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Alexander N. Stein

dblp:324/0266 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-5039-4330ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
isoform expression visualization
0.612022
ScisorWiz: visualizing differential isoform expression in single-cell long-read data · Bioinform. 2022
Bioinformatics and computational biology
transcriptomics
0.612022
ScisorWiz: visualizing differential isoform expression in single-cell long-read data · Bioinform. 2022
Bioinformatics and computational biology › transcriptomics
alternative splicing analysis
0.212022
ScisorWiz: visualizing differential isoform expression in single-cell long-read data · Bioinform. 2022

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

clustering · 0.6
YearPublicationVenuePosition
2022 ScisorWiz: visualizing differential isoform expression in single-cell long-read data
abstract
SUMMARY: RNA isoforms contribute to the diverse functionality of the proteins they encode within the cell. Visualizing how isoform expression differs across cell types and brain regions can inform our understanding of disease and gain or loss of functionality caused by alternative splicing with potential negative impacts. However, the extent to which this occurs in specific cell types and brain regions is largely unknown. This is the kind of information that ScisorWiz plots can provide in an informative and easily communicable manner. ScisorWiz affords its user the opportunity to visualize specific genes across any number of cell types, and provides various sorting options for the user to gain different ways to understand their data. ScisorWiz provides a clear picture of differential isoform expression through various clustering methods and highlights features such as alternative exons and single-nucleotide variants. Tools like ScisorWiz are key for interpreting single-cell isoform sequencing data. This tool applies to any single-cell long-read RNA sequencing data in any cell type, tissue or species. AVAILABILITY AND IMPLEMENTATION: Source code is available at http://github.com/ans4013/ScisorWiz. No new data were generated for this publication. Data used to generate figures was sourced from GEO accession token GSE158450 and available on GitHub as example data.
Alexander N. Stein, Anoushka Joglekar, Chi-Lam Poon, Hagen U. Tilgner
Bioinform.1