cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3958920
title: Generation of stable mammalian cell lines for the expression of proteins related to COVID-19 through random integration

description: Scientists centred around University of Oxford came together in the current COVID-19 pandemic to contribute to relevant studies collaboratively. Researchers with no prior experience in virology studies, myself included, had volunteered our time to contribute whichever way we can based on our field of expertise. The Biotech team of SGC Oxford, headed by Nicola Burgess-Brown had taken up the role of producing proteins used in serological assays, basic research to understand COVID-19 pathophysiology and hunt for treatment compounds. The initial production of these proteins was based on transient transfection of expression construct DNA into mammalian cells. This approach was laborious and consumed large amounts of plasmid DNA. Therefore, I volunteered to generate stable expression cell lines that will negate the constant need for transfection. I aimed to stably integrate the expression constructs into the genome of Expi293F human cells commonly used in large scale protein production. The expression constructs carried neomycin marker for selection in mammalian cells. Toxicity to the cells is not a concern in this case because the expressed proteins are secreted into the medium and do not build up in the cells. The expression constructs are randomly integrated into the genome mainly via non-homologous end-joining (NHEJ). An advantage of this approach is that molecular sub-cloning is not necessary. In order to maximise the rate of correct integration of the expression constructs, restriction digestion was performed to cut once between the expression cassette and antibiotic resistance cassette (refer to cartoon in Figure 1). Without this step, the construct DNA will be broken at a random position during the integration step, potentially disrupting the expression cassette. I have also tested the effect of actively creating double strand breaks (DSBs) in the genome of the cells on the integration efficiency. More DSBs in the genome might increase the incidence of NHEJ and integration of our constructs. This was achieved by co-transfection of AAVS1 CRISPR/eSpCas9(1.1) construct (refer to cartoon in Figure 1). The eSpCas9(1.1)_No_FLAG_AAVS1_T2 construct was a gift from Yannick Doyon (Addgene plasmid # 79888 ; http://n2t.net/addgene:79888 ; RRID:Addgene_79888) Please refer to my SGC opennotebook post for my other research work unrelated to the pandemic. https://openlabnotebooks.org/generation-of-stable-mammalian-cell-lines-for-the-expression-of-proteins-related-to-covid-19-through-random-integration/
DOI: 10.25403/upresearchdata.12611369
title: Cochlear Spiral Reference Framework (CSRF) v0.1

description: The Cochlear Spiral Reference Framework (CSRF) is a set of coefficients for 6th order polynomial equations to describe the cochlear spirals that are relevant to the construction of three-dimensional person-specific computational models of the cochlea. The polynomials provide references for each of the lateral, medial, superior, inferior, superolateral, inferolateral, medial spiral lamina and lateral spiral lamina spirals for as well as a set of predictor polynomials from which spirals that are obscured on low-resolution clinical images may be derived.<br>The files ReconSummary_?.xls are the reconstruction polynomials for obscured spirals according to taxonomical class (roller coaster = R, intermediate = I, sloping = S) and for the pooled = P data. <br>The file MeanSpirals.xls contains the polynomial description for the cochlear spirals according to the three classes and for the pooled datasets.
DOI: 10.25403/upresearchdata.12611369.v2
title: Cochlear Spiral Reference Framework (CSRF) v0.1

description: The Cochlear Spiral Reference Framework (CSRF) is a set of coefficients for 6th order polynomial equations to describe the cochlear spirals that are relevant to the construction of three-dimensional person-specific computational models of the cochlea. The polynomials provide references for each of the lateral, medial, superior, inferior, superolateral, inferolateral, medial spiral lamina and lateral spiral lamina spirals for as well as a set of predictor polynomials from which spirals that are obscured on low-resolution clinical images may be derived.<br>The files ReconSummary_?.xls are the reconstruction polynomials for obscured spirals according to taxonomical class (roller coaster = R, intermediate = I, sloping = S) and for the pooled = P data. <br>The file MeanSpirals.xls contains the polynomial description for the cochlear spirals according to the three classes and for the pooled datasets.
DOI: 10.5517/ccdc.csd.cc24yjl7
title: CCDC 1994589: Experimental Crystal Structure Determination

description: Related Article: Ju Hyun Hong, Seonah Kim, Hyunhee So, Ji Hye Lee, Hyonseok Hwang, Kang Mun Lee|2020|Dyes Pigm.|183|108706|doi:10.1016/j.dyepig.2020.108706
DOI: 10.5517/ccdc.csd.cc24yjm8
title: CCDC 1994590: Experimental Crystal Structure Determination

description: Related Article: Ju Hyun Hong, Seonah Kim, Hyunhee So, Ji Hye Lee, Hyonseok Hwang, Kang Mun Lee|2020|Dyes Pigm.|183|108706|doi:10.1016/j.dyepig.2020.108706
DOI: 10.5517/ccdc.csd.cc14l5sp
title: CCDC 1060162: Experimental Crystal Structure Determination

description: Related Article: Peng Yang, Jian Li, Li Sun, Ming Yao, Xiang Zhang, Wei-Lie Xiao, Jian-Hua Wang, Ping Tian, Han-Dong Sun, Pema-Tenzin Puno, Ang Li|2019|J.Am.Chem.Soc.|142|13701|doi:10.1021/jacs.9b09699
DOI: 10.5517/ccdc.csd.cc14ls7r
title: CCDC 1060734: Experimental Crystal Structure Determination

description: Related Article: Peng Yang, Jian Li, Li Sun, Ming Yao, Xiang Zhang, Wei-Lie Xiao, Jian-Hua Wang, Ping Tian, Han-Dong Sun, Pema-Tenzin Puno, Ang Li|2019|J.Am.Chem.Soc.|142|13701|doi:10.1021/jacs.9b09699
DOI: 10.5517/ccdc.csd.cc14l5vr
title: CCDC 1060164: Experimental Crystal Structure Determination

description: Related Article: Peng Yang, Jian Li, Li Sun, Ming Yao, Xiang Zhang, Wei-Lie Xiao, Jian-Hua Wang, Ping Tian, Han-Dong Sun, Pema-Tenzin Puno, Ang Li|2019|J.Am.Chem.Soc.|142|13701|doi:10.1021/jacs.9b09699
DOI: 10.5517/ccdc.csd.cc1j0dgd
title: CCDC 1400563: Experimental Crystal Structure Determination

description: Related Article: Peng Yang, Jian Li, Li Sun, Ming Yao, Xiang Zhang, Wei-Lie Xiao, Jian-Hua Wang, Ping Tian, Han-Dong Sun, Pema-Tenzin Puno, Ang Li|2019|J.Am.Chem.Soc.|142|13701|doi:10.1021/jacs.9b09699
DOI: 10.5281/zenodo.3992737
title: Supplementary material for "Modeling Difficulties in Data Modeling: Similarities and Differences between Experienced and Non-experienced Modelers"

description: This material supplements the following conference publication: Rosenthal, K., Strecker, S., Pastor, O.: Modeling Difficulties in Data Modeling: Similarities and Differences between Experienced and Non-experienced Modelers. In: ER 2020. Vienna, Austria (2020)
DOI: 10.5281/zenodo.3992736
title: Supplementary material for "Modeling Difficulties in Data Modeling: Similarities and Differences between Experienced and Non-experienced Modelers"

description: This material supplements the following conference publication: Rosenthal, K., Strecker, S., Pastor, O.: Modeling Difficulties in Data Modeling: Similarities and Differences between Experienced and Non-experienced Modelers. In: ER 2020. Vienna, Austria (2020)
DOI: 10.5281/zenodo.3989318
title: Cold and warm temperature advection mask for the Antarctic Circumnavigation Expedition from December 2016 – March 2017.

description: <strong>Dataset abstract</strong> This dataset contains a mask for the identification of cold and warm temperature advection along the Antarctic Circumnavigation Expedition (ACE) track based on a simple method using the difference between the sea surface and air temperature. This mask is a combination of measured air temperature and sea surface temperature during ACE. <strong>Dataset contents</strong> coldwarm_mask_1h.csv, data file, comma-separated values data_file_header.txt, metadata, text README.txt, metadata, text change_log.txt <strong>Dataset license</strong> This cold and warm temperature advection mask dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0 <strong>Change log</strong> v1.1 - data file updated using new input dataset of measured air and sea surface temperature data file modified README updated accordingly with details of processing and change_log.txt added change_log.txt file v1.0 - initial release of dataset
description: The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals.
DOI: 10.5281/zenodo.3973198
title: Cold and warm temperature advection mask for the Antarctic Circumnavigation Expedition from December 2016 – March 2017.

description: <strong>Dataset abstract</strong> This dataset contains a mask for the identification of cold and warm temperature advection along the Antarctic Circumnavigation Expedition (ACE) track based on a simple method using the difference between the sea surface and air temperature. This mask is a combination of measured air temperature and sea surface temperature during ACE. <strong>Dataset contents</strong> coldwarm_mask_1h.csv, data file, comma-separated values data_file_header.txt, metadata, text README.txt, metadata, text change_log.txt <strong>Dataset license</strong> This cold and warm temperature advection mask dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0 <strong>Change log</strong> v1.1 - data file updated using new input dataset of measured air and sea surface temperature data file modified README updated accordingly with details of processing and change_log.txt added change_log.txt file v1.0 - initial release of dataset
description: The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals.
DOI: 10.25625/eznvw8/jblj91
title: MAG 02_Prokka_based_annotation.tbl

description: Prokka-based annotation table with respect to MAG 02
DOI: 10.25625/eznvw8/7ue5pt
title: MAG 03_Prokka_based_annotation.tbl

description: Prokka-based annotation table with respect to MAG 03
DOI: 10.25625/eznvw8/gtqk0z
title: MAG 03_contigs_Prokka_designations.fna

description: Designation of contigs considered by Prokka with respect to MAG 03 (MAG 03 contigs as revealed by MaxBin are available at Genbank under accession number JACDZH000000000).
DOI: 10.25625/eznvw8/pnf7sd
title: MAG 04_Prokka_based_annotation.tbl

description: Prokka-based annotation table with respect to MAG 04
DOI: 10.25625/eznvw8/4mwrvm
title: MAG 02_contigs_Prokka_designations.fna

description: Designation of contigs considered by Prokka with respect to MAG 02 (MAG 02 contigs as revealed by MaxBin are available at Genbank under accession number JACDZG000000000).
DOI: 10.25625/eznvw8/qzdgj4
title: MAG 01_Prokka_based_annotation.tbl

description: Prokka-based annotation table with respect to MAG 01
DOI: 10.25625/eznvw8/czwjyz
title: MAG 01_contigs_Prokka_designations.fna

description: Designation of contigs considered by Prokka with respect to MAG 01 (MAG 01 contigs as revealed by MaxBin are available at Genbank under accession number JACDZF000000000).
DOI: 10.25625/eznvw8/djabjt
title: MAG 04_contigs_Prokka_designations.fna

description: Designation of contigs considered by Prokka with respect to MAG 04 (MAG 04 contigs as revealed by MaxBin are available at Genbank under accession number JACDZI000000000).
DOI: 10.25625/eznvw8
title: Metagenome-assembled genome sequences from an anoxygenic photosynthetic consortium

description: Prokka-based annotation of 4 metagenome-assembled genomes
DOI: 10.5281/zenodo.3992738
title: LatinISE test data for SemEval 2020 task 1 with additional token versions of the corpora

description: This data collection contains the Latin test data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection: a Latin text corpus pair (`corpus1/lemma`, `corpus2/lemma`) 40 lemmas which have been annotated for their lexical semantic change between the two corpora (`targets.txt`) the annotated binary change scores of the targets for subtask 1, and their annotated graded change scores for subtask 2 (`truth/`) The corpus data have been automatically lemmatized and part-of-speech tagged, and have been partially corrected by hand. For homonyms, the lemmas are followed by the '\#' symbol and the number of the homonym according to the Lewis-Short dictionary of Latin when this number is greater than 1. For example, the lemma 'dico' corresponds to the first homonym in the Lewis-Short dictionary and 'dico\#2' corresponds to the second homonym, cf. Lewis-Short dictionary. __Corpus 1__ based on: LatinISE (McGillivray and Kilgarriff 2013), version on Sketch Engine language: Latin time covered: from the beginning of the second century before Christ (BC) to the end of the first century BC size: ~1.7 million tokens format: lemmatized, sentence length &gt;= 2, no punctuation, sentences randomly shuffled encoding: UTF-8 __Corpus 2__ based on: LatinISE (McGillivray and Kilgarriff 2013) , version on Sketch Engine language: Latin time covered: from the beginning of the first century after Christ (AD) to the end of the twenty-first century AD size: ~9.4 million tokens format: lemmatized, sentence length &gt;= 2, no punctuation, sentences randomly shuffled encoding: UTF-8 Find more information on the data in the papers referenced below. Besides the official lemma version of the corpora for SemEval-2020 Task 1 we also provide the raw token version (<code>corpus1/token/</code>, <code>corpus2/token/</code>). It contains the raw sentences in the same order as in the lemma version. Find more information on the data and SemEval-2020 Task 1 in the paper referenced below. The creation of the data was supported by the CRETA center and the CLARIN-D grant funded by the German Ministry for Education and Research (BMBF). <strong>References</strong> Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky and Nina Tahmasebi SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection. To appear in SemEval@COLING2020. McGillivray, B. and Kilgarriff, A. (2013). Tools for historical corpus research, and a corpus of Latin. In Paul Bennett, Martin Durrell, Silke Scheible, Richard J. Whitt (eds.), New Methods in Historical Corpus Linguistics, Tübingen: Narr.<br>
DOI: 10.5281/zenodo.3674098
title: LatinISE test data for SemEval 2020 task 1 with additional token versions of the corpora

description: This data collection contains the Latin test data for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection: a Latin text corpus pair (`corpus1/lemma`, `corpus2/lemma`) 40 lemmas which have been annotated for their lexical semantic change between the two corpora (`targets.txt`) the annotated binary change scores of the targets for subtask 1, and their annotated graded change scores for subtask 2 (`truth/`) The corpus data have been automatically lemmatized and part-of-speech tagged, and have been partially corrected by hand. For homonyms, the lemmas are followed by the '\#' symbol and the number of the homonym according to the Lewis-Short dictionary of Latin when this number is greater than 1. For example, the lemma 'dico' corresponds to the first homonym in the Lewis-Short dictionary and 'dico\#2' corresponds to the second homonym, cf. Lewis-Short dictionary. __Corpus 1__ based on: LatinISE (McGillivray and Kilgarriff 2013), version on Sketch Engine language: Latin time covered: from the beginning of the second century before Christ (BC) to the end of the first century BC size: ~1.7 million tokens format: lemmatized, sentence length &gt;= 2, no punctuation, sentences randomly shuffled encoding: UTF-8 __Corpus 2__ based on: LatinISE (McGillivray and Kilgarriff 2013) , version on Sketch Engine language: Latin time covered: from the beginning of the first century after Christ (AD) to the end of the twenty-first century AD size: ~9.4 million tokens format: lemmatized, sentence length &gt;= 2, no punctuation, sentences randomly shuffled encoding: UTF-8 Find more information on the data in the papers referenced below. Besides the official lemma version of the corpora for SemEval-2020 Task 1 we also provide the raw token version (<code>corpus1/token/</code>, <code>corpus2/token/</code>). It contains the raw sentences in the same order as in the lemma version. Find more information on the data and SemEval-2020 Task 1 in the paper referenced below. The creation of the data was supported by the CRETA center and the CLARIN-D grant funded by the German Ministry for Education and Research (BMBF). <strong>References</strong> Dominik Schlechtweg, Barbara McGillivray, Simon Hengchen, Haim Dubossarsky and Nina Tahmasebi SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection. To appear in SemEval@COLING2020. McGillivray, B. and Kilgarriff, A. (2013). Tools for historical corpus research, and a corpus of Latin. In Paul Bennett, Martin Durrell, Silke Scheible, Richard J. Whitt (eds.), New Methods in Historical Corpus Linguistics, Tübingen: Narr.<br>
DOI: 10.25678/000194
title: Data for: Benchmarking Soft Sensors for Remote Monitoring of On-Site Wastewater Treatment Plants

description: On-site wastewater treatment plants (OSTs) are usually unattended, so failures often remain undetected and lead to prolonged periods of reduced performance. To stabilize the performance of unattended plants, soft sensors could expose faults and failures to the operator. In a previous study, we developed soft sensors and showed that soft sensors with data from unmaintained physical sensors can be as accurate as soft sensors with data from maintained ones. The monitored variables were pH and dissolved oxygen (DO), and soft sensors were used to predict nitrification performance. In the present study, we use synthetic data and monitor three plants to test these soft sensors. We find that a long solids retention time and a moderate aeration rate improve the pH soft-sensor accuracy and that the aeration regime is the main operational parameter affecting the accuracy of the DO soft sensor. We demonstrate that integrated design of monitoring and control is necessary to achieve robustness when extrapolating from one OST to another in the absence of plant-specific fine-tuning. Additionally, we provide a unique labeled dataset for further feature and data-driven soft-sensor development. Our benchmarking results indicate that it is feasible to monitor OSTs with unmaintained sensors and without plant-specific tuning of the developed soft sensors. This is expected to drastically reduce monitoring costs for OST-based sanitation systems.
DOI: 10.5523/bris.26pu30dm5k0sv2qk15x92av7tl
title: Data for Publication: Snaking and Laddering in Axially Compressed Cylinders

description: Underlying data and figures for the journal publication "Snaking and Laddering in Axially Compressed Cylinders".
DOI: 10.5281/zenodo.3993082
title: Galactic extinction within 400pc in cartesian coordinates

description: Galactic 3D extinction of Leike et al 2020 using data of Anders et al 2019. See readme.txt or the information within the h5 files for more details.<br>
description: Corrected power.h5 which had a mistake and is now correct in this version.
DOI: 10.5281/zenodo.3750925
title: Galactic extinction within 400pc in cartesian coordinates

description: Galactic 3D extinction of Leike et al 2020 using data of Anders et al 2019. See readme.txt or the information within the h5 files for more details.<br>
description: Corrected power.h5 which had a mistake and is now correct in this version.
DOI: 10.5281/zenodo.3954348
title: Distinguishing Between Shock Darkening and Space Weathering Trends in Ordinary Chondrite Reflectance Spectra

description: The data file contains raw spectra of Chelyabinsk meteorite IM, SD, and SW series as described in the linked journal publication.
DOI: 10.5281/zenodo.3954347
title: Distinguishing Between Shock Darkening and Space Weathering Trends in Ordinary Chondrite Reflectance Spectra

description: The data file contains raw spectra of Chelyabinsk meteorite IM, SD, and SW series as described in the linked journal publication.
DOI: 10.5517/ccdc.csd.cc255ftm
title: CCDC 2001230: Experimental Crystal Structure Determination

description: Related Article: Álvaro Beltrán, Inmaculada Gata, Celia Maya, João Avó, João Carlos Lima, César A. T. Laia, Riccardo Peloso, Mani Outis, M. Carmen Nicasio|2020|Inorg.Chem.|59|10894|doi:10.1021/acs.inorgchem.0c01397
DOI: 10.5517/ccdc.csd.cc255knl
title: CCDC 2001349: Experimental Crystal Structure Determination

description: Related Article: Álvaro Beltrán, Inmaculada Gata, Celia Maya, João Avó, João Carlos Lima, César A. T. Laia, Riccardo Peloso, Mani Outis, M. Carmen Nicasio|2020|Inorg.Chem.|59|10894|doi:10.1021/acs.inorgchem.0c01397
DOI: 10.5517/ccdc.csd.cc257tgq
title: CCDC 2003513: Experimental Crystal Structure Determination

description: Related Article: Louis J. Morris, Nasir A. Rajabi, Mary F. Mahon, Ian Manners, Claire L. McMullin, Michael S. Hill|2020|Dalton Trans.|49|10523|doi:10.1039/D0DT02406F
DOI: 10.5517/ccdc.csd.cc257thr
title: CCDC 2003514: Experimental Crystal Structure Determination

description: Related Article: Louis J. Morris, Nasir A. Rajabi, Mary F. Mahon, Ian Manners, Claire L. McMullin, Michael S. Hill|2020|Dalton Trans.|49|10523|doi:10.1039/D0DT02406F
DOI: 10.5517/ccdc.csd.cc257tjs
title: CCDC 2003515: Experimental Crystal Structure Determination

description: Related Article: Louis J. Morris, Nasir A. Rajabi, Mary F. Mahon, Ian Manners, Claire L. McMullin, Michael S. Hill|2020|Dalton Trans.|49|10523|doi:10.1039/D0DT02406F
DOI: 10.5517/ccdc.csd.cc257tkt
title: CCDC 2003516: Experimental Crystal Structure Determination

description: Related Article: Louis J. Morris, Nasir A. Rajabi, Mary F. Mahon, Ian Manners, Claire L. McMullin, Michael S. Hill|2020|Dalton Trans.|49|10523|doi:10.1039/D0DT02406F
DOI: 10.5517/ccdc.csd.cc257tlv
title: CCDC 2003517: Experimental Crystal Structure Determination

description: Related Article: Louis J. Morris, Nasir A. Rajabi, Mary F. Mahon, Ian Manners, Claire L. McMullin, Michael S. Hill|2020|Dalton Trans.|49|10523|doi:10.1039/D0DT02406F
DOI: 10.5517/ccdc.csd.cc257tmw
title: CCDC 2003518: Experimental Crystal Structure Determination

description: Related Article: Louis J. Morris, Nasir A. Rajabi, Mary F. Mahon, Ian Manners, Claire L. McMullin, Michael S. Hill|2020|Dalton Trans.|49|10523|doi:10.1039/D0DT02406F
DOI: 10.5517/ccdc.csd.cc257tnx
title: CCDC 2003519: Experimental Crystal Structure Determination

description: Related Article: Louis J. Morris, Nasir A. Rajabi, Mary F. Mahon, Ian Manners, Claire L. McMullin, Michael S. Hill|2020|Dalton Trans.|49|10523|doi:10.1039/D0DT02406F
DOI: 10.5517/ccdc.csd.cc258hrq
title: CCDC 2004173: Experimental Crystal Structure Determination

description: Related Article: Takuya Miyazaki, Yoshiaki Shoji, Fumitaka Ishiwari, Takashi Kajitani, Takanori Fukushima|2020|Chemical Science|11|8388|doi:10.1039/D0SC02836C
DOI: 10.5517/ccdc.csd.cc258hsr
title: CCDC 2004174: Experimental Crystal Structure Determination

description: Related Article: Takuya Miyazaki, Yoshiaki Shoji, Fumitaka Ishiwari, Takashi Kajitani, Takanori Fukushima|2020|Chemical Science|11|8388|doi:10.1039/D0SC02836C
DOI: 10.5517/ccdc.csd.cc242ty0
title: CCDC 1968932: Experimental Crystal Structure Determination

description: Related Article: Zohreh Razmara, Jan Janczak|2020|Dalton Trans.|49|10498|doi:10.1039/D0DT01230K
DOI: 10.5517/ccdc.csd.cc23s4mp
title: CCDC 1959622: Experimental Crystal Structure Determination

description: Related Article: Khaled Hassanein, Chiara Cappuccino, Pilar Amo-Ochoa, Jesús López-Molina, Lucia Maini, Elisa Bandini, Barbara Ventura|2020|Dalton Trans.|49|10545|doi:10.1039/D0DT01127D