cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3252173
title: RAB1B Expression and Purification

description: As a result of a BioID experiment done to identify possible interaction partners of Huntingtin, RAB1B was flagged. This purification aims to provide a RAB1B sample for future experiments to confirm the possible interaction between these proteins.
description: Funding Acknowledgment: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome.
DOI: 10.5281/zenodo.3252174
title: RAB1B Expression and Purification

description: As a result of a BioID experiment done to identify possible interaction partners of Huntingtin, RAB1B was flagged. This purification aims to provide a RAB1B sample for future experiments to confirm the possible interaction between these proteins.
description: Funding Acknowledgment: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome.
DOI: 10.5281/zenodo.3252175
title: MECP2 Expression and Purification

description: As a result of a BioID experiment done to identify possible interaction partners of Huntingtin, MECP2 was flagged. This purification aims to provide a MECP2 sample for future experiments to confirm the possible interaction between these proteins.
description: Funding Acknowledgment: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome.
DOI: 10.5281/zenodo.3252176
title: MECP2 Expression and Purification

description: As a result of a BioID experiment done to identify possible interaction partners of Huntingtin, MECP2 was flagged. This purification aims to provide a MECP2 sample for future experiments to confirm the possible interaction between these proteins.
description: Funding Acknowledgment: The SGC is a registered charity (number 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada through Ontario Genomics Institute [OGI-055], Innovative Medicines Initiative (EU/EFPIA) [ULTRA-DD grant no. 115766], Janssen, Merck KGaA, Darmstadt, Germany, MSD, Novartis Pharma AG, Ontario Ministry of Research, Innovation and Science (MRIS), Pfizer, São Paulo Research Foundation-FAPESP, Takeda, and Wellcome.
DOI: 10.7910/dvn/e5gxjm/jkgzia
title: Full_Cycle_Networks.zip

description: :unav
DOI: 10.7910/dvn/idbnzc/6sujdk
title: backboning.txt

description: :unav
DOI: 10.7910/dvn/idbnzc/9uwmjo
title: elect_state_list.tab

description: :unav
DOI: 10.7910/dvn/idbnzc/kz4a17
title: scripts.R

description: :unav
DOI: 10.7910/dvn/idbnzc/syute2
title: DataCombine.R

description: :unav
DOI: 10.7910/dvn/ymdfpw/6tn88f
title: Election_Networks.zip

description: :unav
DOI: 10.7910/dvn/idbnzc/1nab4n
title: state_list.tab

description: :unav
DOI: 10.7910/dvn/idbnzc/ez42nb
title: HPC_mpi.pbs

description: :unav
DOI: 10.7910/dvn/idbnzc/txmoke
title: MakeBackbones_HPC.R

description: :unav
DOI: 10.7910/dvn/idbnzc/x91wyd
title: hurdleBackbone_0.0.2.tar.gz

description: :unav
DOI: 10.25810/4c3b-b819.14
title: World Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - May 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/558f-c477.14
title: Australia Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - May 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/es52-xr23.14
title: Canadian Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - May 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/fx6e-r462.2
title: European Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - May 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25810/rxtv-eb29.14
title: German Newspaper Coverage of Climate Change or Global Warming, 2004-2019 - May 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.25345/c50w74
title: MassIVE MSV000084004 - GNPS Diaporthe phaseolorum endophytic fungus
title: Desreplication Diaporthe phaseolorum endophytic fungus
DOI: 10.25810/k55w-7a04.14
title: World Radio Coverage of Climate Change or Global Warming, 2004-2019 - May 2019

description: The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).
DOI: 10.5281/zenodo.3252189
title: Dataset of AD and normal aging in the hippocampus

description: Alzheimer's disease (AD) is the most common type of dementia in the elderly, characterized by irreversible degenerative memory, language, learning, and other cognitive impairments. It is estimated that nearly 500,000 new cases of AD, which is the fifth-leading cause of death for those 65 and older in the United States in 2016. AD brings immense suffering and heavy financial burdens. However, few therapeutic strategies are available to prevent or cure AD due to complex pathogenesis. Due to the high morbidity and mortality of AD, revealing its causes and potential pathogenesis, identifying molecular biomarkers for the early diagnosis, prevention, and treatment are a vital event. However, existing studies have shown that Tau, amyloid-β (Aβ) and APOE play important roles in the pathogenesis of AD, but the above-mentioned aspects as a targeted treatment have not achieved good results. It is imperative in the search for hub gene and pathways in AD. Thus, we extracted mRNA expression data with AD and normal aging in the same tissue and used an integrative network-based method for combining transcriptomic and protein-protein interaction data to find differentially expressed genes (DEGs) and pathways that may reflect key biological processes in AD.
DOI: 10.5281/zenodo.3252188
title: Dataset of AD and normal aging in the hippocampus

description: Alzheimer's disease (AD) is the most common type of dementia in the elderly, characterized by irreversible degenerative memory, language, learning, and other cognitive impairments. It is estimated that nearly 500,000 new cases of AD, which is the fifth-leading cause of death for those 65 and older in the United States in 2016. AD brings immense suffering and heavy financial burdens. However, few therapeutic strategies are available to prevent or cure AD due to complex pathogenesis. Due to the high morbidity and mortality of AD, revealing its causes and potential pathogenesis, identifying molecular biomarkers for the early diagnosis, prevention, and treatment are a vital event. However, existing studies have shown that Tau, amyloid-β (Aβ) and APOE play important roles in the pathogenesis of AD, but the above-mentioned aspects as a targeted treatment have not achieved good results. It is imperative in the search for hub gene and pathways in AD. Thus, we extracted mRNA expression data with AD and normal aging in the same tissue and used an integrative network-based method for combining transcriptomic and protein-protein interaction data to find differentially expressed genes (DEGs) and pathways that may reflect key biological processes in AD.
DOI: 10.7910/dvn/8bthim/eqxcwv
title: ChurchesNorthAndSouth_Brazil2014_Clergy.tab

description: :unav
DOI: 10.25345/c5qd39
title: MassIVE MSV000084005 - GNPS Diaporthe phaseolorum endophytic fungus
title: GNPS Diaporthe phaseolorum endophytic fungus desreplicaao
DOI: 10.17632/8mzws8r4st.1
title: Data for: A robust superhydrophobic and highly oleophobic coating based on F-SiO2-copolymer composites

description: contains Particle size distribution ; Gel rate; contact angle; IR spectrum ; TG analysis
DOI: 10.7910/dvn/yfhmu3/fuaqwq
title: ChurchesNorthAndSouth_Brazil2014.tab

description: :unav
DOI: 10.17632/788dz83hj8.1
title: Data for: Gut yeasts decrease desiccation survival in Drosophila melanogaster

description: Data on the effects of gut yeasts on desiccation survival in Drosophila melanogaster.
DOI: 10.21227/rcx2-pz33
title: GSET Somi: A Game-Specific Eye Tracking Dataset for Somi

description: This is an eye tracking dataset of 84 computer game players who played the side-scrolling cloud game Somi. The game was streamed in the form of video from the cloud to the player. The dataset consists of 135 raw videos (YUV) at 720p with eye tracking data for both eyes (left and right). Male and female candidates were asked to play the game in front of a remote eye-tracking device. For each player, we recorded gaze points, video frames of the gameplay, and mouse and keyboard commands. For each video frame, a list of its game objects with their locations and sizes was also recorded. This data, synchronized with eye-tracking data, allows one to calculate the amount of attention that each object or group of objects draw from each player. This dataset can be used for designing and testing game-specific visual attention models.
DOI: 10.25548/14-4kj4
title: Human adult kidney single nucleus RNA-seq

description: We used single nucleus 10x Chromium to profile a human adult kidney. This dataset was used in the "Wu H, Uchimura K, Donnelly EL, Kirita Y, Morris SA, Humphreys BD, Comparative Analysis and Refinement of Human PSC-Derived Kidney Organoid Differentiation with Single-Cell Transcriptomics, Cell Stem Cell, 2018, 23 (6) 869-881, 30449713, https://doi.org/10.1016/j.stem.2018.10.010, https://www.ncbi.nlm.nih.gov/pubmed/30449713" study.
DOI: 10.5061/dryad.cn2rv96/1
title: sFDvent trait database for deep-sea hydrothermal-vent species, v.1.0

description: This file is the processed, ‘ready-to-use’ version of the sFDvent trait dataset that we recommend for use. The sFDvent database comprises species-level trait scores for deep-sea hydrothermal-vent species across the globe, as contributed by experts using their observations on research cruises and in laboratories, as well as published literature. ‘Taxon’ refers to the taxonomic identity assigned by contributors, while ‘UniqueID’ is an identifier created using letters from the taxon and the entry number, to make it easier to work with the data and reference a taxon. A glossary, describing the traits and modalities, is provided with the paper that accompanies this dataset. We would recommend that users check these data are processed in line with criteria and thresholds appropriate for their research question and/or analytical approach and make adjustments where required, as no dataset will be fit for all purposes. Nevertheless, to ensure this dataset is as user-friendly and ‘ready-to-use’ as possible, we only include traits in this version of the dataset that meet thresholds for certainty and coverage, with more than 50% of species scored and/or an average certainty score of more than 2.3 (of a maximum score of 3). References have been assigned numeric identifiers, which can be matched to the references provided in the paper that accompanies this dataset. If more than one reference is provided to support a score, the reference identifiers are separated by a semi-colon (;). Please note that species with UniqueID 'Aus74' should not have 'Lau Basin' listed as a location. This has been corrected since publication and will be updated in future versions of the sFDvent database.
DOI: 10.5061/dryad.cn2rv96/3
title: Table_S4.3_Raw

description: Table S4.3 is a copy of raw data contributions, compiled from the personalised files sent to each sFDvent contributor. This version of the dataset is provided for transparency and as metadata for users wanting to refer to raw contributions and/or data provided by specific contributors. This dataset includes traits that were removed from the error-checked, quality-controlled dataset due to lack of coverage and would require appropriate processing for each user’s research question before it could be used in an analysis. A glossary to support the traits and modalities given in Table S4.3 is provided in Table S4.1.
DOI: 10.5061/dryad.cn2rv96/4
title: Table_S4.4_CleanedRaw

description: Table S4.4 is a cleaned version of Table S4.3, processed according to the decision rules documented in Table S4.5. We refer users to the Supporting Information accompanying the manuscript for further information about this, and other, files.
DOI: 10.5061/dryad.cn2rv96/5
title: Table_S4.5_Metadata

description: Here, we document the decision rules used to clean / process the data provided in Table S4.3 (raw data). We refer users to the Supporting Information accompanying the manuscript, as well as the manuscript itself, for further information.
DOI: 10.23721/109/1503979
title: internet_address_census_it85c-20190417 (2019-04-17 to 2019-05-19)

description: To collect this data, an Internet-wide IP address sweep was conducted. Every IP address in the ranges allocated by IANA was pinged once by sending ICMP ECHO_REQUEST (PING) packet. If the response (ICMP_ECHO_REPLY) came, its IP address was recorded in this data-set. In all, over 2.5 billion distinct IP addresses were probed during this experiment.
DOI: 10.23721/109/1503980
title: internet_address_census_it85e-20190417 (2019-04-17 to 2019-05-19)

description: To collect this data, an Internet-wide IP address sweep was conducted. Every IP address in the ranges allocated by IANA was pinged once by sending ICMP ECHO_REQUEST (PING) packet. If the response (ICMP_ECHO_REPLY) came, its IP address was recorded in this data-set. In all, over 2.5 billion distinct IP addresses were probed during this experiment.
DOI: 10.23721/109/1503982
title: internet_address_census_it85j-20190417 (2019-04-17 to 2019-05-20)

description: To collect this data, an Internet-wide IP address sweep was conducted. Every IP address in the ranges allocated by IANA was pinged once by sending ICMP ECHO_REQUEST (PING) packet. If the response (ICMP_ECHO_REPLY) came, its IP address was recorded in this data-set. In all, over 2.5 billion distinct IP addresses were probed during this experiment.
DOI: 10.23721/109/1503983
title: internet_address_census_it85n-20190417 (2019-04-17 to 2019-05-19)

description: To collect this data, an Internet-wide IP address sweep was conducted. Every IP address in the ranges allocated by IANA was pinged once by sending ICMP ECHO_REQUEST (PING) packet. If the response (ICMP_ECHO_REPLY) came, its IP address was recorded in this data-set. In all, over 2.5 billion distinct IP addresses were probed during this experiment.
DOI: 10.23721/109/1503984
title: internet_address_census_it85w-20190417 (2019-04-17 to 2019-05-19)

description: To collect this data, an Internet-wide IP address sweep was conducted. Every IP address in the ranges allocated by IANA was pinged once by sending ICMP ECHO_REQUEST (PING) packet. If the response (ICMP_ECHO_REPLY) came, its IP address was recorded in this data-set. In all, over 2.5 billion distinct IP addresses were probed during this experiment.
DOI: 10.23721/109/1503985
title: internet_address_history_it85w-20190417 (2016-06-02 to 2019-05-19)

description: This dataset, generated on 2019-05-29, contains all IPv4 addresses who ever responded to our ISI-west (w) censuses, starting from census it11w (internet_address_survey_it11w-20060307), e.g. it11w, it12w, ... Each IP address is given a history of replies (as a bit-string with 's representing ICMP_ECHO_REPLY received from this IP, and 's corresponding to no-replies. We also include numerical scores that are intended to reflect the likelihood that the given IP address will repond in the future. The scores are based on census data from it70w to it85w.
DOI: 10.23721/109/1503981
title: internet_address_census_it85g-20190417 (2019-04-17 to 2019-05-20)

description: To collect this data, an Internet-wide IP address sweep was conducted. Every IP address in the ranges allocated by IANA was pinged once by sending ICMP ECHO_REQUEST (PING) packet. If the response (ICMP_ECHO_REPLY) came, its IP address was recorded in this data-set. In all, over 2.5 billion distinct IP addresses were probed during this experiment.
DOI: 10.23721/109/1503986
title: internet_address_hitlist_it85w-20190417 (2016-06-02 to 2019-05-19)

description: This dataset, generated on 2019-05-29, contains all IPv4 addresses who ever responded to our ISI-west (w) censuses, starting from census it11w (internet_address_survey_it11w-20060307), e.g. it11w, it12w, ... Each IP address is given a history of replies (as a bit-string with 's representing ICMP_ECHO_REPLY received from this IP, and 's corresponding to no-replies. We also include numerical scores that are intended to reflect the likelihood that the given IP address will repond in the future. The scores are based on census data from it70w to it85w.
DOI: 10.23721/109/1503987
title: internet_address_survey_reprobing_it85c-20190507 (2019-05-07 to 2019-05-21)

description: To collect this data, a subset of Internet IP addresses was pinged by sending ICMP ECHO_REQUEST (PING) packet. The response (if it ever came within 11 minutes time interval) was recorded in this data set. Probe was repeated every 11 minutes. In all, 40490 netblocks (/24 subnets) were periodically reprobed.
DOI: 10.23721/109/1503988
title: internet_address_survey_reprobing_it85w-20190417 (2019-04-17 to 2019-05-01)

description: To collect this data, a subset of Internet IP addresses was pinged by sending ICMP ECHO_REQUEST (PING) packet. The response (if it ever came within 11 minutes time interval) was recorded in this data set. Probe was repeated every 11 minutes. In all, 40490 netblocks (/24 subnets) were periodically reprobed.
DOI: 10.17632/hc4vkpdtss.1
title: Data for: Study on jump height of transmission lines after ice-shedding by reduced-scale modeling test
DOI: 10.25345/c5f076
title: MassIVE MSV000084007 - Basidiobolus_Data_for_IIN_6-21-2019
title: 45 samples consisting of 1:1 MeOH:H2O, and MeOH C18 RP-SPE fractions of mycelium and broth extracts of cultures of the amphibian gut-symbiotic fungus Basidiobolus meristosporus, prepared by Spatafora Lab and McPhail Lab.
DOI: 10.26134/exofop4
title: TESS Camera 4 Image Mosaic

description: This dataset or service is made available by the NASA Exoplanet Science Institute at IPAC, which is operated by the California Institute of Technology under contract with the National Aeronautics and Space Administration.
DOI: 10.5281/zenodo.3252212
title: DWD European Weather 2

description: opendata.dwd.de - OpenData by Deutscher Wetter Dienst

Conditions: https://www.dwd.de/EN/service/copyright/copyright_node.html

dates and times are UTC.
DOI: 10.17632/swfs75tjsr.1
title: Data for: OsmC in Corynebacterium glutamicum was a new MarR-dependent organic hydroperoxide stress Regulon
DOI: 10.17632/c6bbrvcfp7.1
title: Data for: Sound, structure and meaning: The bases of prominence ratings in English, French and Spanish

description: Three Excel spreadsheets contain prominence rating data and accompanying word-level phonological, syntactic, discourse and acoustic properties from a prominence rating study of English, French and Spanish. Prominence ratings obtained from untrained raters, for samples of conversational speech in English, French and Spanish. Spreadsheets are organized with each word from the speech excerpt presented on a separate row of the spreadsheet, with acoustic measures, part of speech, and frequency, and individual raters’ prominence ratings specified in columns. The spreadsheets include legends for all variable names, and information about acoustic measures calculated in the spreadsheet. The methods by which these data were obtained are described in the related research article (Cole, Hualde, Smith, Eager, Mahrt, Napoleão de Souza, Journal of Phonetics, in press). This work was supported by a grant to Jennifer Cole, José I. Hualde and Caroline Smith from the National Science Foundation [BCS 1251343 and 1251134].
DOI: 10.17632/z6sxcbjp9k.1
title: Data for: Modulation of the word frequency effect in recognition memory after an unrelated lexical decision task

description: The dataset includes all the behavioral data for all the three tasks used in the study: Lexical Decision, Familiarity Judgement and Recognition.
DOI: 10.5519/qd.hu49nnmp
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (176 records)
DOI: 10.17632/gh5z7f2y26.1
title: Data for: Determining complex refractive index of cellulose nanocrystals by combination of Beer-Lambert and immersion matching methods

description: Complex refractive index of CNC as a function of wavelength (400 -700 nm) .