cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc200svp
title: CCDC 1847812: Experimental Crystal Structure Determination

description: Related Article: Anton Shetnev, Angelina Osipyan, Sergey Baykov, Alexander Sapegin, Zhanna Chirkova, Michail Korsakov, Anél Petzer, Idalet Engelbrecht, Jacobus P. Petzer|2019|Bioorg.Med.Chem.Lett.|29|40|doi:10.1016/j.bmcl.2018.11.018
DOI: 10.5517/ccdc.csd.cc207s13
title: CCDC 1854514: Experimental Crystal Structure Determination

description: Related Article: Pratibha Kumari, Sanjay K. Verma, Shaikh M. Mobin|2019|Chem.Commun.|55|294|doi:10.1039/C8CC07429A
DOI: 10.5517/ccdc.csd.cc20c19r
title: CCDC 1857653: Experimental Crystal Structure Determination

description: Related Article: Houssein Amjaour, Zhihan Wang, Micah Mabin, Jenna Puttkammer, Sullivan Busch, Qianli R. Chu|2019|Chem.Commun.|55|214|doi:10.1039/C8CC08017H
DOI: 10.5517/ccdc.csd.cc20ll5d
title: CCDC 1864903: Experimental Crystal Structure Determination

description: Related Article: Hayden A. Evans, Jessica L. Andrews, Douglas H. Fabini, Molleigh B. Preefer, Guang Wu, Anthony K. Cheetham, Fred Wudl, Ram Seshadri|2019|Chem.Commun.|55|588|doi:10.1039/C8CC07536K
DOI: 10.5517/ccdc.csd.cc20ll6f
title: CCDC 1864904: Experimental Crystal Structure Determination

description: Related Article: Hayden A. Evans, Jessica L. Andrews, Douglas H. Fabini, Molleigh B. Preefer, Guang Wu, Anthony K. Cheetham, Fred Wudl, Ram Seshadri|2019|Chem.Commun.|55|588|doi:10.1039/C8CC07536K
DOI: 10.5517/ccdc.csd.cc20ll7g
title: CCDC 1864905: Experimental Crystal Structure Determination

description: Related Article: Hayden A. Evans, Jessica L. Andrews, Douglas H. Fabini, Molleigh B. Preefer, Guang Wu, Anthony K. Cheetham, Fred Wudl, Ram Seshadri|2019|Chem.Commun.|55|588|doi:10.1039/C8CC07536K
DOI: 10.5517/ccdc.csd.cc20ll8h
title: CCDC 1864906: Experimental Crystal Structure Determination

description: Related Article: Hayden A. Evans, Jessica L. Andrews, Douglas H. Fabini, Molleigh B. Preefer, Guang Wu, Anthony K. Cheetham, Fred Wudl, Ram Seshadri|2019|Chem.Commun.|55|588|doi:10.1039/C8CC07536K
DOI: 10.5517/ccdc.csd.cc20ll9j
title: CCDC 1864907: Experimental Crystal Structure Determination

description: Related Article: Hayden A. Evans, Jessica L. Andrews, Douglas H. Fabini, Molleigh B. Preefer, Guang Wu, Anthony K. Cheetham, Fred Wudl, Ram Seshadri|2019|Chem.Commun.|55|588|doi:10.1039/C8CC07536K
DOI: 10.5517/ccdc.csd.cc20rdfm
title: CCDC 1869530: Experimental Crystal Structure Determination

description: Related Article: Carlos J.A. Ribeiro, Jayakanth Kankanala, Jiashu Xie, Jessica Williams, Hideki Aihara, Zhengqiang Wang|2019|Bioorg.Med.Chem.Lett.|29|257|doi:10.1016/j.bmcl.2018.11.044
DOI: 10.5517/ccdc.csd.cc20tkdt
title: CCDC 1871606: Experimental Crystal Structure Determination

description: Related Article: Ryohei Yamakado, Haruna Ishibashi, Yukari Motoyoshi, Nobuhiro Yasuda, Hiromitsu Maeda|2019|Chem.Commun.|55|326|doi:10.1039/C8CC08205G
DOI: 10.5517/ccdc.csd.cc20tkfv
title: CCDC 1871607: Experimental Crystal Structure Determination

description: Related Article: Ryohei Yamakado, Haruna Ishibashi, Yukari Motoyoshi, Nobuhiro Yasuda, Hiromitsu Maeda|2019|Chem.Commun.|55|326|doi:10.1039/C8CC08205G
DOI: 10.5517/ccdc.csd.cc20tkgw
title: CCDC 1871608: Experimental Crystal Structure Determination

description: Related Article: Ryohei Yamakado, Haruna Ishibashi, Yukari Motoyoshi, Nobuhiro Yasuda, Hiromitsu Maeda|2019|Chem.Commun.|55|326|doi:10.1039/C8CC08205G
DOI: 10.5517/ccdc.csd.cc20tkhx
title: CCDC 1871609: Experimental Crystal Structure Determination

description: Related Article: Ryohei Yamakado, Haruna Ishibashi, Yukari Motoyoshi, Nobuhiro Yasuda, Hiromitsu Maeda|2019|Chem.Commun.|55|326|doi:10.1039/C8CC08205G
DOI: 10.5517/ccdc.csd.cc20tkjy
title: CCDC 1871610: Experimental Crystal Structure Determination

description: Related Article: Ryohei Yamakado, Haruna Ishibashi, Yukari Motoyoshi, Nobuhiro Yasuda, Hiromitsu Maeda|2019|Chem.Commun.|55|326|doi:10.1039/C8CC08205G
DOI: 10.5517/ccdc.csd.cc20tkkz
title: CCDC 1871611: Experimental Crystal Structure Determination

description: Related Article: Ryohei Yamakado, Haruna Ishibashi, Yukari Motoyoshi, Nobuhiro Yasuda, Hiromitsu Maeda|2019|Chem.Commun.|55|326|doi:10.1039/C8CC08205G
DOI: 10.5517/ccdc.csd.cc20tkl0
title: CCDC 1871612: Experimental Crystal Structure Determination

description: Related Article: Ryohei Yamakado, Haruna Ishibashi, Yukari Motoyoshi, Nobuhiro Yasuda, Hiromitsu Maeda|2019|Chem.Commun.|55|326|doi:10.1039/C8CC08205G
DOI: 10.5517/ccdc.csd.cc20vgx8
title: CCDC 1872490: Experimental Crystal Structure Determination

description: Related Article: Thomas Simler, Thomas J. Feuerstein, Ravi Yadav, Michael T. Gamer, Peter W. Roesky|2019|Chem.Commun.|55|222|doi:10.1039/C8CC08120D
DOI: 10.5517/ccdc.csd.cc20vgy9
title: CCDC 1872491: Experimental Crystal Structure Determination

description: Related Article: Thomas Simler, Thomas J. Feuerstein, Ravi Yadav, Michael T. Gamer, Peter W. Roesky|2019|Chem.Commun.|55|222|doi:10.1039/C8CC08120D
DOI: 10.5517/ccdc.csd.cc20vh0d
title: CCDC 1872493: Experimental Crystal Structure Determination

description: Related Article: Thomas Simler, Thomas J. Feuerstein, Ravi Yadav, Michael T. Gamer, Peter W. Roesky|2019|Chem.Commun.|55|222|doi:10.1039/C8CC08120D
DOI: 10.5281/zenodo.3525366
title: doclevel-MT-benchmark-discoMT2019

description: This release contains data sets for experiments with document-level machine translation. The data sets have been used in previous studies and provided here for replicability and comparison with other systems. The data sets are taken from the English-German news translation task at WMT 2019 and the English-German bitext in the OpenSubtitles collection v2016 from OPUS. All data sets are sentence aligned with corresponding lines being aligned to each other. Document boundaries are marked with empty lines (on both sides of the parallel corpus). The data set has been used in the following publication: <pre><code>@inproceedings{scherrer-tiedemann-loaiciga-2019, title = "Analysing concatenation approaches to document-level NMT in two different domains", author = {Scherrer, Yves and Tiedemann, J{\"o}rg and Lo{\'a}iciga, Sharid}, booktitle = "Proceedings of the Third Workshop on Discourse in Machine Translation", month = nov, year = "2019", address = "Hong-Kong", publisher = "Association for Computational Linguistics", } </code></pre> Please, cite that paper if you use the data set in your own work.
description: {"references": ["Scherrer, Tiedemann and Lo\u00e1iciga: \"Analysing concatenation approaches to document-level NMT in two different domains\", in Proceedings of DiscoMT2019 at EMNLP 2019, Hong-Kong"]}
DOI: 10.5281/zenodo.3525365
title: doclevel-MT-benchmark-discoMT2019

description: This release contains data sets for experiments with document-level machine translation. The data sets have been used in previous studies and provided here for replicability and comparison with other systems. The data sets are taken from the English-German news translation task at WMT 2019 and the English-German bitext in the OpenSubtitles collection v2016 from OPUS. All data sets are sentence aligned with corresponding lines being aligned to each other. Document boundaries are marked with empty lines (on both sides of the parallel corpus). The data set has been used in the following publication: <pre><code>@inproceedings{scherrer-tiedemann-loaiciga-2019, title = "Analysing concatenation approaches to document-level NMT in two different domains", author = {Scherrer, Yves and Tiedemann, J{\"o}rg and Lo{\'a}iciga, Sharid}, booktitle = "Proceedings of the Third Workshop on Discourse in Machine Translation", month = nov, year = "2019", address = "Hong-Kong", publisher = "Association for Computational Linguistics", } </code></pre> Please, cite that paper if you use the data set in your own work.
description: {"references": ["Scherrer, Tiedemann and Lo\u00e1iciga: \"Analysing concatenation approaches to document-level NMT in two different domains\", in Proceedings of DiscoMT2019 at EMNLP 2019, Hong-Kong"]}
DOI: 10.6073/pasta/209e0bda4bc8e5e56262f71878be957b
title: TeRaCON eight year mean of NPP, carbon pools, and soil flux:BioCON : Biodiversity, Elevated CO2, and N Enrichment

description: BioCON (Biodiversity, CO2, and Nitrogen) is an ecological experiment started in 1997 at the University of Minnesota's Cedar Creek Ecosystem Science Reserve. BioCON's goal is to explore the ways in which plant communities will respond to three environmental changes that are known to be occurring on a global scale: increasing nitrogen deposition, increasing atmospheric CO2, and decreasing biodiversity. Why Biodiversity, CO2, and Nitrogen? While there are many uncertainties in global change biology, there are also some well documented facts. Some of these are: 1. The amount of carbon dioxide (CO2) in the atmosphere is rising. Since the industrial revolution, the CO2 concentration in the atmosphere has increased from approximately 275 parts per million (ppm) to about 378 ppm today. This has been largely the result of fossil fuel burning. It is expected that CO2 levels will continue to rise, and that by the year 2050 these levels will be approximately 550 ppm. CO2 is the raw material for photosynthesis and is known to affect plant growth and development. 2. The amount of nitrogen moving through terrestrial ecosystems has increased in the recent past. While natural "background" levels of nitrogen fixation have remained constant, human additions to the system through fertilizer production and fossil fuel use have increased dramatically. Nitrogen is a key nutrient for plant growth and plays a critical role in plant community structure and composition in many environments. 3. Biodiversity levels are falling. While the research and data are not as complete as they are for CO2 and nitrogen, data indicate that the number of species globally, is being reduced. Perhaps more important for ecosystem function, diversity levels on local to regional scales have fallen due to land use change, biotic invasion and many other drivers. While much is known about how each of these factors affects ecosystem functioning, many questions remain. There is also little data on how these issues affect each other, and what emergent qualities may arise when systems are exposed to these changes simultaneously. BioCON seeks to address these issues with this multi-year study at Cedar Creek Ecosytem Science Preserve.
DOI: 10.25387/g3.13060790
title: Supplemental Material for McClanahan et al., 2020

description: Supplemental Video File S1: Time lapse video of dehydration, rehydration, and recovery of C. elegans. A 10 µL droplet of N2 worms in M9 buffer containing 15% trehalose was pipetted on a PDMS surface and dehydrated for 12 h. The dehydrated droplet was transferred to a seeded NGM plate for recovery. <br>Supplemental Protocol File S2: Detailed protocol for dehydration, freezing, rehydration, and recovery of <i>C. elegans.</i>
DOI: 10.25387/g3.13060790.v1
title: Supplemental Material for McClanahan et al., 2020

description: Supplemental Video File S1: Time lapse video of dehydration, rehydration, and recovery of C. elegans. A 10 µL droplet of N2 worms in M9 buffer containing 15% trehalose was pipetted on a PDMS surface and dehydrated for 12 h. The dehydrated droplet was transferred to a seeded NGM plate for recovery. <br>Supplemental Protocol File S2: Detailed protocol for dehydration, freezing, rehydration, and recovery of <i>C. elegans.</i>
DOI: 10.21227/gkpq-t832
title: Survey: Departamento de Ingeniería Biológica, Universidad de la República Uruguay (Course: Taller 1 — Change to Virtual Modality during COVID-19)

description: The dataset links to the survey performed on students and professors of Biological Engineering introductory course, as the Department of Biological Engineering, University of the Republic, Uruguay.
DOI: 10.17632/8ch6z2tncv.1
title: Data for: Correlation and causation between the intestinal microbiota and male morphotypes in the giant freshwater prawn Macrobrachium rosenbergii
DOI: 10.6084/m9.figshare.12999857
title: Rndom number generation

description: Random number data set for DSCI560 assignment 2
DOI: 10.6084/m9.figshare.12999857.v2
title: Rndom number generation

description: Random number data set for DSCI560 assignment 2
DOI: 10.6084/m9.figshare.12999857.v1
title: dsci560_hw2

description: Random number data set for DSCI560 assignment 2
DOI: 10.6084/m9.figshare.13067978
title: Micryletta Trees

description: Maximum likelihood tree newick files from this study.
DOI: 10.6084/m9.figshare.13067978.v1
title: Micryletta Trees

description: Maximum likelihood tree newick files from this study.
DOI: 10.6084/m9.figshare.13067930
title: Micryletta Alignments

description: Sequence alignments from this study.
DOI: 10.6084/m9.figshare.13067930.v1
title: Micryletta Alignments

description: Sequence alignments from this study.
DOI: 10.6084/m9.figshare.13067756
title: Supplemental Tables

description: Supplementary Tables associated with the manuscript "Phylogeny, Diversity, and Distribution of Micryletta (Anura: Microhylidae) in Myanmar".
DOI: 10.6084/m9.figshare.13067756.v1
title: Supplemental Tables

description: Supplementary Tables associated with the manuscript "Phylogeny, Diversity, and Distribution of Micryletta (Anura: Microhylidae) in Myanmar".
DOI: 10.25921/910v-v249
title: EK80 Water Column Sonar Data Collected During BordelonMC20
DOI: 10.15482/usda.adc/1520057
title: NAL_Test
DOI: 10.5281/zenodo.4073433
title: Preprocessing scripts and data for study: Identifying high-confidence capture Hi-C interactions using CHiCANE

description: Preprocessing scripts and processed data from CHi-C libraries generated from breast cancer cells (T47-D) and Megakaryoctye cells (MK).
DOI: 10.5281/zenodo.3930995
title: Preprocessing scripts and data for study: Identifying high-confidence capture Hi-C interactions using CHiCANE

description: Preprocessing scripts and processed data from CHi-C libraries generated from breast cancer cells (T47-D) and Megakaryoctye cells (MK).
DOI: 10.15482/usda.adc/1520058
title: NAL_Test
DOI: 10.15482/usda.adc/1520059
title: NAL_Test
DOI: 10.5517/ccdc.csd.cc20vh1f
title: CCDC 1872494: Experimental Crystal Structure Determination

description: Related Article: Thomas Simler, Thomas J. Feuerstein, Ravi Yadav, Michael T. Gamer, Peter W. Roesky|2019|Chem.Commun.|55|222|doi:10.1039/C8CC08120D
DOI: 10.5517/ccdc.csd.cc20vh2g
title: CCDC 1872495: Experimental Crystal Structure Determination

description: Related Article: Thomas Simler, Thomas J. Feuerstein, Ravi Yadav, Michael T. Gamer, Peter W. Roesky|2019|Chem.Commun.|55|222|doi:10.1039/C8CC08120D
DOI: 10.5517/ccdc.csd.cc20vgzb
title: CCDC 1872492: Experimental Crystal Structure Determination

description: Related Article: Thomas Simler, Thomas J. Feuerstein, Ravi Yadav, Michael T. Gamer, Peter W. Roesky|2019|Chem.Commun.|55|222|doi:10.1039/C8CC08120D
DOI: 10.5517/ccdc.csd.cc20kpbm
title: CCDC 1864040: Experimental Crystal Structure Determination

description: Related Article: Qinfen Gu|2018|CSD Communication|||
description: Related Article: Xiongfei Zheng, Yanjing Yang, Mengxuan Li, Fengqi Zhao, Qinfen Gu, Xiaohua Ma, Yanhui Guo|2019|Chem.Commun.|55|408|doi:10.1039/C8CC08300B
DOI: 10.5517/ccdc.csd.cc2160v4
title: CCDC 1882625: Experimental Crystal Structure Determination

description: Related Article: Ting Li, Yuhan Yang, Bo Li, Ping Yang|2019|Chem.Commun.|55|353|doi:10.1039/C8CC07659F
DOI: 10.5517/ccdc.csd.cc22gr3f
title: CCDC 1920794: Experimental Crystal Structure Determination

description: Related Article: Ahmed Abdelhameed, Xiaoping Liao, Craig A. McElroy, April C. Joice, Liva Rakotondraibe, Junan Li, Carla Slebodnick, Pu Guo, W. David Wilson, Karl A. Werbovetz|2020|Bioorg.Med.Chem.Lett.|30|126725|doi:10.1016/j.bmcl.2019.126725
DOI: 10.5281/zenodo.4073512
title: SimRoot Simulation Results - Root Hairs and Nitrogen

description: <strong><em>SimRoot</em> modeling data</strong> In order to investigate the relationships between changes in root hair phenotypes and N capture under different N and transpiration regimes, a maize root system with the primary root and lateral branches varying in root hair length and density were simulated in the functional-structural plant model <em>SimRoot</em>. <em>SimRoot</em> offers a realistic platform to simulate the effect of the whole root system and/or a specific root traits on plant growth and resource acquisition because it is equipped with both carbon and nutrient models (Lynch <em>et al.</em> 1997; Dathe <em>et al.</em> 2016). Root hair length was modified by varying root hair growth rate. We used a 1*1*1 mm cubic finite element grid for the simulations. Simulations were run for 15 days. Transpiration rate was modified to manipulate the mass flow component. Four levels of nitrate were used in the simulations corresponding to 20.8, 62.4, 104 and 145.6 kg ha<sup>-1</sup>. All root parameters except for the parameters of interest (root hair length, root hair density) were kept constant. This research was supported by grants from the Howard G. Buffett Foundation and the National Science Foundation-PGRP grant DBI 0820624 to JPL and Mahidol University to PS’s time for developing the manuscript.
DOI: 10.5281/zenodo.4073511
title: SimRoot Simulation Results - Root Hairs and Nitrogen

description: <strong><em>SimRoot</em> modeling data</strong> In order to investigate the relationships between changes in root hair phenotypes and N capture under different N and transpiration regimes, a maize root system with the primary root and lateral branches varying in root hair length and density were simulated in the functional-structural plant model <em>SimRoot</em>. <em>SimRoot</em> offers a realistic platform to simulate the effect of the whole root system and/or a specific root traits on plant growth and resource acquisition because it is equipped with both carbon and nutrient models (Lynch <em>et al.</em> 1997; Dathe <em>et al.</em> 2016). Root hair length was modified by varying root hair growth rate. We used a 1*1*1 mm cubic finite element grid for the simulations. Simulations were run for 15 days. Transpiration rate was modified to manipulate the mass flow component. Four levels of nitrate were used in the simulations corresponding to 20.8, 62.4, 104 and 145.6 kg ha<sup>-1</sup>. All root parameters except for the parameters of interest (root hair length, root hair density) were kept constant. This research was supported by grants from the Howard G. Buffett Foundation and the National Science Foundation-PGRP grant DBI 0820624 to JPL and Mahidol University to PS’s time for developing the manuscript.
DOI: 10.6084/m9.figshare.9782771.v1
title: Characteristics of Studies Inlcuded in Cochrane Oral Health Reviews

description: This data set includes characteristics of all systematic reviews and included studies of Cochrane Oral Health Group.<br>
DOI: 10.6084/m9.figshare.9782771
title: Iranian RCTs Inlcuded in Cochrane Systematic Reviews

description: This dataset includes characteristics of all Iranian RCTs included in Cochrane Systematic Reviews.<br>
DOI: 10.6084/m9.figshare.9782771.v3
title: Iranian RCTs Inlcuded in Cochrane Systematic Reviews

description: This dataset includes characteristics of all Iranian RCTs included in Cochrane Systematic Reviews.<br>
DOI: 10.6084/m9.figshare.9782771.v2
title: Iranian RCTs Inlcuded in Cochrane Systematic Reviews

description: This dataset includes characteristics of all Iranian RCTs included in Cochrane Systematic Reviews.<br>
DOI: 10.15490/fairdomhub.1.datafile.3892.1
title: Visualization of gap filling of subsystem "Metabolism of xenobiotics by cytochrome P450"

description: The reactions existing in the auto-generated draft model are shown in blue, and the manually filled gaps are shown in green. Comparing our draft model with the same subsystem from model iHepatocytes2322, the missing reactions are highlighted in pink. The pink dots indicate the parent toxicants.
DOI: 10.5281/zenodo.4073486
title: Nitrogen and phosphorus in water and sediments of small floodplain reservoirs

description: Nitrogen and phosphorus in water and sediments of small floodplain reservoirs
DOI: 10.5281/zenodo.4073485
title: Nitrogen and phosphorus in water and sediments of small floodplain reservoirs

description: Nitrogen and phosphorus in water and sediments of small floodplain reservoirs
DOI: 10.6084/m9.figshare.12191691
title: Supplementary data for Esterman et al (2020)

description: This dataset contains supplementary data for the bioinformatic analyses presented in:<br><br>Emma Esterman, Yuri I. Wolf, Roman Kogay, Eugene V. Koonin, and Olga Zhaxybayeva, “Phylogenetic evidence of headful packaging strategy in gene transfer agents” (under review)<br><br><b>File Descriptions:</b><br><br><b>254382_acc.zip:</b> GenBank accession numbers of the RcGTA TerL protein homologs that are taxonomically assigned to bacteria, archaea, or viruses and likely include both an ATPase (N terminal) and nuclease (C terminal) domains.<br><br><b>11051_tree_acc.zip: </b>GenBank accession numbers of amino acid sequences used for reconstruction of the tree shown in Figure 1.<br><br><b>252614_acc.zip:</b> GenBank accession numbers of the RcGTA TerL protein homologs that are represented by 11,051 TerLs on the phylogenetic tree.<br><br><b>terminase_alignment.zip:</b> Alignment of 11,051 amino acid sequences of terminases. The alignment is in FASTA format.<br><br><b>terminase_alignment.trimmed.zip:</b> Alignment of 11,051 amino acid sequences of TerLs, trimmed to remove all sites with more than 50% gaps and less than 10% amino acid similarity. The alignment is in FASTA format.<br><br><b>Figure1_tree.zip: </b>Phylogenetic tree of 11,051 terLs shown in Figure 1 in NEWICK format. aLRT support values are included as node labels.<br><b>terL_subtree_aligned.zip: </b>Alignment of 616 amino acid sequences of TerLs used to detect sites differentiating viruses and RcGTA-like proteins. The 616 TerLs are from the subtree shown on Figure 2. The alignment is in FASTA format.<br><b>IQ-Tree_Alignments.zip:</b> Alignments of 342 and 346 amino acid sequences of TerLs used to validate obtained phylogenetic patterns via IQ-TREE. The alignments are in FASTA format.<br><b>IQ-TREE_trees.zip:</b> Phylogenetic trees of 342 and 346 TerLs reconstructed in IQ-TREE. The trees are in NEWICK format. Ultrafast bootstrap support values are included as node labels.<br><br>