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Ethan Bahl

dblp:197/8261 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
transcriptomic data visualization
0.112017
cerebroViz: an R package for anatomical visualization of spatiotemporal brain data · Bioinform. 2017

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

vector graphic rendering · 0.3
YearPublicationVenuePosition
2017 cerebroViz: an R package for anatomical visualization of spatiotemporal brain data
abstract
Summary: Spatiotemporal transcriptomic profiling has provided valuable insight into the patterning of gene expression throughout the human brain from early fetal development to adulthood. When combined with prior knowledge of a disease's age at onset and region-specificity, these expression profiles have provided the necessary context to both strengthen putative gene-disease associations and infer new associations. While a wealth of spatiotemporal expression data exists, there are currently no tools available to visualize this data within the anatomical context of the brain, thus limiting the intuitive interpretation of many such findings. We present cerebroViz, an R package to map spatiotemporal brain data to vector graphic diagrams of the human brain. Our tool allows rapid generation of publication-quality figures that highlight spatiotemporal trends in the input data, while striking a balance between usability and customization. cerebroViz is generalizable to any data quantifiable at a brain-regional resolution and currently supports visualization of up to thirty regions of the brain found in databases such as BrainSpan, GTEx and Roadmap Epigenomics. Availability and Implementation: cerebroViz is freely available through GitHub ( https://github.com/ethanbahl/cerebroViz ). The tutorial is available at http://ethanbahl.github.io/cerebroViz/. Contacts: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Ethan Bahl, Tanner Koomar, Jacob J. Michaelson
Bioinform.1