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Cristiane P. G. Calixto

dblp:201/5546 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0002-9935-9325ORCID · reported

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics
alternative splicing analysis
0.312017
TSIS: an R package to infer alternative splicing isoform switches for time-series data · Bioinform. 2017
Bioinformatics and computational biology › transcriptomics › alternative splicing analysis
isoform switch detection
0.312017
TSIS: an R package to infer alternative splicing isoform switches for time-series data · Bioinform. 2017
Bioinformatics and computational biology › gene expression analysis
time-series gene expression analysis
0.112017
TSIS: an R package to infer alternative splicing isoform switches for time-series data · Bioinform. 2017

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

statistical testing · 0.3
YearPublicationVenuePosition
2017 TSIS: an R package to infer alternative splicing isoform switches for time-series data
abstract
SUMMARY: An alternative splicing isoform switch is where a pair of transcript isoforms reverse their relative expression abundances in response to external or internal stimuli. Although computational methods are available to study differential alternative splicing, few tools for detection of isoform switches exist and these are based on pairwise comparisons. Here, we provide the TSIS R package, which is the first tool for detecting significant transcript isoform switches in time-series data. The main steps of TSIS are to search for the isoform switch points in the time-series, characterize the switches and filter the results with user input parameters. All the functions are integrated into a Shiny App for ease of implementation of the analysis. AVAILABILITY AND IMPLEMENTATION: The TSIS package is available on GitHub: https://github.com/wyguo/TSIS. CONTACT: [email protected].
Cristiane P. G. Calixto, John W. S. Brown, Runxuan Zhang
Bioinform.2