1,720,969 research outputs found
Number (no.) of studies and reference genes (RGs) analysed according to: (A) species groupings (rodent = rodent model species, livestock = livestock mammal) and (B) model versus non-model species.
No full text<p>Number (no.) of studies and reference genes (RGs) analysed according to: (A) species groupings (rodent = rodent model species, livestock = livestock mammal) and (B) model versus non-model species.</p
Testing and selection of RGs in different structures of the rat brain after various treatments.
No full text<p>Shading in grey indicates the gene was tested and black indicates it was selected as within the group of most stable genes required for accurate normalisation. OB is the olfactory bulb with cerebral substructure codes provided as a footnote. Only genes tested more than once included. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0141853#pone.0141853.s005" target="_blank">S4 Table</a> for further details of each study, including treatment regime and full list of all RGs tested and selected. <sup><i>a</i></sup><i>Substructures</i>: <i>1 = Whole</i>, <i>2 = Dendate gyrus</i>, <i>3 = Auditory</i>, <i>4 = Prefrontal</i>, <i>5 = Frontal</i>, <i>6 = Temporal</i>, <i>7 = Whole + Basal ganglia</i>, <i>8 = Striatum</i>, <i>9 = Nigra</i>.</p
PRISMA flowchart.
No full text<p>The number (n) of studies included and excluded at various stages of the quantitative review process, where numbers are specified as LitRev1/LitRev2.</p
Influence of the number of GOI investigated on the rigor with which RGs are selected and used.
No full text<p>(A) Number of GOIs analysed does not affect whether or not the stability of RGs is tested. (B) Number of GOIs analysed does not affect the number of RGs used to normalise data. (C) Amongst those studies that do test a panel of RGs for stability (<i>n</i> = 19), more RGs are tested in studies subsequently analysing more GOI. For panels (B) and (C), a linear regression (solid line) and 95% confidence intervals (dotted lines) were fitted solely to show the direction of the relationship.</p
Publication of studies testing expression of GOI(s).
No full text<p>Papers included in LitRev1 showing (A) The mean number (no.) of RGs utilised in gene expression studies per year. (B) Mean no. of RGs utilised, according to whether or not a panel of RGs was first tested for stability. In both cases, data is represented as mean (dot) ± standard deviation (bars).</p
Publication of studies testing a panel of RGs for expression stability.
No full text<p>Papers included in LitRev2 showing (A) Temporal trend, and (B) Median and interquartile range of number (no.) of RGs included in stability panels per year, where whiskers span the 5–95 percentiles. Data for 2015 are shown in grey as this comprises the months January to June 2015 only.</p
Utilisation of <i>GAPDH</i> and <i>ACTB</i> and <i>18S rRNA</i> as RGs in gene expression studies since the publication of the MIQE guidelines.
No full text<p>Utilisation of <i>GAPDH</i> and <i>ACTB</i> and <i>18S rRNA</i> as RGs in gene expression studies since the publication of the MIQE guidelines.</p
Number of RGs tested for stability based on taxonomic categorisation of study organism.
No full text<p>(A) Number of RGs used per species grouping. (B) Number of RGs used in model and non-model species. In both cases, data is represented as mean (dot) ± standard deviation (bars).</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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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