cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1208400
title: New Annotation Of The Lolium Perenne Genome Described By Bryne Et Al, (2015)

description: Annotation of the Lolium perenne genome described by Bryne <em>et al,</em> (2015, DOI: 10.1111/tpj.13037).

To identify genic regions RNA sequencing data were aligned to the genome using Tophat (Tophat version: V2.0.11; Bowtie2 version: 2.1.0). Isoforms, of genes, were identified using Cufflinks (Version: 2.2.0). Open reading frames (ORF), were found using using program ORFpredictor (version: 3.0). Frame selection was assisted by BLASTX searching the proteomes of <em>Arabidopsis thaliana</em> (TAIR, version: 10), <em>Oryza sativa</em> (Ensembl)<em>, Gycine max </em>(Ensembl)<em>, Populus trichocarpa </em>(Ensembl)<em> and Manihot esculenta </em>(cassava, v4.1). The predicted CDS was back translated to annotate the GFF file created by Cufflinks for CDS using scripts kindly provided by Palmieri<em> et al.,</em> 2012 (doi: 10.1371/journal.pone.0046415). These results are included in the file LG_V2_full.gtf.

Functional annoatation was using three sources. First, protein sequences were search against the <em>A. thaliana</em> proteome using BLASTP. Second, the proteins were search against the Swiss-Prot non-redundant protein database (http://www.uniprot.org/downloads downloaded 14/03/2016, UniProt Consortium, 2014), again using BLASTP. In the third step, the protein sequences were scanned against InterPro's signatures using InterProScan (Version: 5.16-55). These data are included in the file ALLXLOC.txt.
DOI: 10.5281/zenodo.1208401
title: New Annotation Of The Lolium Perenne Genome Described By Bryne Et Al, (2015)

description: Annotation of the Lolium perenne genome described by Bryne <em>et al,</em> (2015, DOI: 10.1111/tpj.13037).

To identify genic regions RNA sequencing data were aligned to the genome using Tophat (Tophat version: V2.0.11; Bowtie2 version: 2.1.0). Isoforms, of genes, were identified using Cufflinks (Version: 2.2.0). Open reading frames (ORF), were found using using program ORFpredictor (version: 3.0). Frame selection was assisted by BLASTX searching the proteomes of <em>Arabidopsis thaliana</em> (TAIR, version: 10), <em>Oryza sativa</em> (Ensembl)<em>, Gycine max </em>(Ensembl)<em>, Populus trichocarpa </em>(Ensembl)<em> and Manihot esculenta </em>(cassava, v4.1). The predicted CDS was back translated to annotate the GFF file created by Cufflinks for CDS using scripts kindly provided by Palmieri<em> et al.,</em> 2012 (doi: 10.1371/journal.pone.0046415). These results are included in the file LG_V2_full.gtf.

Functional annoatation was using three sources. First, protein sequences were search against the <em>A. thaliana</em> proteome using BLASTP. Second, the proteins were search against the Swiss-Prot non-redundant protein database (http://www.uniprot.org/downloads downloaded 14/03/2016, UniProt Consortium, 2014), again using BLASTP. In the third step, the protein sequences were scanned against InterPro's signatures using InterProScan (Version: 5.16-55). These data are included in the file ALLXLOC.txt.
DOI: 10.5287/bodleian:yryknexed
title: Sweet potato and wild relatives - Molecular data

description: This dataset was generated as part of a comprehensive phylogenetic study of all species closely related to sweet potato that addressed several questions pertaining to the origin and evolution of the crop.
DOI: 10.4225/08/5abb208d8de9f
title: Update of the Australian Soil Classification orders map with visible-near infrared spectroscopy and digital soil class mapping

description: Traditional soil maps have helped us to better understand soil, to form our concepts and to teach and transfer our ideas about it, and so they have been used for many purposes. Although, soil maps are available in many countries, there is a need for them to be updated because they are often deficient in that their spatial delineations and their descriptions are subjective and lack assessments of uncertainty. Updating them is a priority for federal soil surveys worldwide as well as for research, teaching and communication. New data from sensors and quantitative ‘digital’ methods provide us with the tools to do so. Here, we present an approach to update large scale, national soil maps with data derived from a combination of traditional soil profile classifications, classifications made with visible–near infrared (vis–NIR) spectroscopy, and digital soil class mapping (DSM). Our results present an update of the Australian Soil Classification (ASC) orders map. The overall error rate of the DSM model, tested on an independent validation set, was 55.6%, and a few of the orders were poorly classified. We discuss the possible reasons for these errors, but argue that compared to the previous ASC maps, our classification was derived objectively, using currently best available data sets and methods, the classification model was interpretable in terms of the factors of soil formation, the modelling produced a 1×1 km resolution soil map with estimates of spatial uncertainty for each soil order and our map has no artefacts at state and territory borders.
DOI: 10.5255/ukda-sn-7631-3
title: Gambling in England and Scotland, 2012: Combined Data from the Health Survey for England and the Scottish Health Survey
DOI: 10.5281/zenodo.1208110
title: Brightness Data

description: This file contains brightness data in Rayleigh for OI 630.0 nm (red line), OI 557.7 (green line), N<sup>+</sup><sub>2</sub> 427.8 nm (blue line) through the night of June 22-23, 2015 obtained using the HiT&MIS from Lowell, MA.

 

The files are in numpy's .npz format and can be accessed (in python) as such after zipping:

import numpy as np

june22=np.load("june22_23_brightness.npz")<br>
i630=(june22['imi630'])# imi630 -  OI 630.0 nm brightness at 37-54 degrees zenith angles<br>
i557=(june22['imi557'])# OI 557.7 nm brightness at 37-54 degrees zenith angles<br>
i427=(june22['imi427'])# N2+ 427.8 nm brightness at 37-54 degrees zenith angles.

i6305=june22['imi6305']# NeI 630.5 nm brightness (this is not calibrated so in Arb. units) at 37-54 degrees zenith angle

time=june22['time']--&gt; Time in Local time

Similarly, june22[iml...] and june22[imz...] can be used to get the brightnesses at 54-70 degrees and 20-37 degrees zenith angles. For example june22['imz630] gives the red line brightness at 20-37 degrees zenith angle.

Contact me at saurav_aryal@student.uml.edu if you have any specific questions.
DOI: 10.5281/zenodo.1208111
title: Brightness Data

description: This file contains brightness data in Rayleigh for OI 630.0 nm (red line), OI 557.7 (green line), N<sup>+</sup><sub>2</sub> 427.8 nm (blue line) through the night of June 22-23, 2015 obtained using the HiT&MIS from Lowell, MA.

 

The files are in numpy's .npz format and can be accessed (in python) as such after zipping:

import numpy as np

june22=np.load("june22_23_brightness.npz")<br>
i630=(june22['imi630'])# imi630 -  OI 630.0 nm brightness at 37-54 degrees zenith angles<br>
i557=(june22['imi557'])# OI 557.7 nm brightness at 37-54 degrees zenith angles<br>
i427=(june22['imi427'])# N2+ 427.8 nm brightness at 37-54 degrees zenith angles.

i6305=june22['imi6305']# NeI 630.5 nm brightness (this is not calibrated so in Arb. units) at 37-54 degrees zenith angle

time=june22['time']--&gt; Time in Local time

Similarly, june22[iml...] and june22[imz...] can be used to get the brightnesses at 54-70 degrees and 20-37 degrees zenith angles. For example june22['imz630] gives the red line brightness at 20-37 degrees zenith angle.

Contact me at saurav_aryal@student.uml.edu if you have any specific questions.
DOI: 10.5517/ccdc.csd.cc1q66hm
title: CCDC 1584890: Experimental Crystal Structure Determination

description: Related Article: Jimil George, Hun Young Kim, Kyungsoo Oh|2018|Org.Lett.|20|2249|doi:10.1021/acs.orglett.8b00590
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.cc1qck2q
title: CCDC 1590023: Experimental Crystal Structure Determination

description: Related Article: Subhrajit Rout, Harshit Joshi, Vinod K. Singh|2018|Org.Lett.|20|2199|doi:10.1021/acs.orglett.8b00493
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.cc1pbyb9
title: CCDC 1559651: Experimental Crystal Structure Determination

description: Related Article: Ghodrat Mahmoudi, Farhad A. Afkhami, Alfonso Castiñeiras, Isabel García-Santos, Atash Gurbanov, Fedor I. Zubkov, Mariusz P. Mitoraj, Mercedes Kukulka, Filip Sagan, Dariusz W. Szczepanik, Irina A. Konyaeva, Damir A. Safin|2018|Inorg.Chem.|57|4395|doi:10.1021/acs.inorgchem.8b00064
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.cc1pbycb
title: CCDC 1559652: Experimental Crystal Structure Determination

description: Related Article: Ghodrat Mahmoudi, Farhad A. Afkhami, Alfonso Castiñeiras, Isabel García-Santos, Atash Gurbanov, Fedor I. Zubkov, Mariusz P. Mitoraj, Mercedes Kukulka, Filip Sagan, Dariusz W. Szczepanik, Irina A. Konyaeva, Damir A. Safin|2018|Inorg.Chem.|57|4395|doi:10.1021/acs.inorgchem.8b00064
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.cc1z0fq4
title: CCDC 1817676: Experimental Crystal Structure Determination

description: Related Article: Jia-Wang Liu, Ying Liu, Yong-Ming Yan, Jing Yang, Xi-Feng Lu, Yong-Xian Cheng|2018|Org.Lett.|20|2220|doi:10.1021/acs.orglett.8b00561
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.cc1qb2gl
title: CCDC 1588609: Experimental Crystal Structure Determination

description: Related Article: Takuma Yano, Yuko Wasada-Tsutsui, Tomohiro Ikeda, Tomonori Shibayama, Yuji Kajita, Tomohiko Inomata, Yasuhiro Funahashi, Tomohiro Ozawa, Hideki Masuda|2018|Inorg.Chem.|57|4277|doi:10.1021/acs.inorgchem.6b02324
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.cc1qb2lq
title: CCDC 1588613: Experimental Crystal Structure Determination

description: Related Article: Takuma Yano, Yuko Wasada-Tsutsui, Tomohiro Ikeda, Tomonori Shibayama, Yuji Kajita, Tomohiko Inomata, Yasuhiro Funahashi, Tomohiro Ozawa, Hideki Masuda|2018|Inorg.Chem.|57|4277|doi:10.1021/acs.inorgchem.6b02324
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: 10.18434/t4/1429857
title: CANDOR - Chromatic Analysis Neutron Diffractometer Or Reflectometer
DOI: 10.20375/0000-000b-cafd-5
title: DHtech Workshop: Gitlab CI/CD for Django

description: Two of the cornerstones of modern software development, Continuous Integration (CI) and Continuous Delivery (CD) are practices to support collaborative and fast development through automation.

With CI, software is built and tested on every code push. Using triggers from version control systems, code is compiled and tested against defined criteria, such as unit and integration tests. This ensures that the latest changes to the code base are compatible with the existing code base, i.e. they integrate well.

On top of this, CD is the practices of packaging and publishing the build artifact of a successful integration run. In an optimal setup, this allows the immediate delivery of the latest successfully built version to a production environment.

In our first Virtual Workshop we will be hearing from Malte Vogl on his experience using Gitlab CI for Django projects. Expanding on Malte’s introduction, Julia Damerow and Carsten Thiel will open up the general discussion with their experiences using Travis-CI and Jenkins.
DOI: 10.20375/0000-000b-cafe-4
title: [Recording] Gitlab CI/CD for Django

description: Two of the cornerstones of modern software development, Continuous Integration (CI) and Continuous Delivery (CD) are practices to support collaborative and fast development through automation.

With CI, software is built and tested on every code push. Using triggers from version control systems, code is compiled and tested against defined criteria, such as unit and integration tests. This ensures that the latest changes to the code base are compatible with the existing code base, i.e. they integrate well.

On top of this, CD is the practices of packaging and publishing the build artifact of a successful integration run. In an optimal setup, this allows the immediate delivery of the latest successfully built version to a production environment.

In our first Virtual Workshop we will be hearing from Malte Vogl on his experience using Gitlab CI for Django projects. Expanding on Malte’s introduction, Julia Damerow and Carsten Thiel will open up the general discussion with their experiences using Travis-CI and Jenkins.
DOI: 10.20375/0000-000b-caff-3
title: [Audio] Gitlab CI/CD for Django
DOI: 10.20375/0000-000b-cb00-0
title: [Slides] Gitlab CI/CD for Django
DOI: 10.15468/krkffx
title: Two new species of penicillate millipedes (Diplopoda, Polyxenidae) from Phu Quoc Island in southern Vietnam

description: This dataset contains the digitized treatments in Plazi based on the original journal article Huynh, Cuong (2018): Two new species of penicillate millipedes (Diplopoda, Polyxenidae) from Phu Quoc Island in southern Vietnam. Zootaxa 4402 (2): 283-302, DOI: https://doi.org/10.11646/zootaxa.4402.2.3
DOI: 10.15468/utxuih
title: A comparative description of the larvae of Psychomyia pusilla (Fabricius 1781), Metalype fragilis (Pictet 1834), and Paduniella vandeli Décamps 1965 (Trichoptera: Psychomyiidae) and comments on the larvae of other species belonging to these three genera

description: This dataset contains the digitized treatments in Plazi based on the original journal article Tachet, Henri, Coppa, Gennaro, Forcellini, Maxence (2018): A comparative description of the larvae of Psychomyia pusilla (Fabricius 1781), Metalype fragilis (Pictet 1834), and Paduniella vandeli Décamps 1965 (Trichoptera: Psychomyiidae) and comments on the larvae of other species belonging to these three genera. Zootaxa 4402 (1): 91-112, DOI: https://doi.org/10.11646/zootaxa.4402.1.4
DOI: 10.5281/zenodo.1208693
title: Fuzzy Ecospace Modelling

description: Fuzzy Ecospace Modelling (FEM) is an R-based program for quantifying and comparing functional disparity, using a fuzzy set theory-based machine learning approach. FEM clusters n-dimensional matrices of functional traits (ecospace matrices – here called the Training Matrix) into functional groups and converts them into fuzzy functional groups using fuzzy discriminant analysis (Lin and Chen 2004 – see main text for more information). Following this, FEM classifies the functional entities from a second matrix (the Test Matrix) into the groups made using the Training Matrix, generating fuzzy membership values for each unit in the Test Matrix. These values are real numbers from 0 to 1, representing increasing degrees of “truth” regarding an organism’s membership in the fuzzy set (see main text). A value of 0 represents non-membership in the fuzzy set, and a value of 1 represents total membership in the fuzzy set. Values in between represent degrees of niche overlap.
DOI: 10.5517/ccdc.csd.cc1z8xqw
title: CCDC 1825829: Experimental Crystal Structure Determination

description: Related Article: M. Solar, N. Trapp|2018|J.Appl.Crystallogr.|51|541|doi:10.1107/S1600576718003291
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.cc1zf26p
title: CCDC 1829812: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf27q
title: CCDC 1829813: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf28r
title: CCDC 1829814: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf29s
title: CCDC 1829815: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf2bt
title: CCDC 1829816: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf2cv
title: CCDC 1829817: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf2dw
title: CCDC 1829818: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf2fx
title: CCDC 1829819: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf2gy
title: CCDC 1829820: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.cc1zf2hz
title: CCDC 1829821: Experimental Crystal Structure Determination

description: Related Article: G. Hofer, F. Grieder, M. Kröger, A.D. Schlüter, T. Weber|2018|J.Appl.Crystallogr.|51|481|doi:10.1107/S1600576718002820
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.