cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1423299.v3
title: The C-terminal region of the RNA helicase CshA is required for the interaction with the degradosome and turnover of bulk RNA in the opportunistic pathogen <i>Staphylococcus aureus</i>

description: <i>Staphylococcus aureus</i> is a versatile opportunistic pathogen that adapts readily to a variety of different growth conditions. This adaptation requires a rapid regulation of gene expression including the control of mRNA abundance. The CshA DEAD-box RNA helicase was previously shown to be required for efficient turnover of the <i>agr</i> quorum sensing mRNA. Here we show by transcriptome-wide RNA sequencing and microarray analyses that CshA is required for the degradation of bulk mRNA. Moreover a subset of mRNAs is significantly stabilised in absence of CshA. Deletion of the C-terminal extension affects RNA turnover similar to the full deletion of the <i>cshA</i> gene. In accordance with RNA decay data, the C-terminal region of CshA is required for an RNA-independent interaction with components of the RNA degradation machinery. The C-terminal truncation of CshA reduces its ATPase activity and this reduction cannot be compensated at high RNA concentrations. Finally, the deletion of the C-terminal extension does affect growth at low temperatures, but to a significantly lesser degree than the full deletion, indicating that the core of the helicase can assume a partial function and opening the possibility that CshA is involved in different cellular processes.
DOI: 10.6084/m9.figshare.1422175
title: Characterization of Salivary Microbiome in Patients with Pancreatic Cancer

description: TorresEtAl_seqs_FigshareVer_052115.fna is the processed and quality checked data from QIIME, after having run the split_libraries command. It is the seqs.fna file. TorresEtAl_MappingFile_FigshareVer_052115.txt is the mapping file for the sequences that has the metadata and runs in QIIME.
DOI: 10.6084/m9.figshare.1422178
title: Messaging to increase public support for naloxone distribution policies in the United States: results from a randomized survey experiment

description: Data from participants of a randomized survey assessing the effects of factual information, preemptive refutation, and a sympathetic narrative on support for naloxone distribution and related overdose mortality prevention policies.
DOI: 10.6084/m9.figshare.1422325.v1
title: COUNCIL OF FLORENCE: THE UNREALIZED UNION

description: Master Thesis on the Council of Florence (1437-39), its Union between Christian East and West and the reasons for its limited success.
DOI: 10.6084/m9.figshare.1422174
title: Characterization of Salivary Microbiome in Patients with Pancreatic Cancer

description: TorresEtAl_seqs_FigshareVer_052115.fna is the processed and quality checked data from QIIME, after having run the split_libraries command. It is the seqs.fna file. TorresEtAl_MappingFile_FigshareVer_052115.txt is the mapping file for the sequences that has the metadata and runs in QIIME.
DOI: 10.6084/m9.figshare.1422178.v1
title: Messaging to increase public support for naloxone distribution policies in the United States: results from a randomized survey experiment

description: Data from participants of a randomized survey assessing the effects of factual information, preemptive refutation, and a sympathetic narrative on support for naloxone distribution and related overdose mortality prevention policies.
DOI: 10.6084/m9.figshare.1423299.v2
title: The C-terminal region of the RNA helicase CshA is required for the interaction with the degradosome and turnover of bulk RNA in the opportunistic pathogen <i>Staphylococcus aureus</i>

description: <i>Staphylococcus aureus</i> is a versatile opportunistic pathogen that adapts readily to a variety of different growth conditions. This adaptation requires a rapid regulation of gene expression including the control of mRNA abundance. The CshA DEAD-box RNA helicase was previously shown to be required for efficient turnover of the <i>agr</i> quorum sensing mRNA. Here we show by transcriptome-wide RNA sequencing and microarray analyses that CshA is required for the degradation of bulk mRNA. Moreover a subset of mRNAs is significantly stabilised in absence of CshA. Deletion of the C-terminal extension affects RNA turnover similar to the full deletion of the <i>cshA</i> gene. In accordance with RNA decay data, the C-terminal region of CshA is required for an RNA-independent interaction with components of the RNA degradation machinery. The C-terminal truncation of CshA reduces its ATPase activity and this reduction cannot be compensated at high RNA concentrations. Finally, the deletion of the C-terminal extension does affect growth at low temperatures, but to a significantly lesser degree than the full deletion, indicating that the core of the helicase can assume a partial function and opening the possibility that CshA is involved in different cellular processes.
DOI: 10.6084/m9.figshare.1422175.v1
title: Characterization of Salivary Microbiome in Patients with Pancreatic Cancer

description: TorresEtAl_seqs_FigshareVer_052115.fna is the processed and quality checked data from QIIME, after having run the split_libraries command. It is the seqs.fna file. TorresEtAl_MappingFile_FigshareVer_052115.txt is the mapping file for the sequences that has the metadata and runs in QIIME.
DOI: 10.6084/m9.figshare.1422131
title: Subject_3_1 from Appelgren and Bengtsson, Feedback on Trait or Action Impacts on Caudate and Paracingulum Activity, Plos one 2015

description: Subject 3 Session Task from Appelgren and Bengtsson, Feedback on Trait or Action Impacts on Caudate and Paracingulum Activity, Plos one 2015
DOI: 10.6084/m9.figshare.1422133
title: Subject_4_1 from Appelgren and Bengtsson, Feedback on Trait or Action Impacts on Caudate and Paracingulum Activity, Plos one 2015

description: Subject 4 Session Task from Appelgren and Bengtsson, Feedback on Trait or Action Impacts on Caudate and Paracingulum Activity, Plos one 2015
DOI: 10.5281/zenodo.4074998
title: DO THE TERRORISTS VERITABLY THE DEPRIVED SOULS? EXPLORING THE BITTER TRUTH EMPIRICALLY

description: This dataset is related to the research conducted by the Authors on the topic "<strong>DO THE TERRORISTS VERITABLY THE DEPRIVED SOULS? EXPLORING THE BITTER TRUTH EMPIRICALLY".</strong>
DOI: 10.5517/ccdc.csd.cc20gdxt
title: CCDC 1860896: Experimental Crystal Structure Determination

description: Related Article: A.H.Hasratyan, A.H.Sukoyan, L.A.Bolyan, R.M.Hakobyan, R.A.Tamazyan, A.G.Ayvazyan, G.G.Danagulyan, O.S.Attaryan|2020|Arm.Khim.Zh.|73|37|
DOI: 10.5517/ccdc.csd.cc216q88
title: CCDC 1883289: Experimental Crystal Structure Determination

description: Related Article: Da-Peng Qin, Hai-Bo Li, Qian-Qian Pang, Yu-Xin Huang, Da-Bo Pan, Zhen-Zhen Su, Xiao-Jun Yao, Xin-Sheng Yao, Wei Xiao, Yang Yu|2020|Bioorg.Chem.|103|104221|doi:10.1016/j.bioorg.2020.104221
DOI: 10.5517/ccdc.csd.cc216q99
title: CCDC 1883290: Experimental Crystal Structure Determination

description: Related Article: Da-Peng Qin, Hai-Bo Li, Qian-Qian Pang, Yu-Xin Huang, Da-Bo Pan, Zhen-Zhen Su, Xiao-Jun Yao, Xin-Sheng Yao, Wei Xiao, Yang Yu|2020|Bioorg.Chem.|103|104221|doi:10.1016/j.bioorg.2020.104221
DOI: 10.5517/ccdc.csd.cc216qcc
title: CCDC 1883292: Experimental Crystal Structure Determination

description: Related Article: Da-Peng Qin, Hai-Bo Li, Qian-Qian Pang, Yu-Xin Huang, Da-Bo Pan, Zhen-Zhen Su, Xiao-Jun Yao, Xin-Sheng Yao, Wei Xiao, Yang Yu|2020|Bioorg.Chem.|103|104221|doi:10.1016/j.bioorg.2020.104221
DOI: 10.5517/ccdc.csd.cc216qkk
title: CCDC 1883298: Experimental Crystal Structure Determination

description: Related Article: Da-Peng Qin, Hai-Bo Li, Qian-Qian Pang, Yu-Xin Huang, Da-Bo Pan, Zhen-Zhen Su, Xiao-Jun Yao, Xin-Sheng Yao, Wei Xiao, Yang Yu|2020|Bioorg.Chem.|103|104221|doi:10.1016/j.bioorg.2020.104221
DOI: 10.5517/ccdc.csd.cc216qll
title: CCDC 1883299: Experimental Crystal Structure Determination

description: Related Article: Da-Peng Qin, Hai-Bo Li, Qian-Qian Pang, Yu-Xin Huang, Da-Bo Pan, Zhen-Zhen Su, Xiao-Jun Yao, Xin-Sheng Yao, Wei Xiao, Yang Yu|2020|Bioorg.Chem.|103|104221|doi:10.1016/j.bioorg.2020.104221
DOI: 10.5517/ccdc.csd.cc216qmm
title: CCDC 1883300: Experimental Crystal Structure Determination

description: Related Article: Da-Peng Qin, Hai-Bo Li, Qian-Qian Pang, Yu-Xin Huang, Da-Bo Pan, Zhen-Zhen Su, Xiao-Jun Yao, Xin-Sheng Yao, Wei Xiao, Yang Yu|2020|Bioorg.Chem.|103|104221|doi:10.1016/j.bioorg.2020.104221
DOI: 10.5517/ccdc.csd.cc21bbk9
title: CCDC 1886770: Experimental Crystal Structure Determination

description: Related Article: Junhong Xiang, Xuemei Zhang, Dehong Wang, Jiaxin Li, Qiuying Li, Qin Wang, Yahui Ding, Tianyang Chen, Yuanjun Sun, Shiqi Bao, Jing Chen, Dongmei Li, Liang Wang, Yue Chen|2020|Chem.Commun.|56|11018|doi:10.1039/C9CC07573A
DOI: 10.5517/ccdc.csd.cc21bblb
title: CCDC 1886771: Experimental Crystal Structure Determination

description: Related Article: Junhong Xiang, Xuemei Zhang, Dehong Wang, Jiaxin Li, Qiuying Li, Qin Wang, Yahui Ding, Tianyang Chen, Yuanjun Sun, Shiqi Bao, Jing Chen, Dongmei Li, Liang Wang, Yue Chen|2020|Chem.Commun.|56|11018|doi:10.1039/C9CC07573A
DOI: 10.15161/oar.it/73170
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.5281/zenodo.4075008
title: Dr.

description: This dataset inlcudes all original data produced and used in the accepted paper of Wu et al. entitled '<strong>Evaluating Zr/Rb ratio from XRF scanning as an indicator of grain-size variations of glaciomarine sediments in the Southern Ocean</strong>'.
DOI: 10.6084/m9.figshare.12554090
title: Data on the correlation between climate indicators and the COVID-19 pandemic in 12 cities in China

description: This fileset contains 2 data files. <b>Raw Data.xlsx</b> is in .xlsx file format and <b>Difference statistics.docx</b> in .docx file format.<br>Dataset Raw Data.xlsx contains daily data of the cumulative number of infected cases, cured cases and death, and the climate indicators including average temperature, wind speed, relative humidity, precipitation and the air quality index (AQI) in 12 cities in China during the period of Jan 23rd to Feb 22nd, 2020. The 12 cities for which data are reported, are: Guangzhou, Chongqing, Hefei, Shanghai, Beijing, Harbin, Xinyang, Changsha, Nanchang, Xianning, Shenzhen and Wenzhou.<br>Dataset Difference statistics.docx contains the results of the statistical analyses. Data were analysed by SPSS 21.0.<br><b>Study aims and methodology</b>: The purpose of the present study was to explore the correlation between the novel coronavirus disease 2019 (COVID-19) and climate indicators in cities of China.Twelve cities including Guangzhou, Chongqing, Hefei, Shanghai, Beijing, Harbin, Xinyang, Changsha, Nanchang, Xianning, Shenzhen, Wenzhou were chosen as the study objects. Daily officially reported total number of infected cases, cured cases and death in the 12 cities during the period ofJan 23 to Feb 22, 2020, were obtained. The data of climate indicators including average temperature, wind speed, relative humidity, precipitation and air quality index (AQI) in the cities above were obtained from the National Meteorological Center (http://www.nmc.cn/publish/observations/hourly-precipitation.html). Wuhan was excluded as it was the first place reported the COVID-19 case. Also Wuhan had the severe burst and extremely dense crowds.For more details on the methodology and statistical analysis, please read the related article.<br>
DOI: 10.6084/m9.figshare.12554090.v2
title: Data on the correlation between climate indicators and the COVID-19 pandemic in 12 cities in China

description: This fileset contains 2 data files. <b>Raw Data.xlsx</b> is in .xlsx file format and <b>Difference statistics.docx</b> in .docx file format.<br>Dataset Raw Data.xlsx contains daily data of the cumulative number of infected cases, cured cases and death, and the climate indicators including average temperature, wind speed, relative humidity, precipitation and the air quality index (AQI) in 12 cities in China during the period of Jan 23rd to Feb 22nd, 2020. The 12 cities for which data are reported, are: Guangzhou, Chongqing, Hefei, Shanghai, Beijing, Harbin, Xinyang, Changsha, Nanchang, Xianning, Shenzhen and Wenzhou.<br>Dataset Difference statistics.docx contains the results of the statistical analyses. Data were analysed by SPSS 21.0.<br><b>Study aims and methodology</b>: The purpose of the present study was to explore the correlation between the novel coronavirus disease 2019 (COVID-19) and climate indicators in cities of China.Twelve cities including Guangzhou, Chongqing, Hefei, Shanghai, Beijing, Harbin, Xinyang, Changsha, Nanchang, Xianning, Shenzhen, Wenzhou were chosen as the study objects. Daily officially reported total number of infected cases, cured cases and death in the 12 cities during the period ofJan 23 to Feb 22, 2020, were obtained. The data of climate indicators including average temperature, wind speed, relative humidity, precipitation and air quality index (AQI) in the cities above were obtained from the National Meteorological Center (http://www.nmc.cn/publish/observations/hourly-precipitation.html). Wuhan was excluded as it was the first place reported the COVID-19 case. Also Wuhan had the severe burst and extremely dense crowds.For more details on the methodology and statistical analysis, please read the related article.<br>
DOI: 10.6084/m9.figshare.12554090.v1
title: Data on the correlation between climate indicators and the COVID-19 pandemic in 12 cities in China

description: This fileset contains 2 data files. <b>Raw Data.xlsx</b> is in .xlsx file format and <b>Difference statistics.docx</b> in .docx file format.<br>Dataset Raw Data.xlsx contains daily data of the cumulative number of infected cases, cured cases and death, and the climate indicators including average temperature, wind speed, relative humidity, precipitation and the air quality index (AQI) in 12 cities in China during the period of Jan 23rd to Feb 22nd, 2020. The 12 cities for which data are reported, are: Guangzhou, Chongqing, Hefei, Shanghai, Beijing, Harbin, Xinyang, Changsha, Nanchang, Xianning, Shenzhen and Wenzhou.<br>Dataset Difference statistics.docx contains the results of the statistical analyses. Data were analysed by SPSS 21.0.<br><b>Study aims and methodology</b>: The purpose of the present study was to explore the correlation between the novel coronavirus disease 2019 (COVID-19) and climate indicators in cities of China.Twelve cities including Guangzhou, Chongqing, Hefei, Shanghai, Beijing, Harbin, Xinyang, Changsha, Nanchang, Xianning, Shenzhen, Wenzhou were chosen as the study objects. Daily officially reported total number of infected cases, cured cases and death in the 12 cities during the period ofJan 23 to Feb 22, 2020, were obtained. The data of climate indicators including average temperature, wind speed, relative humidity, precipitation and air quality index (AQI) in the cities above were obtained from the National Meteorological Center (http://www.nmc.cn/publish/observations/hourly-precipitation.html). Wuhan was excluded as it was the first place reported the COVID-19 case. Also Wuhan had the severe burst and extremely dense crowds.For more details on the methodology and statistical analysis, please read the related article.<br>
DOI: 10.6084/m9.figshare.13060955
title: MRC5_pol2_1_hg19_sorted.bam.bai

description: dddddddddddddddddd
DOI: 10.6084/m9.figshare.13060955.v1
title: MRC5_pol2_1_hg19_sorted.bam.bai

description: dddddddddddddddddd
DOI: 10.6084/m9.figshare.13072223
title: CNV calling in Malagueña goats

description: The agouti signaling protein (ASIP) gene has a crucial role in pigmentation by encoding a protein that binds the melanocortin 1 receptor and stimulates the synthesis of pheomelanin rather than eumelanin. Several studies have suggested that an increased copy number of the ASIP gene might explain the white pigmentation of certain goat breeds, as previously demonstrated in sheep. In the current work, we have identified the segregation of the ASIP CNV in Murciano-Granadina (black or brown coat), Malagueña (brown, blond or white coat) and Saanen (white coat) goats with available Illumina Goat SNP50 BeadChip (Illumina Inc., San Diego, CA) genotypes by using the PennCNV v1.0.5 and QuantiSNP v2 tools. This result shows that the ASIP CNV segregates in dark-colored breeds. To gain new insights into this issue, we have estimated the copy number of the ASIP gene in 83 goats from 8 breeds with different coloration patterns using a real-time quantitative PCR approach. Our results showed an increased ASIP copy number not only in Saanen (3.50 ± 0.23 copies relative to the calibrator) and white Malagueña (3.51 ± 0.51 copies) goats, but also in the Murciano-Granadina breed (3.33 ± 0.58 copies) as well as in blond/brown individuals from the Malagueña (3.58 ± 0.73 copies) breed. The number of ASIP copies was not significantly different in these four caprine populations (P value &gt; 0.05). Moreover, we did not observe a trend towards increased ASIP copy number in breeds with predominantly white colors, such as Maltese (2.85 ± 0.28 copies), Jonica (2.82 ± 0.39 copies) and Blanca de Rasquera (2.37 ± 0.33 copies). Our results, combined with recent findings demonstrating the high structural complexity of the ASIP locus, indicate that additional functional and expression studies should be performed in order to fully understand the role of ASIP structural variation in goat pigmentation.
DOI: 10.6084/m9.figshare.13072223.v1
title: CNV calling in Malagueña goats

description: The agouti signaling protein (ASIP) gene has a crucial role in pigmentation by encoding a protein that binds the melanocortin 1 receptor and stimulates the synthesis of pheomelanin rather than eumelanin. Several studies have suggested that an increased copy number of the ASIP gene might explain the white pigmentation of certain goat breeds, as previously demonstrated in sheep. In the current work, we have identified the segregation of the ASIP CNV in Murciano-Granadina (black or brown coat), Malagueña (brown, blond or white coat) and Saanen (white coat) goats with available Illumina Goat SNP50 BeadChip (Illumina Inc., San Diego, CA) genotypes by using the PennCNV v1.0.5 and QuantiSNP v2 tools. This result shows that the ASIP CNV segregates in dark-colored breeds. To gain new insights into this issue, we have estimated the copy number of the ASIP gene in 83 goats from 8 breeds with different coloration patterns using a real-time quantitative PCR approach. Our results showed an increased ASIP copy number not only in Saanen (3.50 ± 0.23 copies relative to the calibrator) and white Malagueña (3.51 ± 0.51 copies) goats, but also in the Murciano-Granadina breed (3.33 ± 0.58 copies) as well as in blond/brown individuals from the Malagueña (3.58 ± 0.73 copies) breed. The number of ASIP copies was not significantly different in these four caprine populations (P value &gt; 0.05). Moreover, we did not observe a trend towards increased ASIP copy number in breeds with predominantly white colors, such as Maltese (2.85 ± 0.28 copies), Jonica (2.82 ± 0.39 copies) and Blanca de Rasquera (2.37 ± 0.33 copies). Our results, combined with recent findings demonstrating the high structural complexity of the ASIP locus, indicate that additional functional and expression studies should be performed in order to fully understand the role of ASIP structural variation in goat pigmentation.
DOI: 10.6084/m9.figshare.13072229.v1
title: MRC5_pol2_2h_hg19_sorted.bam.bai

description: qqqqqqw
DOI: 10.6084/m9.figshare.13072229
title: MRC5_pol2_2h_hg19_sorted.bam.bai

description: qqqqqqw
DOI: 10.6084/m9.figshare.13072238.v1
title: MRC5_pol2_30m_hg19_sorted.bam.bai

description: dddddddddddddd
DOI: 10.6084/m9.figshare.13072238
title: MRC5_pol2_30m_hg19_sorted.bam.bai

description: dddddddddddddd
DOI: 10.6084/m9.figshare.13072208
title: Proteomic data in HelaS3 Scalia et al. 2020

description: An Excel file is given which describes a proteomic study for EphB4 interactors on block of a IGFII-IRA loop block. Data is described in Scalia et al 2020 (in press)
DOI: 10.6084/m9.figshare.13072208.v1
title: Proteomic data in HelaS3 Scalia et al. 2020

description: An Excel file is given which describes a proteomic study for EphB4 interactors on block of a IGFII-IRA loop block. Data is described in Scalia et al 2020 (in press)
DOI: 10.5522/04/12783845
title: HEGP Challenge Dataset 2

description: Encrypted Dataset #2 for the HEGP Challenge, see https://github.com/encryption4genetics/HEGP-website for more details. <br><br>IMPORTANT UPDATE 09/10/2020<br>Data have been replaced with final versions to be used in the actual challenge - DON'T USE THE INITIAL VERSION of the data in file ciphertext2.RData as this is not correct.<br><br>The new files, and their MD5 checksums, are:<br>challenge2.ciphertext.RData 357a562462c10428a0278d461d56d06b<br>challenge2.ciphertext.txt c3706ecf12275859e3a040b23af1c9f9<br>They contain the same data in different formats, namely RData and text.<br>These data are also available from<br>http://ipfs.genenetwork.org/ipfs/QmWhtzavGi9FXhabQX6tuNAp2KaBoYTHgKUFuk8jgsZVHi<br><br>
DOI: 10.5522/04/12783845.v2
title: HEGP Challenge Dataset 2

description: Encrypted Dataset #2 for the HEGP Challenge, see https://github.com/encryption4genetics/HEGP-website for more details. <br><br>IMPORTANT UPDATE 09/10/2020<br>Data have been replaced with final versions to be used in the actual challenge - DON'T USE THE INITIAL VERSION of the data in file ciphertext2.RData as this is not correct.<br><br>The new files, and their MD5 checksums, are:<br>challenge2.ciphertext.RData 357a562462c10428a0278d461d56d06b<br>challenge2.ciphertext.txt c3706ecf12275859e3a040b23af1c9f9<br>They contain the same data in different formats, namely RData and text.<br>These data are also available from<br>http://ipfs.genenetwork.org/ipfs/QmWhtzavGi9FXhabQX6tuNAp2KaBoYTHgKUFuk8jgsZVHi<br><br>
DOI: 10.5522/04/12783845.v1
title: HEGP Challenge Dataset 2

description: Encrypted Dataset #2 for the HEGP Challenge, see https://github.com/encryption4genetics/HEGP-website for more details. <br>The MD5 checksum for these data is 8bbdc29e3d51dafa224a1af5a9bbadf7<br>
DOI: 10.5522/04/12794999
title: HEGP Challenge Dataset 1

description: Encrypted Dataset #1 for the HEGP Challenge, see https://github.com/encryption4genetics/HEGP-website for more details. <br><br>Dataset comprises encrypted genotypes of 500 subjects at 12,359 SNPs,<br><br><br>IMPORTANT Update 09/10/2020<br>Data have been replaced with final versions to be used in the actual challenge - DON'T USE THE INITIAL VERSION of the data in file ciphertext1.RData as this is not correct. <br>The new files and their MD5 checksums, are:<br>challenge1.ciphertext.RData 82f2f6bf027d185e095db7e571e50a67<br><br>challenge1.ciphertext.txt 148ce09c6dfc878af09874c090a7bd64<br>The two datasets contain the same data (encrypted genotypes) in different file formats, namely RData and text.<br>These data are also available from http://ipfs.genenetwork.org/ipfs/QmWhtzavGi9FXhabQX6tuNAp2KaBoYTHgKUFuk8jgsZVHi<br><br>