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Data files: Single-cell RNA profiling of Plasmodium vivax-infected hepatocytes reveals parasite- and host- specific transcriptomic signatures and therapeutic targets
<p>Scripts, preprocessed count matrices, and single-cell data objects generated in <strong>“Single-cell RNA profiling of <em>Plasmodium vivax</em><em>-</em>infected hepatocytes reveals parasite- and host- specific transcriptomic signatures and therapeutic targets” </strong></p>
Host removal database: Homo sapiens, Sars-Cov-2, PhiX174
<p>๐พ <strong>cleanup-db</strong></p> <p>Kraken2 database, built upon a viral sequence masked human reference from:</p> <ul> <li>Handley, Scott A. (2020). <strong>Virus+ Sequence Masked Human Reference Genome (hg19)</strong> (1.0) [Data set]. Zenodo. [<a href="https://zenodo.org/record/4116107">10.5281/zenodo.4116107</a>]</li> </ul> <p>but separating chromosomes as artificial taxa to allow for QC, and includes Sars-Cov-2 and PhiX 174</p> <p>๐พ <strong>gutcheck-db</strong></p> <p>A very small DB containg some common gut bacteria and Human and Murine mitochondrial genome:</p> <ul> <li><em>Akkermansia muciniphila</em></li> <li><em>Bacteroides fragilis</em></li> <li><em>Bifidobacterium longum</em></li> <li><em>Blautia obeum strain</em></li> <li><em>Escherichia coli</em></li> <li><em>Enterococcus faecium</em></li> <li><em>Prevotella copri</em></li> </ul> <p> </p> <p>See: <a href="https://github.com/telatin/cleanup">https://github.com/telatin/cleanup</a></p>
2021_2022_E4_EBIRD_30spp_SEASONAL_BirdDistribution_WMV_hosts
<p><strong>Abstract</strong></p> <p>A series of weekly bird abundance distribution datasets is now available from EBIRD (<a href="https://science.ebird.org/en/status-and-trends" target="_blank" rel="noopener">https://science.ebird.org/en/status-and-trends</a>). ERGO has processed these data in several tranches to provide weekly species richness and weekly aggregated abundance indices at 3km resolution. Data for thirty species have now been processed. These species have been selected as being West Nile Virus hosts, using literature search, inference from mosquito WNV vector blood meals and from bird serology reports. The two tranches are a) all 30 selected species and b) the top 15 E4Warning priority species . Details are provided in the accompanying Excel Spreadsheet (e4ebird readmeJune24.xls).</p> <p><strong>Description</strong></p> <p>This dataset has been requested for 'the Horizon e4Warning project on mapping and modelling West Nile Virus Disease and its Hosts' then been downloaded from ebird.org and it includes weekly abundance geospatial tifs for 30 species:</p> <ol> <li>weekly presence</li> <li>weekly species richness</li> <li>week abundance sum</li> </ol> <p>Data obtained from Ebird https://science.ebird.org/en/status-and-trends/species/</p> <p><strong>Species Names: </strong></p> <table> <tbody> <tr> <td><strong>Species</strong></td> <td><strong>English Name</strong></td> <td><strong>filname code</strong></td> </tr> <tr> <td>Alcedo atthis</td> <td>Common Kingfisher</td> <td>comkin1</td> </tr> <tr> <td>Anas platyrhynchos</td> <td>Mallard</td> <td>mallar3</td> </tr> <tr> <td>Anser anser</td> <td>Graylag Gose</td> <td>gragoo</td> </tr> <tr> <td>Athene noctua</td> <td>Little Owl</td> <td>litowl1</td> </tr> <tr> <td>Bulbulcus ibis</td> <td>Cattle Egret</td> <td>categr</td> </tr> <tr> <td>Buteo buteo</td> <td>Common Buzzard</td> <td>combuz1</td> </tr> <tr> <td>Columba palumbus</td> <td>Commin Wood Piegon</td> <td>cowpig</td> </tr> <tr> <td>Corvus cornix</td> <td>Hooded Crow</td> <td>hoocro1</td> </tr> <tr> <td>Corvus corone cornix</td> <td>Carrion Crow</td> <td>carcro1</td> </tr> <tr> <td>Corvus monedula</td> <td>Eurasian Jackdaw</td> <td>eurjac</td> </tr> <tr> <td>Cyanistes caeruleus</td> <td>Blue Tit</td> <td>blutit</td> </tr> <tr> <td>Egretta garzetta</td> <td>(Little Egret)</td> <td>litegr</td> </tr> <tr> <td>Eremophila alpestris</td> <td>Horned Lark</td> <td>horlar</td> </tr> <tr> <td>Falco tinnunculus</td> <td>Eurasian Kestrel</td> <td>eurkes</td> </tr> <tr> <td>Garrulus glandarius</td> <td>Eurasian Jay</td> <td>eurjay1</td> </tr> <tr> <td>Hirundo rustica</td> <td>Barn Swallow</td> <td>barswa</td> </tr> <tr> <td>Larus argentatus</td> <td>Herring Gull</td> <td>hergul</td> </tr> <tr> <td>Lulua arborea</td> <td>Woodlark</td> <td>woolar1</td> </tr> <tr> <td>Luscinia Luscinia</td> <td>Thrush Nightinglae</td> <td>thrnig1</td> </tr> <tr> <td>Luscinia megarhynchos</td> <td>Common nightingale</td> <td>comnig1</td> </tr> <tr> <td>Passer domesticus (including Passer italiae and Passer hispaniolensis)</td> <td>House Sparrow</td> <td>houspa</td> </tr> <tr> <td>Pica pica</td> <td>Eurasian Magpie</td> <td>eurmag1</td> </tr> <tr> <td>Streptopelia decaocto</td> <td>Eurasian Collared Dove</td> <td>eucdov</td> </tr> <tr> <td>Turdus merula</td> <td>Eurasian Blackbird</td> <td>eurbla</td> </tr> <tr> <td>Ciconia ciconia</td> <td>White Stork</td> <td>whisto1</td> </tr> <tr> <td>Sturnus vulgaris</td> <td>European Starling</td> <td>eursta</td> </tr> <tr> <td>Sylvia atricapilla</td> <td>Eurasian Bl;ackcap</td> <td>blackc1</td> </tr> <tr> <td>Acrocephalus scirpaceus</td> <td>Common Reed Warbler</td> <td>eurwar1</td> </tr> <tr> <td>Fulica atra</td> <td>Eurasian Coot</td> <td>eurcoo</td> </tr> <tr> <td>Columba livia</td> <td>Rock Pigeon</td> <td>rocpig</td> </tr> <tr> <td>Gallus gallus</td> <td>Domestic chicken</td> <td> </td> </tr> </tbody> </table> <p><strong>File Names:</strong></p> <div> <div><strong>a)</strong> e4ebirdabundanceall30weeklyJune24 All weekly abundance datasets for 30 availablke spp at 3km resolution, June 24</div> <div><strong>b) </strong>e4ebirdPAall30weeklyJune24 Presence absence with missing recoded to 0 for all 30 species available in June 24. This recoding is based of ad hoc checks of weekly datasets against the birdlife species ranges, which suggest that the maximum extents of combined weekly abundance distributions match the rage boundares fairly well </div> <div> </div> <div><strong>c)</strong> e4ebirdspprichnessall23SUMMEANweeklyFeb24 Summed and mean weekly presence absence for 23 available species calc Feb24. If a species in missing a weekly dataset, missing weeks are filled with last valid presence week up to halfway through the gap in availability, then with the first available distribution after the gap</div> <div><strong>d)</strong> e4ebirdspprichnesse415SUMMEANweeklyJun24 Summed and mean weekly presence absence for e4 15 priority species calc June 24. If a species in missing a weekly dataset, missing weeks are filled with last valid presence week up to halfway through the gap in availability, then with the first available distribution after the gap</div> <div><strong>e)</strong> e4ebirdspprichnessall30SUMMEANweeklyJun24 Summed and mean weekly presence absence for 30 available species calc June 24. If a species in missing a weekly dataset, missing weeks are filled with last valid presence week up to halfway through the gap in availability, then with the first available distribution after the gap</div> <div> </div> <div><strong>f)</strong> e4ebirdabundanceall30summeanweekJun24 Summed and mean weekly median abundance for 30 available species calc June 24. If a species in missing a weekly dataset, missing weeks are filled with last valid presence week up to halfway through the gap in availability, then with the first available distribution after the gap</div> <div><strong>g)</strong> e4ebirdeabundance415summeanweekJun24 Summed and mean weekly median abundance for e4 15 priority species calc June 24. If a species in missing a weekly dataset, missing weeks are filled with last valid presence week up to halfway through the gap in availability, then with the first available distribution after the gap</div> <p> </p> </div> <p> </p> <p> </p>
Data and code for: Habitat preference of an herbivore shapes the habitat distribution of its host plant
<p>Initial release of analysis and code for:</p> <p>Alexandre, N. M., P. T. Humphrey, A. D. Gloss, J. Lee, J. Frazier, H. A. Affeldt III, and N. K. Whiteman. 2018. Habitat preference of an herbivore shapes the habitat distribution of its host plant. Ecosphere 00(00):e02372. (full citation pending)</p> <p>Release published to accompany corrected proofs on 2018-Jul-26.</p>
Data and code for: Genomic changes underlying host specialization in the bee gut symbiont Lactobacillus Firm5
<p>This dataset contains data and code underlying the comparative genomics, amplicon sequencing, and statistical analysis of the research article "Genomic changes underlying host specialization in the bee gut symbiont Lactobacillus Firm5”. Genome sequences and short read datasets are available under NCBI Bioproject accession PRJNA392822.</p> <p>The dataset contains tar-balls for the main workflows of the analysis. Dowload and unpack to view the contents (tar -zxvf filename.tar.gz). For each tar-ball, a README.txt file describes the contents of the directory. The analyses require certain open-source software packages to be installed. These are not provided here.</p>
Host plant dataset of Curculionidae Scolytinae of the world: miscellaneous tribes (Part 2)
<p><span>This dataset include a complete list of host plants, with economic categorization, for 2205 scolytine species, belonging to 16 tribes: Amphiscolytini, Bothrosternini, Carphodicticini, Chaetophloeini, Crypturgini, Diamerini, Dryocoetini, Hexacolini, Hylesinini, Hyorrhynchini, Hypoborini, Micracidini, Phloeotribini, Phrixosomatini, Scolytini, and Scolytoplatypodini</span></p>
Catalog Data for Prior-Informed AGN-Host Spectral Decomposition Using PyQSOFit
<p>This catalog contains 76,565 AGN-host decomposed spectral measurements for all quasars with z<0.8 in SDSS DR16Q. Our prior-informed decomposition method significantly improved the decomposition success rate from less than 60% to 94%. For the first time, we perform the AGN-host spectral decomposition on survey scale catalog.</p> <p>Our spectral decomposition results are highly consistent to those of HSC image decomposition. Our catalog suggests that an average host galaxy contribution at 5100A is 38.8%, which would lead to an overestimation of 0.215 dex in L5100 and 0.219 dex in black hole mass if the host is not removed. The Dn4000 and stellar velocity dispersion measurements from the decomposed host galaxy spectra are also provided.</p> <p>Please read this paper for more techinique details: <a href="https://arxiv.org/abs/2406.17598">arXiv: 2406.17598</a></p>
PhasAGE Training School 1 - Phase separation in virus-host interactions- LECTURE
<p>The Training School 1 <strong>“Computational Methods to Study Protein Phase Separation”</strong> is the first edition of a series of PhasAGE training activities.</p> <p>The goal of this course is to provide participants with the basic knowledge to understand the phenomenon of <strong>Phase Separation</strong>, its role in biological processes and diseases. In addition, the course will provide <strong>an overview of the available computational resources</strong> to navigate this knowledge. Participants will have <strong>hands-on training</strong> in tools and resources available for life sciences, to collect information from the literature on biomolecular phase transitions, identify features triggering phase transitions, mutations associated with diseases, known or predicted PTMs and molecular interaction sites.</p>
A curated database of fungal pathogens and their host range
<p>This database contains a manually curated set of human, animal and plant pathogens, annotated with their confirmed host range and relevant sources. In addition to that, we include additional sets of plant-associated fungi (which may include non-pathogens), as well as fungi with an automatically assigned, putative human, animal or plant host. The labelled fungal species are linked to their representative GenBank genomes wherever possible. Genomes that were screened, but no label was found, are also included.</p> <p><strong>[Last update on: 11 Dec 2022]</strong><br> [Home page: <a href="https://dacs-hpi.gitlab.io/pathogenic-fungi/">https://dacs-hpi.gitlab.io/pathogenic-fungi/</a>]<br> <br> The database is stored in a flat-file format. All metadata are stored in all_data_[date].csv, and all_data_[date].rds contains the same data in a compressed format that can be easily loaded in R. The database was first compiled on 9 Oct 2021 (v1.0), and then updated on 2 Jan 2022 (v1.1) and 11 Dec 2022 (v1.2).</p> <p>The core database is limited to manually confirmed human, animal and plant pathogens with available genomes as of 9 Oct 2021. Those data are a subset of all_data, and are stored in core_fungal_pathogens.csv and core_fungal_pathogens.rds.</p> <p>The temporal-test subset contains confirmed pathogens with genomes added to GenBank between 9 Oct 2021 and 2 Jan 2022.</p> <p>You may also be interested in trained neural network models predicting pathogenic potentials of novel fungi from DNA sequences (<a href="https://zenodo.org/record/5711877">https://zenodo.org/record/5711877</a>) and simulated Illumina read sets used to train them (<a href="https://zenodo.org/record/5846397">https://zenodo.org/record/5846397</a>).<br> <br> See also the preprint: <a href="https://www.biorxiv.org/content/10.1101/2021.11.30.470625">https://www.biorxiv.org/content/10.1101/2021.11.30.470625</a> and <strong>the paper</strong> presented at ECCB '22 and published in <em>Bioinformatics:</em> <a href="https://doi.org/10.1093/bioinformatics/btac495">https://doi.org/10.1093/bioinformatics/btac495.</a></p>
Spectral Library of European Pegmatites, Pegmatite Minerals and Pegmatite Host-Rocks โ The Greenpeg Database
<p>Spectral signature, obtained through reflectance spectroscopy studies, of European pegmatites and minerals, as well of their host rocks. Samples include LCT- and NYF-type pegmatites and host rocks from pegmatite locations in Austria, Ireland, Norway, Portugal, and Spain. Sample preparation and spectral measurement were conducted in the Universidade do Porto – Faculdade de Ciências (UPORTO) laboratories. The database contains the reflectance spectra (raw and with continuum removed), sample photographs, and main absorption features automatically extracted by a Python routine. Whenever possible, spectral mineralogy was interpreted based on the continuum-removed spectra. A detailed description of the database, its content, the measuring instrument, and interoperability with GIS is found in the database report.</p>
Dataset 2 for "Host-specificity and repeatability of haemosporidian infection parameters and potential consequences when testing host species-level hypotheses"
<p>Dataset with 154 host species (min 45 sampled individuals sampled at 1+ sites) for the second part of the analysis in "Host-specificity and repeatability of haemosporidian infection parameters and potential consequences when testing host species-level hypotheses". One file contains the data table. One file contains a table with descriptions of the columns in the data table.</p>
Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs (Raw data)
<p>Datasets for the analysis developed in the Article "<em><strong>Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs</strong></em>". For more information, please refer to the original publication.</p> <p>Network_Structural_Index_&_SpogeTraits.csv <- Structural Index for the sponge-dwelling fauna network, sponge accumulated area and sponges’ morphology.</p> <p>NWTA_CoralReefs_Sponges_ interactions.csv <- Relationship between host sponges and guest fauna in the Northwester Atlantic coral reefs</p> <p>NWTA_CoralReefs_Sponge_reacords.csv <- Sponge species incidence records in the Northwester Atlantic coral reefs</p> <p>sponges_morphological_description.csv <- Sponge morphological standardization</p> <p>Network.html <- Interactive sponge-dwelling fauna network</p> <p>Enjoy!<br> </p>
Code and data for manuscript: Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir.
<p>This is the source code and data required to reproduce data analysis and figures from the manuscript, "Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir". </p>
Host network traffic time series 2019/01
<p><em><strong>General info</strong></em></p> <p>Dataset was collected over one <strong>month period in January 2019</strong>. The observation points for the collection of IP flows were located at the borders of the university campus network. The campus university network has /16 CIDR IPv4 network range at disposal and contains various network segments from segments connecting dormitories, over server segments, to a segment containing working stations of university administrative workers. The size of the raw IP flows used to create the dataset was over 860GB. <strong>A host in our dataset is identified by its source IPv4 address. </strong><br> </p> <p><em><strong>Variables</strong></em></p> <p>The dataset contains the following variables:</p> <ul> <li><strong>Aggregations</strong> - created from five-minute total volumes aggregated over one-hour disjoint windows using mean/max/min aggregation functions <ul> <li><strong># of flows (FL) </strong>- number of flows for a given source IP </li> <li><strong># of packets (PKT)</strong> - number of packets for a given source IP</li> <li><strong># of bytes (BYT)</strong> - number of packets for a given source IP</li> <li><strong>flow duration (DUR)</strong> - average flow duration in seconds</li> </ul> </li> <li><strong>Distinct Counts </strong>- count of distinct values for each variable in five-minute window aggregated over one-hour disjoint windows using mean/max/min aggregation functions <ul> <li><strong># of peers (PEER)</strong> - number of distinct communication peers for a given source IP</li> <li><strong># of ports (PORTS)</strong> - number of distinct destination ports for a given source IP</li> <li><strong># of protocols (PROTO)</strong> - number of distinct communication protocols for a given source IP</li> <li><strong># of AS numbers (AS)</strong> - number of distinct destination AS numbers for a given source IP</li> <li><strong># of countries (CTRY)</strong> - number of distinct destination countries for a given source IP</li> </ul> </li> <li><strong>Labels</strong> <ul> <li><strong>Range (RNG)</strong> - a network range a host belongs to (anonymized)</li> <li><strong>Unit (UNT) </strong>- an administrative unit owning the network range</li> <li><strong>Sub-unit (SUB-UNT)</strong> - a sub-unit of the unit</li> </ul> </li> </ul> <p> </p> <p><em><strong>Dataset format</strong></em></p> <ul> <li>The dataset is in <strong>comma-separated values (CSV)</strong> format. </li> <li><strong>Header</strong> - multilevel, first 3 lines <ul> <li>1 level - aggregation type {mean|min|max}</li> <li>2 level - variable {see above}</li> <li>3 level - hour of a day {00,01,02,03,...,22,23}</li> </ul> </li> <li><strong>Lablels</strong> - last 4 columns</li> <li><strong>Dataset size </strong> <ul> <li>rows: 65536 host records + 3 headers</li> <li>columns: 648 variables + 4 labels</li> </ul> </li> </ul> <p> </p>
Data from: Deciphering host-parasitoid interactions and parasitism rates of crop pests using DNA metabarcoding
Open the record for dataset details and reuse information.
CSM09 Small mammal host-parasite sampling data associated with the Consume herbivore exclusion plots across two burned and native-grazed watersheds at Konza Prairie
Data set contains summaries of the number of individuals of each species of small mammal captured (relative abundance) on each trapping grid. Each record contains date, treatment, grid, trap station, species, specimen number, recapture status, specimen disposition, external body measurements (where applicable), reproductive information, and miscellaneous associated comments. These sampling records are based on nightly captures during one 4-night trapping period in fall (October concurrent with annual bison roundup activites) for each of 4 permanent trapping grids established on two fire/grazing treatments (two grids per treatment). These treatments are both grazed by native grazers (bison) and include one treatment burned annually (N1A) and one treatment burned every 4 years (N4B). In each treatment, sampling grids are arranged as 5 x 10 permanent stakes spaced 10m apart and labeled numerically between 1-50 for grid A and 51-100 for grid B. One grid per treatment (grid A) is sampled using capture-mark-release methods and the other grid in each treatment (grid B) is sampled using specimen removal and subsequent whole body processing and curation.
Fig. 1 in Pax islamita (Araneae: Zodariidae) as a new host of an acrocerid fly from Israel
Fig. 1: a. retreat built by an infected Pax individual; b. carcass of Pax. Notice the dorsal opening on opisthosoma used by larva of Ogcodes for emergence (arrow); c. larva, after emergence; d. puparium; e. adult male, dorsal side; f. adult male, lateral side. Scale = 5 mm
Figure 8 in Systematics, host plants, and life histories of three new Phyllocnistis species from the central highlands of Costa Rica (Lepidoptera, Gracillariidae, Phyllocnistinae)
Figure 8. Phyllocnistis maxberryi sp. n., pupa. A Ventral view of head B ventral view of cocoon-cutter C frons D lateral view of head E lateral view of cocoon-cutter F dorsal of sixth abdominal tergum G spines on sixth abdominal tergum H lateral view of spines on seventh abdominal tergum I view of abdominal tip ฤฎ dorsal view of A9โ10 K lateral seta on sixth abdominal tergum L ventral view of A9โ10. Scale bars 100 ยตm.
Figure 6 in Systematics, host plants, and life histories of three new Phyllocnistis species from the central highlands of Costa Rica (Lepidoptera, Gracillariidae, Phyllocnistinae)
Figure 6. Phyllocnistis tropaeolicola sp. n., genitalia. A Male, ventral view B right valva, mesal view C aedeagus D female, lateral view E ventral view of terminal segments. (Scale bar 0.5 mm except for figure B, 0.25 mm.)
Figure 2 in Systematics, host plants, and life histories of three new Phyllocnistis species from the central highlands of Costa Rica (Lepidoptera, Gracillariidae, Phyllocnistinae)
Figure 2. Adults of three new Phyllocnistis species from Costa Rica. A Phyllocnistis drimiphaga sp. n., holotype female B P. maxberryi sp. n., holotype female (abdomen removed for dissection) C P. tropaeolicola sp. n., holotype male.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.