cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14794955
title: Supplementary Table 5. from Shared evolutionary footprints suggest mitochondrial oxidative damage underlies multiple complex I losses in fungi

description: <b>Scores of all pathways in the recent CI loss.</b> Show are the scores for all the pathways according to our pathway scoring method.
DOI: 10.6084/m9.figshare.14794958
title: Supplementary Table 1. from Shared evolutionary footprints suggest mitochondrial oxidative damage underlies multiple complex I losses in fungi

description: Species surveyed in the screen of eukaryotic mitochondrial genomes.
DOI: 10.6084/m9.figshare.14266596.v1
title: Additional file 2 of A non-invasive nanoparticles for multimodal imaging of ischemic myocardium in rats

description: Additional file 2: Movie S1. Echocardiography before operation in rats. Movie S2. Echocardiography after operation in model rats.
DOI: 10.6084/m9.figshare.6406580
title: Potential Impacts of Sahara Dust Aerosol on Rainfall Vertical Structure over the Atlantic Ocean as Identified from EOF Analysis (dataset.rar)

description: The current study investigates the potential impacts of Sahara dust on
rainfall vertical structure over the Atlantic Ocean by employing multi-sensor
satellite observations. The variabilities in rainfall vertical structure are
decomposed by empirical orthogonal function (EOF) analysis. For a given near
surface rain rate, the mean storm height of stratiform rain under dust-laden
condition is significantly higher than that under the dust-free condition. The
stratiform rain rate at the layers well above the freezing level is substantially
enhanced under dust-laden condition. Those changes may result from dynamic and thermodynamic
effect of Sahara Air Layer effect and/or the effect that dust aerosol acting as
additional ice nuclei. For convective rain, there is no significant
difference in the leading three normalized EOF modes between the dust-laden and
dust-free sectors, implying that dust effect, if exists, is not strong enough
to cause evident changes in convective rainfall profiles. For stratiform rain,
the EOF1 shows no signals of dust effect either. However, significant
difference are found in the EOF2 and EOF3 modes between dust-laden and
dust-free conditions. The normalized EOF2 and EOF3 under dust-laden condition
both represent enhanced rain rate at upper layer well above the freezing level,
where heterogeneous ice nucleation prevails. The statistical study shows consistent results
with case study, except that the aerosol-related changes in stratiform rainfall
vertical structure is isolated in the EOF3 only. This study suggests EOF
analysis a promising way for isolating the potential and relatively weak
aerosol effects on precipitation from the strong dynamic effects.<br>
DOI: 10.6084/m9.figshare.22655244
title: Additional file 1 of Identification of a m6A-related ferroptosis signature as a potential predictive biomarker for lung adenocarcinoma

description: Additional file 1: Supplementary Table 1. The raw data were applied to process the normalized GSE72094 expression profile.
DOI: 10.6084/m9.figshare.22655244.v1
title: Additional file 1 of Identification of a m6A-related ferroptosis signature as a potential predictive biomarker for lung adenocarcinoma

description: Additional file 1: Supplementary Table 1. The raw data were applied to process the normalized GSE72094 expression profile.
DOI: 10.6084/m9.figshare.22655253
title: Additional file 2 of Identification of a m6A-related ferroptosis signature as a potential predictive biomarker for lung adenocarcinoma

description: Additional file 2: Supplementary Table 2. 348 ferroptosis genes were downloaded from the FerrDb database.
DOI: 10.6084/m9.figshare.18989547
title: Integrated Analysis of Long Non-Coding RNA -mRNA Profile and Validation in Diabetic Cataract

description: To illustrate the expression profile of lncRNAs and mRNAs in diabetic cataract (DC) and explore their potential role in the pathogenesis of DC. LncRNA and mRNA microarray were conducted using the lens epithelium of DC patients (n = 3) and controls from eye bank (n = 3). Further, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were employed to unveil their underlying biological function and signaling pathway. The co-expression network was constructed to explore the relationship between lncRNAs and mRNAs. Then, lens epithelial cells (LECs) were cultured in vitro under high glucose (HG) and normal glucose (NG) groups to further verified the expression profiles of mRNAs. At last, quantitative RT-PCR (qRT-PCR) was performed to confirm the microarray results for the aberrantly expressed lncRNAs, and to unveil the expression prolife of mRNAs in LECs. Eight thousand three hundred and twenty-six lncRNAs and 3303 mRNAs were dysregulated in DC. GO analysis unveiled that the upregulated mRNAs, highest enrichment score of the GO term belonged to oxidation-reduction process, while the highest for downregulated mRNAs went to protein lipidation. In the CC category, the most significant terms for upregulated and downregulated mRNAs appeared in intracellular part and intrinsic component of membrane, respectively. As to MF category, the most significant term for upregulated mRNAs was protein binding, and for downregulated mRNAs was catecholamine binding. KEGG pathways analysis demonstrated that the major enrichment score of pathways in upregulated mRNAs included Glycolysis/Gluconeogenesis, lysosome, carbon metabolism and AGE-RAGE signaling pathway. For the downregulated mRNAs, the glycosphingolipid biosynthesis-lacto and neolacto series pathway was included. Three lncRNAs (LINC01508, MAFA-AS1, MIAT) and the <i>Sirtuin 2</i> are positively related in the co-expression network. This study provided an overview of the lncRNAs and mRNAs expression, and suggesting that several aberrantly expressed lncRNAs might participate in the pathogenesis of DC.
DOI: 10.6084/m9.figshare.18989547.v1
title: Integrated Analysis of Long Non-Coding RNA -mRNA Profile and Validation in Diabetic Cataract

description: To illustrate the expression profile of lncRNAs and mRNAs in diabetic cataract (DC) and explore their potential role in the pathogenesis of DC. LncRNA and mRNA microarray were conducted using the lens epithelium of DC patients (n = 3) and controls from eye bank (n = 3). Further, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were employed to unveil their underlying biological function and signaling pathway. The co-expression network was constructed to explore the relationship between lncRNAs and mRNAs. Then, lens epithelial cells (LECs) were cultured in vitro under high glucose (HG) and normal glucose (NG) groups to further verified the expression profiles of mRNAs. At last, quantitative RT-PCR (qRT-PCR) was performed to confirm the microarray results for the aberrantly expressed lncRNAs, and to unveil the expression prolife of mRNAs in LECs. Eight thousand three hundred and twenty-six lncRNAs and 3303 mRNAs were dysregulated in DC. GO analysis unveiled that the upregulated mRNAs, highest enrichment score of the GO term belonged to oxidation-reduction process, while the highest for downregulated mRNAs went to protein lipidation. In the CC category, the most significant terms for upregulated and downregulated mRNAs appeared in intracellular part and intrinsic component of membrane, respectively. As to MF category, the most significant term for upregulated mRNAs was protein binding, and for downregulated mRNAs was catecholamine binding. KEGG pathways analysis demonstrated that the major enrichment score of pathways in upregulated mRNAs included Glycolysis/Gluconeogenesis, lysosome, carbon metabolism and AGE-RAGE signaling pathway. For the downregulated mRNAs, the glycosphingolipid biosynthesis-lacto and neolacto series pathway was included. Three lncRNAs (LINC01508, MAFA-AS1, MIAT) and the <i>Sirtuin 2</i> are positively related in the co-expression network. This study provided an overview of the lncRNAs and mRNAs expression, and suggesting that several aberrantly expressed lncRNAs might participate in the pathogenesis of DC.
DOI: 10.5281/zenodo.10633768
title: Mud settling experiments - Water/mud interface level time series

description: Various mud settling experiments were conducted during this research. The variable between the different experiments is the procedure (technique and duration) for conditioning of the mud.  Four different techniques were applied. Durations varied from 15 to 60 minutes in steps of 15 minutes. During the experiments the level of the water/mud interface was monitored over a week. These datasets contain these time series of each settling experiment.
description: Behind the settling columns lighting was installed to accentuate the water/mud interface. The water/mud interface was monitored by taking pictures at variable time intervals. Based on the contrast between the water layer and the mud, the interface level was automatically determined using the standard "straight edge detection" algorithm available in LabView. The output of this, are the CSV files containing the evolution of the interface level over time, expressed in pixels. These values are converted to mm and further processed to generate the settling curves.
DOI: 10.5281/zenodo.10633769
title: Mud settling experiments - Water/mud interface level time series

description: Various mud settling experiments were conducted during this research. The variable between the different experiments is the procedure (technique and duration) for conditioning of the mud.  Four different techniques were applied. Durations varied from 15 to 60 minutes in steps of 15 minutes. During the experiments the level of the water/mud interface was monitored over a week. These datasets contain these time series of each settling experiment.
description: Behind the settling columns lighting was installed to accentuate the water/mud interface. The water/mud interface was monitored by taking pictures at variable time intervals. Based on the contrast between the water layer and the mud, the interface level was automatically determined using the standard "straight edge detection" algorithm available in LabView. The output of this, are the CSV files containing the evolution of the interface level over time, expressed in pixels. These values are converted to mm and further processed to generate the settling curves.
DOI: 10.6084/m9.figshare.21995069.v4
title: Files for Main Figure 4

description: GSVA scores with DNA/RNA sensing genesDNA_RNA_gene_TE_cor_GSVA_telescope: Correlation between GSVA score of DNA/RNA sensing genes with TEs quantified by TelescopeDNA_RNA_gene_TE_cor_GSVA_LocusMasterTE: Correlation between GSVA score of DNA/RNA sensing genes with TEs quantified by LocusMasterTECorrelation with intergenic TEs and nearby Genescorrelation_intergenic_TEs_Gene: Spearman correlation between intergenic TEs and nearby GenesSurvival AnalysisTCGA_COAD_log2TPM_Gene: log2TPM values of GenesTCGA_COAD_log2TPM_TE: log2TPM values of TEs quantified by LocusMasterTETEs_catpured_only_by_LocusMasterTE: A list of TEs captured exclusively by LocusMasterTEInverted SINE mutational Signaturemutational_profile_TCGA-COAD: mutational profiles of TCGA-COAD tumor samples and inverted SINE sample
DOI: 10.6084/m9.figshare.12173985
title: A hybrid transfer learning framework for in-plane freeform shape accuracy control in additive manufacturing

description: Shape accuracy control is one of the quality issues of greatest concern in Additive Manufacturing (AM). An efficient approach to improving the shape accuracy of a fabricated product is to compensate the fabrication errors of AM systems by modifying the input shape defined by a digital design model. In contrast with mass production, AM processes typically fabricate customized products with extremely low volume and huge shape varieties, which makes shape accuracy control in AM a challenging problem. In this article, we propose a hybrid transfer learning framework to predict and compensate the in-plane shape deviations of new and untried freeform products based on a small number of previously fabricated products. Within this framework, the shape deviation is decomposed into a shape-independent error and a shape-specific error. A parameter-based transfer learning approach is used to facilitate a sharing of parameters for modeling the shape-independent error, whereas a feature-based transfer learning approach is taken to promote the learning of a common representation of local shape features for modeling the shape-specific error. Experimental studies of a fused filament fabrication process demonstrate the effectiveness of our proposed framework in predicting the shape deviation and improving the shape accuracy of new products with freeform shapes.
DOI: 10.6084/m9.figshare.12173991
title: Bio-entities_Main

description: CSV file containing all types of extracted bio-entities by BioBERT. It correspond to the Table 6 in the article.
DOI: 10.6084/m9.figshare.22655259
title: Additional file 4 of Identification of a m6A-related ferroptosis signature as a potential predictive biomarker for lung adenocarcinoma

description: Additional file 4: Supplementary Table 4-S3. The raw data used to generate Figure 4G-H.
DOI: 10.6084/m9.figshare.12173991.v1
title: Bio-entities_Main

description: CSV file containing all types of extracted bio-entities by BioBERT. It correspond to the Table 6 in the article.
DOI: 10.6084/m9.figshare.6406823
title: Code and data to reproduce "Contrasting latitudinal gradients of body size in helminth parasites and their hosts"

description: This contains code and data to reproduce the analyses from <br>&gt; Dallas, T. et al. 2018. "Contrasting latitudinal gradients of body size in helminth parasites and their hosts"<br>Please cite the original data providers for the NHM helminth data, the Pantheria database, the climate layers, etc.
DOI: 10.6084/m9.figshare.16892610
title: Building optimization testing framework (BOPTEST) for simulation-based benchmarking of control strategies in buildings

description: Development of new building HVAC control algorithms has grown due to needs for energy efficiency and operational flexibility. However, case studies demonstrating new algorithms are largely individualized, making algorithm performance difficult to compare directly. In addition, the effort and expertise required to implement case studies in real or simulated buildings limits rapid prototyping potential. Therefore, this paper presents the Building Optimization Testing Framework (BOPTEST) and associated software for simulation-based benchmarking of building HVAC control algorithms. A containerized run-time environment (RTE) enables rapid, repeatable deployment of common building emulators representing different system types. Emulators use Modelica to represent realistic physical dynamics, embed baseline control, and enable overwriting supervisory and local-loop control signals. Finally, a common set of key performance indicators are calculated within the RTE and reported to the user. This paper details the design and implementation of software and demonstrates its usage to benchmark a Model Predictive Control strategy.
DOI: 10.6084/m9.figshare.12174141
title: Affiliations

description: CSV file containing affiliations and their extracted fine-grained items. It correspond to the Table 8 in the article.
DOI: 10.6084/m9.figshare.12174141.v1
title: Affiliations

description: CSV file containing affiliations and their extracted fine-grained items. It correspond to the Table 8 in the article.
DOI: 10.6084/m9.figshare.22655388.v1
title: Additional file 2 of Integrative analysis of TP53 mutations in lung adenocarcinoma for immunotherapies and prognosis

description: Additional file 2. ST1. Information of TP53 TOP10 mutation frequency. The top 10 information items of TP53 mutations stored by mutation frequency in TP53 include mutation location, mutation type, codon variation, number of mutation samples, and mutation frequency.
DOI: 10.6084/m9.figshare.22655268.v1
title: Additional file 7 of Identification of a m6A-related ferroptosis signature as a potential predictive biomarker for lung adenocarcinoma

description: Additional file 7: Supplementary Table 5. The raw data used to generate Figure 5A,C,E,G.
DOI: 10.6084/m9.figshare.22655274.v1
title: Additional file 9 of Identification of a m6A-related ferroptosis signature as a potential predictive biomarker for lung adenocarcinoma

description: Additional file 9: Supplementary Table 6-S2. The raw data used to generate Figure 6B-D.
DOI: 10.6084/m9.figshare.21995069.v5
title: Files for Main Figure 4

description: GSVA scores with DNA/RNA sensing genesDNA_RNA_gene_TE_cor_GSVA_telescope: Correlation between GSVA score of DNA/RNA sensing genes with TEs quantified by TelescopeDNA_RNA_gene_TE_cor_GSVA_LocusMasterTE: Correlation between GSVA score of DNA/RNA sensing genes with TEs quantified by LocusMasterTECorrelation with intergenic TEs and nearby Genescorrelation_intergenic_TEs_Gene: Spearman correlation between intergenic TEs and nearby GenesLocusMasterTE_cor: correlation score between intergenic TEs quantified by LocusMasterTEs and GenesTelescope_cor: correlation score between intergenic TEs quantified by Telescope and GenesSurvival AnalysisTCGA_COAD_log2TPM_Gene: log2TPM values of GenesTCGA_COAD_log2TPM_TE: log2TPM values of TEs quantified by LocusMasterTETEs_catpured_only_by_LocusMasterTE: A list of TEs captured exclusively by LocusMasterTEInverted SINE mutational Signaturemutational_profile_TCGA-COAD: mutational profiles of TCGA-COAD tumor samples and inverted SINE sample
DOI: 10.6084/m9.figshare.7975295.v1
title: Additional file 3: of Phyllosphere epiphytic and endophytic fungal community and network structures differ in a tropical mangrove ecosystem

description: Table S2. Comparison of the relative abundance of abundant operational taxonomic units (OTUs, &gt;â 1000 reads) between epiphytic and endophytic fungi. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.7975427
title: MOESM2 of Mutation of 4-coumarate: coenzyme A ligase 1 gene affects lignin biosynthesis and increases the cell wall digestibility in maize brown midrib5 mutants

description: Additional file 2: Table S2. SNPs with SNP-index 1 within the candidate genomic region detected on chromosome 5.
DOI: 10.6084/m9.figshare.22655342
title: Additional file 1 of FACI is a novel clathrin adaptor protein 2-binding protein that facilitates low-density lipoprotein endocytosis

description: Additional file 1: Table S1. Lists of reagents, plasmids, antibodies, and oligonucleotides.
DOI: 10.15156/bio/sh1050127.09fu
title: SH1050127.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1050128.09fu
title: SH1050128.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1050129.09fu
title: SH1050129.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1050130.09fu
title: SH1050130.09FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.