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Tallulah S. Andrews

dblp:157/9502 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0003-1120-2196ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 2 · 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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
feature selection		 0.412019
M3Drop: dropout-based feature selection for scRNASeq · Bioinform. 2019
Bioinformatics and computational biology › single-cell analysis › single-cell RNA sequencing
single-cell RNA-seq analysis		 0.412019
M3Drop: dropout-based feature selection for scRNASeq · Bioinform. 2019
Bioinformatics and computational biology › network bioinformatics
biological network analysis		 0.212015
GeneNet Toolbox for MATLAB: a flexible platform for the analysis of gene connectivity in biological networks · Bioinform. 2015
Bioinformatics and computational biology › network bioinformatics › biological network analysis
network visualization		 0.112015
GeneNet Toolbox for MATLAB: a flexible platform for the analysis of gene connectivity in biological networks · Bioinform. 2015

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

dropout-based feature selection · 0.4seed randomization · 0.2network permutation · 0.2
YearPublicationVenuePosition
2019 M3Drop: dropout-based feature selection for scRNASeq
abstract
MOTIVATION: Most genomes contain thousands of genes, but for most functional responses, only a subset of those genes are relevant. To facilitate many single-cell RNASeq (scRNASeq) analyses the set of genes is often reduced through feature selection, i.e. by removing genes only subject to technical noise. RESULTS: We present M3Drop, an R package that implements popular existing feature selection methods and two novel methods which take advantage of the prevalence of zeros (dropouts) in scRNASeq data to identify features. We show these new methods outperform existing methods on simulated and real datasets. AVAILABILITY AND IMPLEMENTATION: M3Drop is freely available on github as an R package and is compatible with other popular scRNASeq tools: https://github.com/tallulandrews/M3Drop. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Tallulah S. Andrews, Martin Hemberg
 Bioinform.1
2015 GeneNet Toolbox for MATLAB: a flexible platform for the analysis of gene connectivity in biological networks
abstract
SUMMARY: We present GeneNet Toolbox for MATLAB (also available as a set of standalone applications for Linux). The toolbox, available as command-line or with a graphical user interface, enables biologists to assess connectivity among a set of genes of interest ('seed-genes') within a biological network of their choosing. Two methods are implemented for calculating the significance of connectivity among seed-genes: 'seed randomization' and 'network permutation'. Options include restricting analyses to a specified subnetwork of the primary biological network, and calculating connectivity from the seed-genes to a second set of interesting genes. Pre-analysis tools help the user choose the best connectivity-analysis algorithm for their network. The toolbox also enables visualization of the connections among seed-genes. GeneNet Toolbox functions execute in reasonable time for very large networks (∼10 million edges) on a desktop computer. AVAILABILITY AND IMPLEMENTATION: GeneNet Toolbox is open source and freely available from http://avigailtaylor.github.io/gntat14. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: [email protected].
Avigail Taylor, Julia Steinberg, Tallulah S. Andrews, Caleb Webber
 Bioinform.3