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Rachel E. Klevit

dblp:196/5514 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1 · 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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
protein dynamics
0.812024
HDXBoxeR: an R package for statistical analysis and visualization of multiple Hydrogen-Deuterium Exchange Mass-Spectrometry datasets of different protein states · Bioinform. 2024
Bioinformatics and computational biology
proteomics
0.812024
HDXBoxeR: an R package for statistical analysis and visualization of multiple Hydrogen-Deuterium Exchange Mass-Spectrometry datasets of different protein states · Bioinform. 2024

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

statistical analysis · 0.8
YearPublicationVenuePosition
2024 HDXBoxeR: an R package for statistical analysis and visualization of multiple Hydrogen-Deuterium Exchange Mass-Spectrometry datasets of different protein states
abstract
SUMMARY: Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS) is a powerful protein characterization technique that provides insights into protein dynamics and flexibility at the peptide level. However, analyzing HDX-MS data presents a significant challenge due to the wealth of information it generates. Each experiment produces data for hundreds of peptides, often measured in triplicate across multiple time points. Comparisons between different protein states create distinct datasets containing thousands of peptides that require matching, rigorous statistical evaluation, and visualization. Our open-source R package, HDXBoxeR, is a comprehensive tool designed to facilitate statistical analysis and comparison of multiple sets among samples and time points for different protein states, along with data visualization. AVAILABILITY AND IMPLEMENTATION: HDXBoxeR is accessible as the R package (https://cran.r-project.org/web//packages/HDXBoxeR) and GitHub: mkajano/HDXBoxeR.
Maria K. Janowska, Katherine Reiter, Pearl Magala, Miklos Guttman, Rachel E. Klevit
Bioinform.5