1,720,960 research outputs found
MarineCyanophageHostGenes
No full textThese fasta files contain the reference sequences for the phylogenetic trees created in “Associations between picocyanobacterial ecotypes and cyanophage host genes across ocean basins and depth” by Clara A. Fuchsman, David Garcia-Prieto, Matthew D. Hays, Jacob A. Cram from the University of Maryland Center for Environmental Science Horn Point Laboratory. The reference sequences are a combination of sequences downloaded from NCBI, and proteins/genes from assembled contigs from the ETNP, HOT viromes and BioGeotraces (Fuchsman et al., 2017; Biller et al., 2018; Luo et al., 2020). </p
Hatchery2021AmpliconsAnalysis
No full textAnalyzing amplicon sequence data. This includes data wrangling plotting figures, making tables and running statistics, from 2021 hatchery runs. Data include healthy and crashed runs from several time-points.</p
Chesapeake_2019_Amplicon_Processing
No full textPipeline for dada2 processing of raw amplicon sequence data form the CB2019 project</p
BeachedSeaLions
No full textProvides data and analysis to accompany the manuscript, soon to be submitted with the title Quantifying the linkages between California sea lion (Zalophus californianus) strandings and particulate domoic acid concentrations at piers across Southern California, by Jayme Smith et al.Compares sea-lion strandings in orange county to DA observations and finds a positive relationship between them.</p
Hatchery2021_ProcAmplicons
No full textProcessing amplicon sequence data from 2021 hatchery runs using DADA2</p
CyanoVirLasso
No full textCode for generating lasso based networks of statistical associations between cyanobacteria and cyanophage host-genes.</p
Chesapeake_Mainstem_2019_Fractions_Analysis
No full textAnalysis of particle size fractions from the mainstem of the Chesapeake Bay 2019</p
CyanoVirLasoo
No full textCode for generating lasso based networks of statistical associations between cyanobacteria and cyanophage host-genes.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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