsy1</i> from PI 114490 did not generate transcripts of <i>ACoS-AS1</i>and <i>SlPsy1-ACoS-AS1</i> suggesting that only the intronic SNP could not cause the <i>trans</i>-splicing event. Over-expression of <i>SlPsy1-ACoS-AS1</i> in red-fruited tomato line M82 did not have any phenotype change while over-expression of wild type <i>SlPsy1</i> resulted in altered leaf colour. Sub-cellular localization analysis showed that SlPSY1-ACoS-AS1 could not enter plastids where SlPSY1 has its enzyme activity. Mutation of <i>ACoS-AS1</i> in PI 114490 generated by CRISPR/Cas9 techniques resulted in red fruits implying that <i>ACoS-AS1</i> was essential to <i>trans</i>-splicing event <i>SlPsy1-ACoS-AS1</i>. The results obtained here will extend knowledge to understand the mechanism of <i>trans</i>-splicing event <i>SlPsy1-ACoS-AS1</i> and provide additional information for the regulation of carotenoids biosynthesis.
DOI: 10.6084/m9.figshare.12780665
title: Additional file 10 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 10. HTML output for the integrated analysis of scRNA-seq (12k cells) and scATAC-seq (10k cells) datasets of human PBMC from different donors using MAESTRO.
DOI: 10.6084/m9.figshare.14877141.v1
title: Triglyceride–glucose index predicts the risk of gestational diabetes mellitus: a systematic review and meta-analysis

description: We aimed to investigate the potential predictive efficacy of triglyceride–glucose (T/Gly) index for gestational diabetes mellitus (GDM) in a systematic review and meta-analysis. Cohort studies demonstrating the association between T/Gly index measured at the first trimester or before pregnancy and the subsequent incidence of GDM were identified by search of PubMed, Embase, China National Knowledge Infrastructure, and WanFang databases. A random-effect model incorporating the heterogeneity was applied to pool the results. Five cohort studies including 382,213 women were included in this meta-analysis. Compared to those with the lowest category of T/Gly index, women with the highest category of T/Gly index were independently associated with higher risk of subsequent GDM (odds ratio [OR]: 2.52, 95% confidence interval [CI]: 1.33 ∼ 4.67, <i>I</i><sup>2</sup>=65%, <i>p</i>=.004) after adjustment of potential confounding factors including age, body mass index, and family history of diabetes. The association was stronger in prospective cohort studies than retrospective cohort studies (<i>p</i> for subgroup difference=.007), and a significant association was detected in Asian women (OR: 3.30, 95% CI: 1.50–7.28, <i>p</i> =.003), but not in non-Asian women (OR: 0.96, 95% CI: 0.35–2.63, <i>p</i>=.94). Higher T/Gly index may independently predict the risk of GDM in Asian women.
DOI: 10.6084/m9.figshare.12780671
title: Additional file 1 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 1: Table S1. Components of MAESTRO that achieved using the existing software and custom code.
DOI: 10.6084/m9.figshare.12780686.v1
title: Additional file 6 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 6: Table S4. Transcription factor motif clusters used in MAESTRO workflow
DOI: 10.6084/m9.figshare.12780692
title: Additional file 8 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 8. HTML output for the scRNA-seq analysis on the human PBMC sample (12k cells) from different donors using MAESTRO.
DOI: 10.6084/m9.figshare.12780692.v1
title: Additional file 8 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 8. HTML output for the scRNA-seq analysis on the human PBMC sample (12k cells) from different donors using MAESTRO.
DOI: 10.6084/m9.figshare.12780689
title: Additional file 7 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 7: Table S5. Number of cells in scATAC-seq that received transferred labels from scRNA-seq.
DOI: 10.6084/m9.figshare.12780674.v1
title: Additional file 2 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 2: Table S2. Running time and memory comparison between MAESTRO and other tools for scATAC-seq analysis.
DOI: 10.6084/m9.figshare.12780695
title: Additional file 9 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 9. HTML output for the scATAC-seq analysis on the human PBMC sample (10k cells) from different donors using MAESTRO.
DOI: 10.6084/m9.figshare.12780683
title: Additional file 5 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 5: Table S3. Immune and stromal gene signatures used in the analysis
DOI: 10.6084/m9.figshare.12780671.v1
title: Additional file 1 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 1: Table S1. Components of MAESTRO that achieved using the existing software and custom code.
DOI: 10.6084/m9.figshare.19071897
title: Genome-wide identification of protein phosphatase 2C family members in <i>Glycyrrhiza uralensis</i> Fisch. and their response to abscisic acid and polyethylene glycol stress

description: The protein phosphatase 2C (PP2C) gene family, which is known to participate in cellular processes, is one of the most conserved plant-specific gene families that regulate signal transduction in eukaryotic organisms. However, the PP2C gene family of <i>Glycyrrhiza uralensis</i> Fisch. has not yet been systematically characterized. In this study, 76 PP2C genes of <i>G. uralensis</i> (<i>GuPP2C</i>s) were identified. Phylogenetic analysis divided these <i>GuPP2C</i>s into 12 subfamilies. The gene structure and protein motifs of the <i>GuPP2C</i>s were then analysed. The analysis of the transcriptomic data of the <i>GuPP2C</i>s revealed that nine genes were highly sensitive to abscisic acid (ABA) stress and might respond to ABA treatment. These nine genes were validated via quantitative real-time polymerase chain reaction. This study provides a foundation for future studies on the functional PP2C genes of <i>G. uralensis</i> and the improvement of the cultivation and quality of <i>G. uralensis</i>.
DOI: 10.6084/m9.figshare.12780665.v1
title: Additional file 10 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 10. HTML output for the integrated analysis of scRNA-seq (12k cells) and scATAC-seq (10k cells) datasets of human PBMC from different donors using MAESTRO.
DOI: 10.6084/m9.figshare.12780683.v1
title: Additional file 5 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 5: Table S3. Immune and stromal gene signatures used in the analysis
DOI: 10.6084/m9.figshare.12780689.v1
title: Additional file 7 of Integrative analyses of single-cell transcriptome and regulome using MAESTRO

description: Additional file 7: Table S5. Number of cells in scATAC-seq that received transferred labels from scRNA-seq.
DOI: 10.6084/m9.figshare.24559891.v1
title: tradeoffs

description: Biodiversity and ecosystem services differ between edges and interiors in European forests
DOI: 10.6084/m9.figshare.19071897.v1
title: Genome-wide identification of protein phosphatase 2C family members in <i>Glycyrrhiza uralensis</i> Fisch. and their response to abscisic acid and polyethylene glycol stress

description: The protein phosphatase 2C (PP2C) gene family, which is known to participate in cellular processes, is one of the most conserved plant-specific gene families that regulate signal transduction in eukaryotic organisms. However, the PP2C gene family of <i>Glycyrrhiza uralensis</i> Fisch. has not yet been systematically characterized. In this study, 76 PP2C genes of <i>G. uralensis</i> (<i>GuPP2C</i>s) were identified. Phylogenetic analysis divided these <i>GuPP2C</i>s into 12 subfamilies. The gene structure and protein motifs of the <i>GuPP2C</i>s were then analysed. The analysis of the transcriptomic data of the <i>GuPP2C</i>s revealed that nine genes were highly sensitive to abscisic acid (ABA) stress and might respond to ABA treatment. These nine genes were validated via quantitative real-time polymerase chain reaction. This study provides a foundation for future studies on the functional PP2C genes of <i>G. uralensis</i> and the improvement of the cultivation and quality of <i>G. uralensis</i>.
DOI: 10.6084/m9.figshare.23790623
title: The complete mitochondrial genome of <i>Cuminum cyminum</i> (Apiales: Apiaceae) and phylogenetic analysis

description: Cumin (<i>Cuminum cyminum</i> L). belongs to the family Apiaceae and the order Apiales, which is a widely grown spice and medicinal plant in Xinjiang province, China. In the current study, whole genome sequencing of <i>C. cyminum</i> was performed using the Illumina HiSeq 4000 platform, and the complete mitogenome sequence was assembled and annotated. We found that the single circular mitogenome of <i>C. cyminum</i> was 246,721 bp in length, and has about 45.5% GC content. It comprised 73 genes in the coding region (35 protein-coding genes, 18 tRNA genes, 3 rRNA genes, and 15 open-reading frames) and a non-coding region. Phylogenetic analysis indicated that <i>C. cyminum</i> is closely related to <i>Daucus carota</i> and the subtribes <i>Daucinae</i>. The mitogenome of <i>C. cyminum</i> revealed its phylogenetic relationships with other species in the Apiaceae family, which would further help in understanding its evolution.
DOI: 10.6084/m9.figshare.19596267
title: Additional file 1 of The impact of medical insurance reimbursement on postoperative inflammation reaction in distinct cardiac surgery from a single center

description: Additional file 1: Supplemental file 1. Entitled ASD was the data of the patients accepted atrium septum defect (ASD) or patent foramen ovale (PFO) occlusion.
DOI: 10.6084/m9.figshare.28788071
title: cybersecurity_science-technology_data

description: Literature data retrieved from WoS and DII using "network security" as the keyword, as well as data generated during paper data processing.
DOI: 10.13145/bacdive15109.20170829.2
title: Streptomyces collinus Lindenbein 1952

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive15110.20170829.2
title: Streptomyces collinus Lindenbein 1952

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive15111.20170829.2
title: Streptomyces corchorusii Ahmad and Bhuiyan 1958 emend. Lanoot et al. 2005

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive15112.20170829.2
title: Streptomyces corchorusii Ahmad and Bhuiyan 1958 emend. Lanoot et al. 2005

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive15113.20170829.2
title: Streptomyces cremeus (Kudrina 1957) Pridham et al. 1958

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive15114.20170829.2
title: Streptomyces curacoi Cataldi 1963

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive15115.20170829.2
title: Streptomyces cyaneofuscatus (Kudrina 1957) Pridham et al. 1958

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16004.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16005.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16006.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16007.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16008.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16009.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16010.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16011.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16012.20170829.2
title: Streptomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16775.20170829.2
title: Thermoactinomyces vulgaris Tsilinsky 1899

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16776.20170829.2
title: Thermoactinomyces vulgaris Tsilinsky 1899

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16777.20170829.2
title: Thermoactinomyces intermedius Kurup et al. 1981

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16778.20170829.2
title: Thermoactinomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16779.20170829.2
title: Thermoactinomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16780.20170829.2
title: Thermoactinomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16781.20170829.2
title: Thermoactinomyces sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive16782.20170829.2
title: Thermoflavimicrobium dichotomicum (Krasil'nikov and Agre 1964) Yoon et al. 2005

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17593.20170829.2
title: Xanthomonas axonopodis Starr and Garces 1950 emend. Vauterin et al. 1995

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17595.20170829.2
title: Xanthomonas sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17596.20170829.2
title: Xanthomonas sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17597.20170829.2
title: Xanthomonas sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17598.20170829.2
title: Xanthomonas sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17599.20170829.2
title: Xanthomonas cynarae Trébaol et al. 2000

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17600.20170829.2
title: Xanthomonas vasicola Vauterin et al. 1995

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17601.20170829.2
title: Xanthomonas arboricola Vauterin et al. 1995

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17602.20170829.2
title: Xanthomonas arboricola Vauterin et al. 1995

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive17603.20170829.2
title: Xanthomonas arboricola Vauterin et al. 1995

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14408.20170829.2
title: Pullulanibacillus uraniitolerans Pereira et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14409.20170829.2
title: Sinobaca qinghaiensis (Li et al. 2006) Li et al. 2008

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14410.20170829.2
title: Jeotgalicoccus pinnipedialis Hoyles et al. 2004

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14411.20170829.2
title: Jeotgalicoccus halotolerans Yoon et al. 2003

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14412.20170829.2
title: Jeotgalicoccus psychrophilus Yoon et al. 2003

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14413.20170829.2
title: Jeotgalicoccus marinus Chen et al. 2009

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive14414.20170829.2
title: Jeotgalicoccus huakuii Guo et al. 2010

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.