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Hugh J. Willison

dblp:254/3571 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › bioimage informatics
bioimage analysis
0.412019
MyelinJ: an ImageJ macro for high throughput analysis of myelinating cultures · Bioinform. 2019
Bioinformatics and computational biology › bioimage informatics › bioimage analysis › microscopy image analysis
fluorescence microscopy
0.412019
MyelinJ: an ImageJ macro for high throughput analysis of myelinating cultures · Bioinform. 2019

Methods — techniques the papers use, named apart from their topics

local contrast normalization · 0.4grayscale morphology · 0.4frangi vesselness · 0.4false discovery rate · 0.4
YearPublicationVenuePosition
2019 MyelinJ: an ImageJ macro for high throughput analysis of myelinating cultures
abstract
SUMMARY: MyelinJ is a free user friendly ImageJ macro for high throughput analysis of fluorescent micrographs such as 2D-myelinating cultures and statistical analysis using R. MyelinJ can analyse single images or complex experiments with multiple conditions, where the ggpubr package in R is automatically used for statistical analysis and the production of publication quality graphs. The main outputs are percentage (%) neurite density and % myelination. % neurite density is calculated using the normalize local contrast algorithm, followed by thresholding, to adjust for differences in intensity. For % myelination the myelin sheaths are selected using the Frangi vesselness algorithm, in conjunction with a grey scale morphology filter and the removal of cell bodies using a high intensity mask. MyelinJ uses a simple graphical user interface and user name system for reproducibility and sharing that will be useful to the wider scientific community that study 2D-myelination in vitro. AVAILABILITY AND IMPLEMENTATION: MyelinJ is freely available at https://github.com/BarnettLab/MyelinJ. For statistical analysis the freely available R and the ggpubr package are also required. MyelinJ has a user guide (Supplementary Material) and has been tested on both Windows (Windows 10) and Mac (High Sierra) operating systems. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Michael J. Whitehead, George A. McCanney, Hugh J. Willison, Susan C. Barnett
Bioinform.3