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Laura Seaman

dblp:211/6405 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0001-9111-9776ORCID · reported

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genome organization
0.312018
4D nucleome Analysis Toolbox: analysis of Hi-C data with abnormal karyotype and time series capabilities · Bioinform. 2018
Bioinformatics and computational biology › epigenomics
hi-c data analysis
0.312018
4D nucleome Analysis Toolbox: analysis of Hi-C data with abnormal karyotype and time series capabilities · Bioinform. 2018
Bioinformatics and computational biology › gene expression analysis
time series gene expression
0.112018
4D nucleome Analysis Toolbox: analysis of Hi-C data with abnormal karyotype and time series capabilities · Bioinform. 2018

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

hi-c normalization · 0.3
YearPublicationVenuePosition
2018 4D nucleome Analysis Toolbox: analysis of Hi-C data with abnormal karyotype and time series capabilities
abstract
Motivation: The availability of powerful analysis tools will further understanding of genome organization and its relationship to phenotype in dynamical settings. Results: The 4D Nucleome Analysis Toolbox (NAT) is a user-friendly and powerful MATLAB toolbox for time series analysis of genome-wide chromosome conformation capture (Hi-C) data and gene expression (RNA-seq). NAT can load and normalize data, define topologically associating domains, analyse translocations, produce visualization, and study time course data. We provide examples that include time series data sets and karyotypically abnormal cell lines demonstrating the flexibility of NAT. Availability and implementation: https://github.com/laseaman/4D_Nucleome_Analysis_Toolbox. Contact: [email protected].
Laura Seaman, Indika Rajapakse
Bioinform.1