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Melissa Grant-Peters

dblp:323/9710 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · none

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › bioimage informatics
bioimage analysis
0.612022
Photizo: an open-source library for cross-sample analysis of FTIR spectroscopy data · Bioinform. 2022
Bioinformatics and computational biology › proteomics › mass spectrometry data analysis
spectral preprocessing
0.612022
Photizo: an open-source library for cross-sample analysis of FTIR spectroscopy data · Bioinform. 2022

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

principal component analysis · 0.6clustering · 0.6
YearPublicationVenuePosition
2022 Photizo: an open-source library for cross-sample analysis of FTIR spectroscopy data
abstract
MOTIVATION: With continually improved instrumentation, Fourier transform infrared (FTIR) microspectroscopy can now be used to capture thousands of high-resolution spectra for chemical characterization of a sample. The spatially resolved nature of this method lends itself well to histological profiling of complex biological specimens. However, current software can make joint analysis of multiple samples challenging and, for large datasets, computationally infeasible. RESULTS: To overcome these limitations, we have developed Photizo-an open-source Python library enabling high-throughput spectral data pre-processing, visualization and downstream analysis, including principal component analysis, clustering, macromolecular quantification and mapping. Photizo can be used for analysis of data without a spatial component, as well as spatially resolved data, obtained e.g. by scanning mode IR microspectroscopy and IR imaging by focal plane array detector. AVAILABILITY AND IMPLEMENTATION: The code underlying this article is available at https://github.com/DendrouLab/Photizo with access to example data available at https://zenodo.org/record/6417982#.Yk2O9TfMI6A.
Melissa Grant-Peters, Charlotte Rich-Griffin, Jonathan E. Grant-Peters, Gianfelice Cinque, Calliope A. Dendrou
Bioinform.1