cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6555463
title: Pixelated Reconstruction of Gravitational Lenses using Recurrent Inference Machine

description: Modeling strong gravitational lenses to quantify the distortions of the background sources and reconstruct the mass density in the foreground lens has traditionally been a major computational challenge. As the quality of gravitational lens images increases, the task of fully exploiting the information they contain becomes computationally and algorithmically more difficult. In order to tackle this challenge, we have trained a Recurrent Inference Machine (RIM) on a large dataset of realistic gravitational lenses simulated from galaxy images from the COSMOS survey and convergence maps from the IllustrisTNG simulation. This dataset contains the dataset used to train the RIM and the Variational AutoEncoder (VAE) used in our work, Pixelated Reconstruction of Gravitational Lenses using Recurrent Inference Machine, presented at the Machine Learning for Astrophysics Workshop at the Thirty-ninth International Conference on Machine Learning (ICML 2022), as well as the checkpoint files for the neural networks. The source code for our work is published under the package name Censai.
DOI: 10.5281/zenodo.6555462
title: Pixelated Reconstruction of Gravitational Lenses using Recurrent Inference Machine

description: Modeling strong gravitational lenses to quantify the distortions of the background sources and reconstruct the mass density in the foreground lens has traditionally been a major computational challenge. As the quality of gravitational lens images increases, the task of fully exploiting the information they contain becomes computationally and algorithmically more difficult. In order to tackle this challenge, we have trained a Recurrent Inference Machine (RIM) on a large dataset of realistic gravitational lenses simulated from galaxy images from the COSMOS survey and convergence maps from the IllustrisTNG simulation. This dataset contains the dataset used to train the RIM and the Variational AutoEncoder (VAE) used in our work, Pixelated Reconstruction of Gravitational Lenses using Recurrent Inference Machine, presented at the Machine Learning for Astrophysics Workshop at the Thirty-ninth International Conference on Machine Learning (ICML 2022), as well as the checkpoint files for the neural networks. The source code for our work is published under the package name Censai.
DOI: 10.6084/m9.figshare.17430701
title: Supplementary Table 1

description: microRNA expression immobilized vs nonimmobilized limb of FAP-derived EVs in wild-type mice.<br>
DOI: 10.6084/m9.figshare.17430707.v2
title: Supplementary Table 3

description: microRNA expression immobilized vs nonimmobilized limb of FAP-derived EVs in IL-1B KO mice.
DOI: 10.6084/m9.figshare.17430707
title: Supplementary Table 3

description: microRNA expression immobilized vs nonimmobilized limb of FAP-derived EVs in IL-1B KO mice.
DOI: 10.6084/m9.figshare.19874227
title: Supplementary Table 2

description: Proteins decreased or increased in skeletal muscle with single hindlimb immobilization.
DOI: 10.6084/m9.figshare.17430701.v2
title: Supplementary Table 1

description: microRNA expression immobilized vs nonimmobilized limb of FAP-derived EVs in wild-type mice.<br>
DOI: 10.6084/m9.figshare.17430707.v1
title: Supplementary Table 2

description: microRNA expression immobilized vs nonimmobilized limb of FAP-derived EVs in IL-1B KO mice.
DOI: 10.6084/m9.figshare.17430701.v1
title: Supplementary Table 1

description: microRNA expression immobilized vs nonimmobilized limb of FAP-derived EVs in wild-type mice.<br>
DOI: 10.6084/m9.figshare.19525471
title: Presence_absence_data_Plasmid_gene_matrix

description: Presence absence data for the plasmid gene matrix with each sample as a row and each gene as a column. It shows plasmid interactomes for all bacterial samples across all unique plasmid-derived genes. The axes were sorted alphabetically.
DOI: 10.6084/m9.figshare.19525471.v3
title: Presence_absence_data_Plasmid_gene_matrix

description: Presence absence data for the plasmid gene matrix with each sample as a row and each gene as a column. It shows plasmid interactomes for all bacterial samples across all unique plasmid-derived genes. The axes were sorted alphabetically.
DOI: 10.6084/m9.figshare.19525471.v2
title: Presence_absence_data_Plasmid_gene_matrix

description: Presence absence data for the plasmid gene matrix with each sample as a row and each gene as a column. This links to Figure S5. It shows plasmid interactomes for all bacterial samples across all unique plasmid-derived genes. The axes were sorted alphabetically.
DOI: 10.5281/zenodo.6797634
title: Imaging data (part 1) for the manuscript "Pregnancy-induced maternal microchimerism shapes neurodevelopment and behavior in mice"

description: This archive contains part 1 of the raw imaging data of the manuscript "Pregnancy-induced maternal microchimerism shapes neurodevelopment and behavior in mice".
DOI: 10.5281/zenodo.6797633
title: Imaging data (part 1) for the manuscript "Pregnancy-induced maternal microchimerism shapes neurodevelopment and behavior in mice"

description: This archive contains part 1 of the raw imaging data of the manuscript "Pregnancy-induced maternal microchimerism shapes neurodevelopment and behavior in mice".
DOI: 10.35077/tip
title: fMOST_182448

description: This dataset comes from combining genetic labeling with fMOST to achieve a genetically targeted single neuron saturation screen of major classes of cortical projection neurons in the sensorimotor system.
description: DATASET METADATA: title:'fMOST_182448', GeneralModality:'cell morphology', Technique:'fMOST' SPECIMEN METADATA: LocalID:'182448', Species:'mouse', NCBITaxonomy:'NCBI:txid10090', Age:'14', Ageunit:'Weeks', Sex:'Female', Genotype:'Fezf2-creER+LSL-flp', OrganName:'Brain', Locations:'brain' INSTRUMENT METADATA: MicroscopeType:'fMOST' IMAGE METADATA: yAxis:'inferior-to-superior', zAxis:'anterior-to-posterior', Number:'1, gray', displayColor:'(0.8, 0.8, 0.8)', stepSizeX:'0.35 micron/pixel', stepSizeY:'0.35 micron/pixel', stepSizeZ:'1 micron/pixel'
DOI: 10.34740/kaggle/dsv/3905516
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.6475667
title: CView: test case dataset

description: <strong>Summary</strong> All North American subtype B gp120 sequences, verified to be CCR5-using sequences (n = 636), were downloaded from the Los Alamos HIV sequence database in aligned fasta format [1]. These were loaded into CView, using the “Load (fasta)” option of the “All Sequences” menu, following which they were saved in unaligned format using the “Save (unaligned)” option of the “All Sequences” menu. Additionally, the titles of these sequences were saved to a separate file using the “Save (titles)” option. This was repeated for CXCR4-using sequences (n = 76). In order to make sites directly comparable between the two sets of unaligned sequences, they were combined into a single file and aligned using MUSCLE [2]. This alignment was used in the test case example of our CView paper [3] titled “<em>CView: A network based tool for enhanced alignment visualization</em>” (view). The CView project page is located at: https://sourceforge.net/projects/cview/ A poster sumarization presented at ISMB 2022 is available here. <strong>Tutorials</strong> 1. A demonstration of CView usage in the form of an mp4 movie is available here. 2. A demonstration of how variants can be identified using CView is available here. Related software to this project are:<br> 1. CStone <br> 2. CSReadGen<br> 3. CView &lt;<br> 4. ChimSim<br> 5. TVScript General details of the project are available here. <strong>References</strong> 1. Kuiken C, Korber B, Shafer RW. HIV Sequence Databases. AIDS Rev. 2003;5: 52. Available: /pmc/articles/PMC2613779/ 2. Edgar R. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32: 1792–1797. doi:10.1093/NAR/GKH340 3. Linheiro, R., Sabatino, S., LoboID, D., & ArcherID, J. (2022). CView: A network based tool for enhanced alignment visualization. <em>PLOS ONE</em>, <em>17</em>(6), e0259726. https://doi.org/10.1371/JOURNAL.PONE.0259726 <strong>| linkedIn . web . orcid |</strong><br> | linheiro . web . orcid |---| sabatino . web . orcid |---| lobo . web . orcid |---| archer . web . orcid |
description: This work was funded by the project NORTE-01-0246-FEDER-000063, supported by Norte Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by research funding from the project under the references PTDC/BIA-EVF/29115/2017 and POCI-01-0145-FEDER-029115 co-funded by Operational Competitiveness and Internationalization Program, Portugal 2020 and the European Union via the European Regional Development Fund (ERDF), and by National Funds through FCT. DL was supported by FCT through a PhD grant with the reference PD/BD/132403/2017. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. FCT URL: https://www.fct.pt/.
DOI: 10.5281/zenodo.6475666
title: CView: test case dataset

description: <strong>Summary</strong> All North American subtype B gp120 sequences, verified to be CCR5-using sequences (n = 636), were downloaded from the Los Alamos HIV sequence database in aligned fasta format [1]. These were loaded into CView, using the “Load (fasta)” option of the “All Sequences” menu, following which they were saved in unaligned format using the “Save (unaligned)” option of the “All Sequences” menu. Additionally, the titles of these sequences were saved to a separate file using the “Save (titles)” option. This was repeated for CXCR4-using sequences (n = 76). In order to make sites directly comparable between the two sets of unaligned sequences, they were combined into a single file and aligned using MUSCLE [2]. This alignment was used in the test case example of our CView paper [3] titled “<em>CView: A network based tool for enhanced alignment visualization</em>” (view). The CView project page is located at: https://sourceforge.net/projects/cview/ A poster sumarization presented at ISMB 2022 is available here. <strong>Tutorials</strong> 1. A demonstration of CView usage in the form of an mp4 movie is available here. 2. A demonstration of how variants can be identified using CView is available here. Related software to this project are:<br> 1. CStone <br> 2. CSReadGen<br> 3. CView &lt;<br> 4. ChimSim<br> 5. TVScript General details of the project are available here. <strong>References</strong> 1. Kuiken C, Korber B, Shafer RW. HIV Sequence Databases. AIDS Rev. 2003;5: 52. Available: /pmc/articles/PMC2613779/ 2. Edgar R. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32: 1792–1797. doi:10.1093/NAR/GKH340 3. Linheiro, R., Sabatino, S., LoboID, D., & ArcherID, J. (2022). CView: A network based tool for enhanced alignment visualization. <em>PLOS ONE</em>, <em>17</em>(6), e0259726. https://doi.org/10.1371/JOURNAL.PONE.0259726 <strong>| linkedIn . web . orcid |</strong><br> | linheiro . web . orcid |---| sabatino . web . orcid |---| lobo . web . orcid |---| archer . web . orcid |
description: This work was funded by the project NORTE-01-0246-FEDER-000063, supported by Norte Portugal Regional Operational Programme (NORTE2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by research funding from the project under the references PTDC/BIA-EVF/29115/2017 and POCI-01-0145-FEDER-029115 co-funded by Operational Competitiveness and Internationalization Program, Portugal 2020 and the European Union via the European Regional Development Fund (ERDF), and by National Funds through FCT. DL was supported by FCT through a PhD grant with the reference PD/BD/132403/2017. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. FCT URL: https://www.fct.pt/.
DOI: 10.6084/m9.figshare.20227533
title: Polyp-canal reconstruction reveals evolution towards complexity in corals (Dataset Part 147)

description: There are 17 files in this dataset. This is the 147th part of this dataset. The <em>A. millepora</em>, <em>A. muricata</em>,<em> C. vaughani</em>,<em> M. capricornis</em>, <em>M. foliosa</em>,<em> P. damicornis</em>, <em>P. meandrina</em>,<em> P. verrucosa</em>, and<em> S. pistillata</em> samples were collected from the Xisha Islands (2018); the <em>A. digitifera</em>, <em>F. speciosa </em>(2008), and<em> M. turgescens</em> (2017) samples were collected from the Nansha Islands; the <em>P. lutea</em> samples were collected from the Weizhou Islands (2017); the <em>G. fascicularis</em>, and<em> M. stellata </em>samples were collected from the Gaven Reef (2017); the <em>A. myriophthalma</em> samples were collected from the Reed Tablemount (2017); the <em>P. sinensis</em> samples were collected from the Subi Reef (2017). All samples, which occurred in large arborescent colonies forming thickets, were found in tropical shallow reefs of the marine neritic zone, from depths of about 5 to 10 m. The daily mean temperature was between 23.2 and 29.2°C. The coral samples were kept whole and housed in our laboratory coral tank, where all conditions were simulated to reflect those of their habitat in the South China Sea. These samples were kept in the tank for about one to three months before HRCT analysis.
DOI: 10.6084/m9.figshare.20227533.v1
title: Polyp-canal reconstruction reveals evolution towards complexity in corals (Dataset Part 147)

description: There are 17 files in this dataset. This is the 147th part of this dataset. The <em>A. millepora</em>, <em>A. muricata</em>,<em> C. vaughani</em>,<em> M. capricornis</em>, <em>M. foliosa</em>,<em> P. damicornis</em>, <em>P. meandrina</em>,<em> P. verrucosa</em>, and<em> S. pistillata</em> samples were collected from the Xisha Islands (2018); the <em>A. digitifera</em>, <em>F. speciosa </em>(2008), and<em> M. turgescens</em> (2017) samples were collected from the Nansha Islands; the <em>P. lutea</em> samples were collected from the Weizhou Islands (2017); the <em>G. fascicularis</em>, and<em> M. stellata </em>samples were collected from the Gaven Reef (2017); the <em>A. myriophthalma</em> samples were collected from the Reed Tablemount (2017); the <em>P. sinensis</em> samples were collected from the Subi Reef (2017). All samples, which occurred in large arborescent colonies forming thickets, were found in tropical shallow reefs of the marine neritic zone, from depths of about 5 to 10 m. The daily mean temperature was between 23.2 and 29.2°C. The coral samples were kept whole and housed in our laboratory coral tank, where all conditions were simulated to reflect those of their habitat in the South China Sea. These samples were kept in the tank for about one to three months before HRCT analysis.
DOI: 10.6084/m9.figshare.19672527.v1
title: All_PPIs_per_sample_per_gene

description: 4,377 samples' CSV files for all proteins showing the number index, gene name (Gene), plasmid status (Plasmid, where 0=plasmid-related), and total number of PPIs (Interactions) for each sample.
DOI: 10.34740/kaggle/dsv/3905561
title: 2021 World Population (updated daily)
DOI: 10.5517/ccdc.csd.cc28mzc8
title: CCDC 2104570: Experimental Crystal Structure Determination

description: Related Article: Kévin Saint-Jacques, Carolyn L. Ladd, André B. Charette|2022|Chem.Commun.|58|7550|doi:10.1039/D2CC01917E
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.cc28mzd9
title: CCDC 2104571: Experimental Crystal Structure Determination

description: Related Article: Kévin Saint-Jacques, Carolyn L. Ladd, André B. Charette|2022|Chem.Commun.|58|7550|doi:10.1039/D2CC01917E
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.19576408
title: xxx

description: The numbers of chromosomal and plasmid for 343 samples as PDF image files - the images were generated where there was sufficient plasmid-encoded PPI data to plot.
DOI: 10.6084/m9.figshare.19576408.v3
title: xxx

description: The numbers of chromosomal and plasmid for 343 samples as PDF image files - the images were generated where there was sufficient plasmid-encoded PPI data to plot.
DOI: 10.6084/m9.figshare.19576408.v2
title: Data for Figure S17.

description: The numbers of chromosomal and plasmid for 4,377 samples are available as CSV files and as 3,008 PDF image files - the images were generated where there was sufficient PPI data to plot.
DOI: 10.5517/ccdc.csd.cc2b04n5
title: CCDC 2145096: Experimental Crystal Structure Determination

description: Related Article: Ping Lu|2022|CSD Communication|||
description: Related Article: Meng Wang, Yingchao Huang, Chunyu Li, Ping Lu|2022|Org.Chem.Front.|9|2149|doi:10.1039/D2QO00167E
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: 10.5281/zenodo.6278237
title: High-resolution (250 m) dataset for drought assessment in India

description: Downscaled Land Surface Temperature for the 2000-2017 period.
DOI: 10.5281/zenodo.6259416
title: High-resolution (250 m) dataset for drought assessment in India

description: Downscaled Land Surface Temperature for the 2000-2017 period.
DOI: 10.5517/ccdc.csd.cc2bqhrb
title: CCDC 2166582: Experimental Crystal Structure Determination

description: Related Article: Yoon-Jung Jang, Leire Sangroniz, Marc A. Hillmyer|2022|Polym.Chem.|13|3882|doi:10.1039/D2PY00479H
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.cc2bqhsc
title: CCDC 2166583: Experimental Crystal Structure Determination

description: Related Article: Yoon-Jung Jang, Leire Sangroniz, Marc A. Hillmyer|2022|Polym.Chem.|13|3882|doi:10.1039/D2PY00479H
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.cc2bqhtd
title: CCDC 2166584: Experimental Crystal Structure Determination

description: Related Article: Yoon-Jung Jang, Leire Sangroniz, Marc A. Hillmyer|2022|Polym.Chem.|13|3882|doi:10.1039/D2PY00479H
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.cc2brbyd
title: CCDC 2167394: Experimental Crystal Structure Determination

description: Related Article: Yu-Hang Miao, Yuan-Zhao Hua, Hao-Jie Gao, Nan-Nan Mo, Min-Can Wang, Guang-Jian Mei|2022|Chem.Commun.|58|7515|doi:10.1039/D2CC02458F
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: 10.5281/zenodo.6796226
title: High-resolution (250 m) dataset for drought assessment in India

description: <strong>We downscaled MODIS (MOD11A2) LST 1000 m to 250 m using the co-kriging method (Pardo-Igúzquiza et al., 2006), <br> and calculated various agriculture drought indices from the downscaled LST and EVI at 250 m.<br> The downscaled LST was then combined with EVI to evaluate various drought indices over India. </strong>
DOI: 10.5281/zenodo.6261354
title: High-resolution (250 m) dataset for drought assessment in India

description: <strong>We downscaled MODIS (MOD11A2) LST 1000 m to 250 m using the co-kriging method (Pardo-Igúzquiza et al., 2006), <br> and calculated various agriculture drought indices from the downscaled LST and EVI at 250 m.<br> The downscaled LST was then combined with EVI to evaluate various drought indices over India. </strong>
DOI: 10.6084/m9.figshare.19611279
title: Data

description: Data
DOI: 10.6084/m9.figshare.19611279.v2
title: Data

description: Data
DOI: 10.6084/m9.figshare.19611279.v1
title: Data for Figure S11

description: Data for Figure S11 - Heatmap of the basis coefficient matrices, reflecting the probability of allocation of the 1,713 samples (y-axis) to 29 different groups (x-axis) based on their plasmid PPI rates using NMF.
DOI: 10.6084/m9.figshare.19525597
title: Figu

description: Figu
DOI: 10.6084/m9.figshare.19525597.v4
title: Figu

description: Figu
DOI: 10.6084/m9.figshare.19525597.v3
title: Figure_S10_NMF_mixtureCoefficientMatrix

description: Figure S10. The frequency distributions of the rate of allocation of 989 plasmid-encoded genes to each of seven ranks from NMF based on presence or absence in 389 samples. The x-axes show the log10-scaled probability of allocation to each rank. 664, 377, 161, 475, 377, 192 and 270 plasmid-encoded genes had high probabilities of being allocated to each rank, respectively.
DOI: 10.6084/m9.figshare.19525480
title: xxx

description: xxxxx
DOI: 10.6084/m9.figshare.19525480.v5
title: xxx

description: xxxxx
DOI: 10.6084/m9.figshare.19525480.v4
title: Figure_S9_NMF_metasamples

description: Figure S9. The frequency distributions of the rate of allocation of the 389 samples to each of seven ranks from NMF based on their presence-absence rates in 989 plasmid-encoded genes. The x-axes show the log10-scaled probability of allocation to each rank. 33, 74, 125, 102, 100, 99 and 180 samples had high probabilities of being allocated to each rank, respectively.
DOI: 10.6084/m9.figshare.19611285
title: Data

description: xxxx
DOI: 10.6084/m9.figshare.19611285.v2
title: Data

description: xxxx
DOI: 10.6084/m9.figshare.19611285.v1
title: Data for Figure S12

description: Data for Figure S12 - Heatmap of the mixture coefficient matrices, reflecting the probability of allocation of 4,032 plasmid-associated genes (x-axis) to 29 different groups (y-axis) based on their PPI rates in 1,713 samples using NMF.
DOI: 10.6084/m9.figshare.19525681
title: xxxx

description: xxxx
DOI: 10.6084/m9.figshare.19525681.v5
title: Table_S6_154_samples

description: Bacterial samples (154, 5% of total) with a much higher aPMNLE for all proteins than the chromosomal ones alone. This indicated that the plasmid-related proteins contributed more indirect PPIs.