cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57745/quoygv
title: transvac-porc51-TM-X100E.tif

description: :unav
DOI: 10.57745/wkh5id
title: transvac-porc64-TM-X100.tif

description: :unav
DOI: 10.57745/5x2gcy
title: transvac-porc53-TM-X100.tif

description: :unav
DOI: 10.57745/nair02
title: transvac-porc52-TM-X100E.tif

description: :unav
DOI: 10.57745/oeyd6i
title: transvac-porc52-TM-X100.tif

description: :unav
DOI: 10.57745/t3xmgm
title: transvac-porc53-TM-X100E.tif

description: :unav
DOI: 10.57745/zy8v3x
title: transvac-porc51-TM-X100.tif

description: :unav
DOI: 10.57745/twgqzx
title: transvac-porc65-TM-X100E.tif

description: :unav
DOI: 10.57745/vfebgy
title: transvac-porc65-TM-X100.tif

description: :unav
DOI: 10.5281/zenodo.7113258
title: Dataset for FlexSNG project - publication CET2022 vol 92

description: Dataset (dataset 1.0) for FlexSNG; Refer to Article Development of a bubbling circulating fluidized-bed reactor for biomass and waste gasification (CET 2022 vol.92)
DOI: 10.5281/zenodo.7113257
title: Dataset for FlexSNG project - publication CET2022 vol 92

description: Dataset (dataset 1.0) for FlexSNG; Refer to Article Development of a bubbling circulating fluidized-bed reactor for biomass and waste gasification (CET 2022 vol.92)
DOI: 10.6084/m9.figshare.21206576
title: Additional file 1 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 1. Table with DEGs in the differentiating gonads of the European sea bass between males and females.
DOI: 10.6084/m9.figshare.21206579
title: Additional file 2 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 2. Table with DEGs in the differentiating gonads of the mouse between males and females.
DOI: 10.6084/m9.figshare.21206582.v1
title: Additional file 3 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 3. Table of co-expressed DEGs in the differentiating gonads of the European sea bass between males and females.
DOI: 10.6084/m9.figshare.21206576.v1
title: Additional file 1 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 1. Table with DEGs in the differentiating gonads of the European sea bass between males and females.
DOI: 10.6084/m9.figshare.21206579.v1
title: Additional file 2 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 2. Table with DEGs in the differentiating gonads of the mouse between males and females.
DOI: 10.6084/m9.figshare.21206582
title: Additional file 3 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 3. Table of co-expressed DEGs in the differentiating gonads of the European sea bass between males and females.
DOI: 10.6084/m9.figshare.21206585.v1
title: Additional file 4 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 4. Table of co-expressed DEGs in the differentiating gonads of the mouse between males and females.
DOI: 10.6084/m9.figshare.21206588
title: Additional file 5 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 5. Significant GO terms enriched from the co-expressed DEGs in the differentiating gonads of the mouse between males and females.
DOI: 10.6084/m9.figshare.21206588.v1
title: Additional file 5 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 5. Significant GO terms enriched from the co-expressed DEGs in the differentiating gonads of the mouse between males and females.
DOI: 10.6084/m9.figshare.21206585
title: Additional file 4 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 4. Table of co-expressed DEGs in the differentiating gonads of the mouse between males and females.
DOI: 10.6084/m9.figshare.21206591
title: Additional file 6 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 6. Key genes involved in the gonadal development of the European sea bass and other teleosts. Data compiled from [93, 111].
DOI: 10.6084/m9.figshare.21206591.v1
title: Additional file 6 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 6. Key genes involved in the gonadal development of the European sea bass and other teleosts. Data compiled from [93, 111].
DOI: 10.6084/m9.figshare.21206594
title: Additional file 7 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 7. Key genes involved in the gonadal development of the mouse. Data compiled from [93, 114, 117].
DOI: 10.6084/m9.figshare.21206594.v1
title: Additional file 7 of Improved biomarker discovery through a plot twist in transcriptomic data analysis

description: Additional file 7. Key genes involved in the gonadal development of the mouse. Data compiled from [93, 114, 117].
DOI: 10.6084/m9.figshare.21206605
title: Additional file 1 of Public health genomics capacity assessment: readiness for large-scale pathogen genomic surveillance in Canada’s public health laboratories

description: Additional file 1. Full data set: themes and responses from focus group discussions.
DOI: 10.6084/m9.figshare.21206605.v1
title: Additional file 1 of Public health genomics capacity assessment: readiness for large-scale pathogen genomic surveillance in Canada’s public health laboratories

description: Additional file 1. Full data set: themes and responses from focus group discussions.
DOI: 10.5517/ccdc.csd.cc24hfhl
title: CCDC 1981039: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Hurlock, Leiduan Hao, Kyle W. Kriegsman, Xiaofeng Guo, Michael O’Keeffe, Qiang Zhang|2021|ACS Applied Materials and Interfaces|13|51945|doi:10.1021/acsami.1c07701
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b7gsv
title: CCDC 2152137: Experimental Crystal Structure Determination

description: Related Article: Xiao Han|2022|CSD Communication|||
description: Related Article: Congqi Li, Xiaobin Gu, Zhihao Chen, Xiao Han, Na Yu, Yanan Wei, Jinhua Gao, Hao Chen, Meng Zhang, Ao Wang, Jianqi Zhang, Zhixiang Wei, Qian Peng, Zheng Tang, Xiaotao Hao, Xin Zhang, Hui Huang|2022|J.Am.Chem.Soc.|144|14731|doi:10.1021/jacs.2c05303
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b7gtw
title: CCDC 2152138: Experimental Crystal Structure Determination

description: Related Article: Xiao Han|2022|CSD Communication|||
description: Related Article: Congqi Li, Xiaobin Gu, Zhihao Chen, Xiao Han, Na Yu, Yanan Wei, Jinhua Gao, Hao Chen, Meng Zhang, Ao Wang, Jianqi Zhang, Zhixiang Wei, Qian Peng, Zheng Tang, Xiaotao Hao, Xin Zhang, Hui Huang|2022|J.Am.Chem.Soc.|144|14731|doi:10.1021/jacs.2c05303
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2by83p
title: CCDC 2173072: Experimental Crystal Structure Determination

description: Related Article: Junyao Zhang|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2by48q
title: CCDC 2172953: Experimental Crystal Structure Determination

description: Related Article: Antonio Buzharevski, Peter Lönnecke, Evamarie Hey-Hawkins|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2by7k3
title: CCDC 2173055: Experimental Crystal Structure Determination

description: Related Article: Shi Xiaolin|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2by8td
title: CCDC 2173094: Experimental Crystal Structure Determination

description: Related Article: Lixia Chen|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2byb8x
title: CCDC 2173139: Experimental Crystal Structure Determination

description: Related Article: Anquan Li, Kelong Zhu|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2byb9y
title: CCDC 2173140: Experimental Crystal Structure Determination

description: Related Article: Anquan Li, Kelong Zhu|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bybbz
title: CCDC 2173141: Experimental Crystal Structure Determination

description: Related Article: Anquan Li, Kelong Zhu|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2byhg8
title: CCDC 2173300: Experimental Crystal Structure Determination

description: Related Article: Sergely Steephen Bokouende, Cassandra L. Ward, Matthew J. Allen|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2byhld
title: CCDC 2173304: Experimental Crystal Structure Determination

description: Related Article: Yingyu Li|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2byj2x
title: CCDC 2173319: Experimental Crystal Structure Determination

description: Related Article: Antonio Buzharevski, Peter Lönnecke, Evamarie Hey-Hawkins|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.21206567
title: 4_5859208124803583508.sav

description: data set
DOI: 10.6084/m9.figshare.21206567.v1
title: 4_5859208124803583508.sav

description: data set
DOI: 10.20372/nadre/20575
title: Ethiopian Socio Economic Survey Agriculture Post Harvest Questionnaire - Dataset

description: Ethiopian Socio Economic Survey Agriculture Post Harvest Questionnaire - Dataset
DOI: 10.20372/nadre/20574
title: Ethiopian Socio Economic Survey Agriculture Post Harvest Questionnaire - Dataset

description: Ethiopian Socio Economic Survey Agriculture Post Harvest Questionnaire - Dataset
DOI: 10.6084/m9.figshare.21206690
title: Additional file 10 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 10. Vectors and CRISPR/Cas9 constructs used in the present study.
DOI: 10.6084/m9.figshare.21206690.v1
title: Additional file 10 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 10. Vectors and CRISPR/Cas9 constructs used in the present study.
DOI: 10.6084/m9.figshare.21206702
title: Additional file 14 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 14. Shotgun proteomics: List of quantified proteins and numerical data.
DOI: 10.6084/m9.figshare.21206702.v1
title: Additional file 14 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 14. Shotgun proteomics: List of quantified proteins and numerical data.
DOI: 10.6084/m9.figshare.21206708.v1
title: Additional file 2 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 2. Numerical data and statistics of regressions of YFP reporter data associated with Figs. 1, 2, and 3.
DOI: 10.6084/m9.figshare.21206711
title: Additional file 3 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 3. Numerical data of maltase activity assays associated with Figures S6-S7.
DOI: 10.6084/m9.figshare.21206711.v1
title: Additional file 3 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 3. Numerical data of maltase activity assays associated with Figures S6-S7.
DOI: 10.6084/m9.figshare.21206714
title: Additional file 4 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 4. Numerical data of glucan measurements associated with Fig. 4.
DOI: 10.6084/m9.figshare.21206714.v1
title: Additional file 4 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 4. Numerical data of glucan measurements associated with Fig. 4.
DOI: 10.6084/m9.figshare.21206720
title: Additional file 5 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 5. Numerical data of chain-length distributions and lambda max values associated with Fig. 5.
DOI: 10.6084/m9.figshare.21206720.v1
title: Additional file 5 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 5. Numerical data of chain-length distributions and lambda max values associated with Fig. 5.
DOI: 10.6084/m9.figshare.21206723
title: Additional file 6 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 6. Targeted proteomics - Numerical data of Fig. 6 and information on proteins, surrogate peptides, transitions and runs.
DOI: 10.6084/m9.figshare.21206723.v1
title: Additional file 6 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 6. Targeted proteomics - Numerical data of Fig. 6 and information on proteins, surrogate peptides, transitions and runs.
DOI: 10.6084/m9.figshare.21206726
title: Additional file 7 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 7. Numerical data of Western blot quantification associated with Figures S12-S13.
DOI: 10.6084/m9.figshare.21206726.v1
title: Additional file 7 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 7. Numerical data of Western blot quantification associated with Figures S12-S13.
DOI: 10.6084/m9.figshare.21206729
title: Additional file 8 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 8. Numerical data of SS/BE2 ratios associated with Fig. 7.
DOI: 10.6084/m9.figshare.21206729.v1
title: Additional file 8 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 8. Numerical data of SS/BE2 ratios associated with Fig. 7.
DOI: 10.6084/m9.figshare.21206732
title: Additional file 9 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 9. Yeast strains, plant lines and antibodies used in the present study.
DOI: 10.6084/m9.figshare.21206732.v1
title: Additional file 9 of Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

description: Additional file 9. Yeast strains, plant lines and antibodies used in the present study.
DOI: 10.6084/m9.figshare.21206774
title: Additional file 4 of Impact of adaptive filtering on power and false discovery rate in RNA-seq experiments

description: Additional file 4. Example code for real data example for programming language R.
DOI: 10.6084/m9.figshare.21206774.v1
title: Additional file 4 of Impact of adaptive filtering on power and false discovery rate in RNA-seq experiments

description: Additional file 4. Example code for real data example for programming language R.
DOI: 10.6084/m9.figshare.21206798
title: Additional file 2 of Transcriptomic and proteomic analyses provide insights into the adaptive responses to the combined impact of salinity and alkalinity in Gymnocypris przewalskii

description: Additional file 2: Background genelist for GO annotation.
DOI: 10.6084/m9.figshare.21206798.v1
title: Additional file 2 of Transcriptomic and proteomic analyses provide insights into the adaptive responses to the combined impact of salinity and alkalinity in Gymnocypris przewalskii

description: Additional file 2: Background genelist for GO annotation.
DOI: 10.6084/m9.figshare.21206801
title: Additional file 3 of Transcriptomic and proteomic analyses provide insights into the adaptive responses to the combined impact of salinity and alkalinity in Gymnocypris przewalskii

description: Additional file 3: Background genelist for KEGG analyses.
DOI: 10.6084/m9.figshare.21206801.v1
title: Additional file 3 of Transcriptomic and proteomic analyses provide insights into the adaptive responses to the combined impact of salinity and alkalinity in Gymnocypris przewalskii

description: Additional file 3: Background genelist for KEGG analyses.
DOI: 10.21227/9et2-7308
title: Dynamic Offset Metric on Heterogeneous Information Networks for Cold-start Recommendation

description: The cold start problem is a significant challenge in recommendation systems. Traditional methods are ineffective when the amount of interaction data is small. Further, as meta-learning has achieved increasingly remarkablesuccess in few-shot classification, some studies in recent years has abstracted cold-start recommendations into few-shot problems and applied meta-learning-based approaches, but mostly, simple transplants of generic approaches have been adopted. Owing to the differences in problem definition, the more effective meta-learning methods represented by metric learning are not directly adaptable to the rating prediction problem. Furthermore, a heterogeneous information network (HIN), as a high-order graph structure, can capture more semantic information even in data-starved conditions. From the data perspective, efficient use of HINs can alleviate the cold-start dilemma. Hence, this study successfully combines metric learning and HIN to propose OMHIN, a Dynamic Offset Metric approach to Heterogeneous Information Networks for solving cold-start recommendations at both the model structure and data representation levels. We transform a direct similarity metric into an indirect metric to improve the robustness of our model. The flexible application of one-dimensional convolution enables OMHIN to integrate the rich information contained in the HIN effectively while avoiding the introduction of excessive noise. Experiments on two datasets validate that OMHIN achieves state-of-the-art performance in a variety of scenarios, with significant improvements in complex and difficult scenarios, and is therefore especially well-suited for use in sequence cold-start recommendations.