cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4056282.v1
title: Where are Australian jobs growing or shrinking (2002 - 2014; over 100 regions; SA4 level)?

description: This data - count of employees by 100 regions within Australia (over 12 years; 2002 - 2014) - 8.5M 2002 -&gt; 10.3M 2014.Parent data - Employee $ DATA by detailed occupation, by location (SA4), by year; This dataset is an aggregation of all Australian Salaries and Wages by location and over 12 years in four year snapshots (2002, 2006, 2010, 2014). Some data excluded which was not allocated to a SA4 location. Source Data from ATO; Australian Tax Office.<br><br>HeadcountRaw.csv provides total data (employee count). Includes total counts per SA4 location, and percent change between each of the years; 2002 - 6; 2006 - 10; 2010 - 14 eg 101 means 1% increase.<br>HeadcountRaw_display.csv provides data (employee count) to visualise at (1) National Map.gov.au or (2) Aurin.org.au. This only includes the data for SA4 regions which can be visualised.<br>Method; CSV files loaded into MariaDB on Nectar Infrastructure (refer NCRIS). Access through http://areff2000.net16.net.<br>Data request at: data.gov.au Ideascale<br>Original data (parent data) at: data.gov.auParent data description: "Individuals data for 2001-02, 2005-06, 2009-10 and 2013-14 income years. Table 1: Salary and Wages income, by Occupation and SA4 location Table 2: Sole trader business income, by Industry and SA4 location." Sole trader data not included in this sub-collection.<br>See analysis in progress for:=&gt; Individual income by occupation / location <br>at: http://areff2000.net16.net<br>To recreate #datavis - How To <b>To view on National Map (data.gov.au mapping tool).</b> 1. Save data as csv. Data (loaded here), currently at: http://118.138.240.130/sa4_deltaHeadcountRaw_display.csv2. Open http://nationalmap.gov.au. 3. Click 'Add Data'. <br>4. Drag csv file onto map. 5. Click Done. <br>6. Select Year in control panel (lower left of screen). Raw shows count of jobs. Year shows % change from four years earlier. <br>7. Click on region (SA4) to see data for that region.<br><b>Data format</b>: Year | Occupation | Location (SA4) | Count of Workers | $ of Workers <br>* Year: [2002, 2006, 2010, 2014]<br><br>* Salary and Wages; 200,000 lines (summary only included here)<br>* Sole Proprietors; 100,000 lines (not included here)* Occupation: Description at Australian Bureau of Statistics. (3,216 lines) (link below)* SA4 Location descriptions at: http://stat.abs.gov.au/itt/r.jsp?databyregion#/. #dataTotals - Salary and WagesYearWorkers (M)Earnings ($B)GDP USD($B)20028.528540020069.4372746201010.24811142201410.35841450Table 1: Aust. Salary and Wages 2002 - 2014.GDP info from: Trading Economics (link below).<br>#datavis1. Chloro images made at aurin.org.au (AU researcher login required).2. Red/Orange (year.tiff) images made at nationalmap.org.au
DOI: 10.7910/dvn/v1rjpf/qb1v6w
title: blc20150921_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/qr1fy1
title: blc20150322_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/ngdn06
title: blc20150605_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/xxjyln
title: blc20150927_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4056246
title: SDF file containing EPA Comptox Chemistry Dashboard Structures and Mappings to PubChem

description: The foundation of chemical safety testing relies on chemistry information such as high-quality chemical structures and physical chemical properties. This information is used by scientists to predict the potential health risks of chemicals.<br>The iCSS CompTox Chemistry Dashboard is part of a suite of dashboards developed by EPA to help evaluate the safety of chemicals. The dashboard provides access to a variety of information on over 700,000 chemicals currently in use.<br> Within the dashboard, users can access chemical structures, experimental and predicted physicochemical and toxicity data, and additional links to relevant websites and applications. It maps curated physicochemical property data associated with chemical substances to their corresponding chemical structures.<br>This data are compiled from sources including the EPA’s computational toxicology research databases, and public domain databases such as the National Center for Biotechnology Information’s PubChem database. <br>This dataset is an SDF file containing all of the chemical structures in the dashboard and mappings between the DTXSIDs and the associated PubChem IDs<br>This file is the version produced by an export of the database on July 25th 2016
DOI: 10.7910/dvn/v1rjpf/mcfjmp
title: blc20150804_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/qp8agf
title: blc20150925_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/a4ymv3
title: blc20150613_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/kradkm
title: blc20150718_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4056213
title: Dataset for: Estimation of conditional and marginal odds ratios using the prognostic score

description: Introduced by Hansen in 2008, the prognostic score (PGS) has been presented as ``the prognostic analogue of the propensity score'' (PPS). PPS-based methods are intended to estimate marginal effects. Most previous studies evaluated the performance of existing PGS-based methods (adjustment, stratification and matching using the PGS) in situations in which the theoretical conditional and marginal effects are equal (i.e., collapsible situations). To support the use of PGS framework as an alternative to the PPS framework, applied researchers must have a reliable information about the type of treatment effect estimated by each method. We propose four new PGS-based methods, each developed to estimate a specific type of treatment effect. We evaluated the ability of existing and new PGS-based methods to estimate the conditional treatment effect (CTE), the (marginal) average treatment effect on the whole population (ATE), and the (marginal) average treatment effect on the treated population (ATT), when the odds ratio (a non-collapsible estimator) is the measure of interest. The performance of PGS-based methods was assessed by Monte Carlo simulations and compared to PPS-based methods and multivariate regression analysis. Existing PGS-based methods did not allow for estimating the ATE and showed from unacceptable performance when the proportion of exposed subjects was large. When estimating marginal effects, PPS-based methods were too conservative, whereas the new PGS-based methods performed better with low prevalence of exposure, and had coverages closer to the nominal value. When estimating CTE, new PGS-based methods performed as well as traditional multivariate regression.
DOI: 10.7910/dvn/v1rjpf/yabbui
title: blc20150916_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4056213.v1
title: Dataset for: Estimation of conditional and marginal odds ratios using the prognostic score

description: Introduced by Hansen in 2008, the prognostic score (PGS) has been presented as ``the prognostic analogue of the propensity score'' (PPS). PPS-based methods are intended to estimate marginal effects. Most previous studies evaluated the performance of existing PGS-based methods (adjustment, stratification and matching using the PGS) in situations in which the theoretical conditional and marginal effects are equal (i.e., collapsible situations). To support the use of PGS framework as an alternative to the PPS framework, applied researchers must have a reliable information about the type of treatment effect estimated by each method. We propose four new PGS-based methods, each developed to estimate a specific type of treatment effect. We evaluated the ability of existing and new PGS-based methods to estimate the conditional treatment effect (CTE), the (marginal) average treatment effect on the whole population (ATE), and the (marginal) average treatment effect on the treated population (ATT), when the odds ratio (a non-collapsible estimator) is the measure of interest. The performance of PGS-based methods was assessed by Monte Carlo simulations and compared to PPS-based methods and multivariate regression analysis. Existing PGS-based methods did not allow for estimating the ATE and showed from unacceptable performance when the proportion of exposed subjects was large. When estimating marginal effects, PPS-based methods were too conservative, whereas the new PGS-based methods performed better with low prevalence of exposure, and had coverages closer to the nominal value. When estimating CTE, new PGS-based methods performed as well as traditional multivariate regression.
DOI: 10.7910/dvn/v1rjpf/1hrb28
title: blc20150507_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/5rkfa5
title: blc20150602_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/utcpvn
title: blc20150215_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4056174
title: Input Data

description: Shapefile of weather station data, and database of county climate change perceptions<br>#R_Start: starting year of the record for the station.#R_End: ending year of the record for the station.#R_Length: among all 365 days, what is the max length of record.#R_Gap: number of years that data is missing.#R_Min: among all 365 days, what is the min length of record. <br>Climate change perceptions#happen_P = % believing global warming is happening<br><br><br>
DOI: 10.7910/dvn/v1rjpf/tnnk82
title: blc20150412_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4056174.v1
title: Input Data

description: Shapefile of weather station data, and database of county climate change perceptions<br>#R_Start: starting year of the record for the station.#R_End: ending year of the record for the station.#R_Length: among all 365 days, what is the max length of record.#R_Gap: number of years that data is missing.#R_Min: among all 365 days, what is the min length of record. <br>Climate change perceptions#happen_P = % believing global warming is happening<br><br><br>
DOI: 10.7910/dvn/v1rjpf/erqsd0
title: blc20150227_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4056189.v2
title: Titanium dioxide nanoparticles: the importance of shape and exposed facets in surface-molecule interactions

description: Slides of the oral contribution presented at the XLIV National Congress of Physical Chemistry, Naples, Italy, September 20-23, 2016
DOI: 10.7910/dvn/v1rjpf/pmccw9
title: blc20150702_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/xhasm5
title: blc20150720_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/grfvyf
title: blc20150524_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/yyg2hb
title: blc20150725_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/yi3pcz
title: blc20150930_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/vwmass
title: blc20150712_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/aduuou
title: blc20151223_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/9wgffg
title: blc20150901_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/jtoyk8
title: blc20150122_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4056066
title: Early stage of cytomegalovirus infection suppresses host microRNA expression regulation in human fibroblasts

description: Responses to human cytomegalovirus (HCMV) infection are largely individual and cell type specific. We investigated molecular profiles in 2 primary cell cultures of human fibroblasts, which are highly or marginally sensitive to HCMV infection, respectively. We screened expression of genes and microRNAs (miRs) at the early (3 hours) stage of infection. To assess molecular pathway activation profiles, we applied bioinformatic algorithms OncoFinder and MiRImpact. In both cell types, pathway regulation properties at mRNA and miR levels were markedly different. Surprisingly, in the infected highly sensitive cells, we observed a “freeze” of miR expression profiles compared to uninfected controls. Our results evidence that in the sensitive cells, HCMV blocks intracellular regulation of microRNA expression already at the earliest stage of infection. These data suggest somewhat new functions for HCMV products and demonstrate dependence of miR expression arrest on the host-encoded factors.
DOI: 10.6084/m9.figshare.4056066.v1
title: Early stage of cytomegalovirus infection suppresses host microRNA expression regulation in human fibroblasts

description: Responses to human cytomegalovirus (HCMV) infection are largely individual and cell type specific. We investigated molecular profiles in 2 primary cell cultures of human fibroblasts, which are highly or marginally sensitive to HCMV infection, respectively. We screened expression of genes and microRNAs (miRs) at the early (3 hours) stage of infection. To assess molecular pathway activation profiles, we applied bioinformatic algorithms OncoFinder and MiRImpact. In both cell types, pathway regulation properties at mRNA and miR levels were markedly different. Surprisingly, in the infected highly sensitive cells, we observed a “freeze” of miR expression profiles compared to uninfected controls. Our results evidence that in the sensitive cells, HCMV blocks intracellular regulation of microRNA expression already at the earliest stage of infection. These data suggest somewhat new functions for HCMV products and demonstrate dependence of miR expression arrest on the host-encoded factors.
DOI: 10.7910/dvn/v1rjpf/emhcju
title: blc20150705_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/2rpzk0
title: blc20150308_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/0q2036
title: blc20150521_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/siq9m5
title: blc20151117_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/bvnb07
title: blc20151219_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/oy277r
title: blc20150905_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/wvggxp
title: blc20150421_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055997
title: MCMC time-calibrated tree of 16 Diptera: Orthorrhapha species (Fig. 7)

description: MCMC time-calibrated tree of 16 Diptera: Orthorrhapha, Nexus format and PNG format
DOI: 10.7910/dvn/v1rjpf/eegxd4
title: blc20151206_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/wivrj2
title: blc20150120_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055997.v4
title: MCMC time-calibrated tree of 16 Diptera: Orthorrhapha species (Fig. 7)

description: MCMC time-calibrated tree of 16 Diptera: Orthorrhapha, Nexus format and PNG format
DOI: 10.7910/dvn/v1rjpf/llmxqa
title: blc20150621_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/skerdp
title: blc20150401_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055961
title: Data - Genetics - Porto et al 2016

description: ## add_effect_vectors<br>folder containing the standardized additive effect vectors<br>## coded_marker_dataGenotypes for all markers, separated by chromosome. Genotype coding is described in the main text<br>## mouse_pleio_vectorsMouse pleiotropy vectors used in the simulation. Values of 1 correspond to a trait being affected by that locus. Zero means no effect.The manuscript corresponding to the mouse data is being submitted separately from this manuscript.<br>## phenotype_covariatesPhenotypes and covariates used when fitting the mixed models.<br>##sas_code Code used to perform trait-specific QTL mapping<br>## matricesG and P matrices calculated from the QTL data<br>
DOI: 10.6084/m9.figshare.4055970.v1
title: Modern graphical methods to compare two groups of observations

description: Data and R code to reproduce the figures in our EJN technical spotlight:<br>Modern graphical methods to compare two groups of observationsGuillaume A. Rousselet, Cyril R. Pernet, Rand R. WilcoxEuropean Journal of Neuroscience (submitted)<br>Also contains all the figures in tif format, and Matlab code implementing the main R functions.
DOI: 10.7910/dvn/v1rjpf/wrfkeg
title: blc20151027_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055955
title: Data-Fig1-OAsugarpaper

description: This data shows that tbh flies have a lower response to sugar in the Proboscis extension assay.<br>Metadata and code for analysis will follow.<br>
DOI: 10.7910/dvn/v1rjpf/wdpsdy
title: blc20150525_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055970.v2
title: Modern graphical methods to compare two groups of observations

description: Data and R code to reproduce the figures in our EJN technical spotlight:<br>Modern graphical methods to compare two groups of observationsGuillaume A. Rousselet, Cyril R. Pernet, Rand R. WilcoxEuropean Journal of Neuroscience (submitted)<br>Also contains a pdf version of the submitted article, all the figures in tif format, and Matlab code implementing the main R functions.
DOI: 10.6084/m9.figshare.4055955.v1
title: Data-Fig1-OAsugarpaper

description: This data shows that tbh flies have a lower response to sugar in the Proboscis extension assay.<br>Metadata and code for analysis will follow.<br>
DOI: 10.7910/dvn/v1rjpf/7y5yfi
title: blc20150604_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055913
title: Individual gene trees of 9,080 orthologs of 16 Diptera: Orthorrhapha analyzed in RAxML

description: Individual gene trees of 9,080 orthologs of 16 Diptera: Orthorrhapha analyzed in RAxML, Newick format
DOI: 10.6084/m9.figshare.4055913.v1
title: Individual gene trees of 9,080 orthologs of 16 Diptera: Orthorrhapha analyzed in RAxML

description: Individual gene trees of 9,080 orthologs of 16 Diptera: Orthorrhapha analyzed in RAxML, Newick format
DOI: 10.7910/dvn/v1rjpf/s9g6ks
title: blc20150714_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055910
title: RAxML tree of 16 Diptera: Orthorrhapha species based on ML analysis of 9,080 orthologs with four or more taxa with bootstrap (Fig. 5)

description: RAxML tree of 16 Diptera: Orthorrhapha species based on ML analysis of 9,080 orthologs with four or more taxa with bootstrap, Nexus format and PNG format
DOI: 10.7910/dvn/v1rjpf/hvv74z
title: blc20150823_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/eorao9
title: blc20151003_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055970.v6
title: Beyond differences in means: robust graphical methods to compare two groups in neuroscience

description: Data and R code to reproduce the figures in our EJN technical spotlight:<br>Beyond differences in means: robust graphical methods to compare two groups in neuroscienceGuillaume A. Rousselet, Cyril R. Pernet, Rand R. Wilcox<br>European Journal of Neuroscience (in press)<br>Also contains a pdf version of the accepted article, all the figures in tif format, and Matlab code implementing the main R functions.
DOI: 10.7910/dvn/v1rjpf/btm7ka
title: blc20150829_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055886
title: Human_CVD_All_Years_Top250_Genes.xlsx

description: This table contains the top-250 genes relevant to Cardiovascular diseases using the method described here: http://dx.doi.org/10.1016/j.jacc.2015.04.072.
DOI: 10.6084/m9.figshare.4055886.v1
title: Human_CVD_All_Years_Top250_Genes.xlsx

description: This table contains the top-250 genes relevant to Cardiovascular diseases using the method described here: http://dx.doi.org/10.1016/j.jacc.2015.04.072.
DOI: 10.6084/m9.figshare.4055910.v1
title: RAxML tree of 16 Diptera: Orthorrhapha species based on of ML analysis of 9,080 orthologs with four or more taxa with bootstrap

description: RAxML tree of 16 Diptera: Orthorrhapha species based on of ML analysis of 9,080 orthologs with four or more taxa with bootstrap
DOI: 10.7910/dvn/v1rjpf/ofzlsw
title: blc20150822_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055910.v3
title: RAxML tree of 16 Diptera: Orthorrhapha species based on ML analysis of 9,080 orthologs with four or more taxa with bootstrap (Fig. 5)

description: RAxML tree of 16 Diptera: Orthorrhapha species based on ML analysis of 9,080 orthologs with four or more taxa with bootstrap, Nexus format and PNG format
DOI: 10.6084/m9.figshare.4055814
title: Partitions of concatenated alignment of 9,080 putative orthologs of 16 Diptera: Orthorrhapha species produced by PartitionFinderProtein

description: Partitions of concatenated alignment of 9,080 putative orthologs of 16 Diptera: Orthorrhapha species produced by PartitionFinderProtein, plain text format
DOI: 10.6084/m9.figshare.4055910.v2
title: RAxML tree of 16 Diptera: Orthorrhapha species based on ML analysis of 9,080 orthologs with four or more taxa with bootstrap

description: RAxML tree of 16 Diptera: Orthorrhapha species based on ML analysis of 9,080 orthologs with four or more taxa with bootstrap, Nexus format
DOI: 10.7910/dvn/v1rjpf/rxuat3
title: blc20151012_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055814.v1
title: Partitions of concatenated alignment of 9,080 putative orthologs of 16 Diptera: Orthorrhapha species produced by PartitionFinderProtein

description: Partitions of concatenated alignment of 9,080 putative orthologs of 16 Diptera: Orthorrhapha species produced by PartitionFinderProtein, plain text format
DOI: 10.6084/m9.figshare.4055781
title: Astral tree of 16 Diptera: Orthorrhapha species based on based on RAxML best trees for 9,080 orthologs with four or more taxa (Fig. 6)

description: Astral tree of 16 Diptera: Orthorrhapha species based on based on RAxML best trees for 9,080 orthologs with four or more taxa, Newick format and PNG format
DOI: 10.7910/dvn/v1rjpf/koufvn
title: blc20150211_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/al5dfc
title: blc20150707_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055781.v1
title: Astral tree of 16 Diptera: Orthorrhapha species based on based on RAxML best trees for 9,080 orthologs with four or more taxa

description: Astral tree of 16 Diptera: Orthorrhapha species based on based on RAxML best trees for 9,080 orthologs with four or more taxa, Newick format
DOI: 10.6084/m9.figshare.4055781.v2
title: Astral tree of 16 Diptera: Orthorrhapha species based on based on RAxML best trees for 9,080 orthologs with four or more taxa (Fig. 6)

description: Astral tree of 16 Diptera: Orthorrhapha species based on based on RAxML best trees for 9,080 orthologs with four or more taxa, Newick format and PNG format
DOI: 10.6084/m9.figshare.4055703
title: Eye_hand_6_Data

description: Data
DOI: 10.7910/dvn/v1rjpf/ti8tex
title: blc20150909_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055703.v1
title: Eye_hand_6_Data

description: Data
DOI: 10.7910/dvn/v1rjpf/vxadcc
title: blc20150810_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/qteyb3
title: blc20150110_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055664
title: Mixed glia GLAST PE CD11b FITC-Layout.tiff

description: Mixed glial cells were stained with an astrocyte marker (GLAST-PE) and a microglial marker (cd11b-FITC) and placed through flow cytometry to determine the relative populations before purification. Image file showing results of flow cytometry.
DOI: 10.6084/m9.figshare.4055664.v1
title: Mixed glia GLAST PE CD11b FITC-Layout.tiff

description: Mixed glial cells were stained with an astrocyte marker (GLAST-PE) and a microglial marker (cd11b-FITC) and placed through flow cytometry to determine the relative populations before purification. Image file showing results of flow cytometry.
DOI: 10.7910/dvn/v1rjpf/dmla6h
title: blc20150329_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/okrun0
title: blc20150430_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055643
title: Proctacanthus coquilletti de novo genome annotation (200kmer) Maker GFF file

description: Proctacanthus coquilletti de novo genome annotation (200kmer) Maker GFF file, plain text GFF format
DOI: 10.7910/dvn/v1rjpf/gaktwa
title: blc20151205_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/ucweav
title: blc20150812_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.4055643.v1
title: Proctacanthus coquilletti USNMENT01136139 genome annotation (200kmer) Maker GFF file

description: Proctacanthus coquilletti USNMENT01136139 genome annotation (200kmer) Maker GFF file, plain text GFF format