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Aparna Bhaduri

dblp:86/11186 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0003-4625-6899ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2 · 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
2 papers
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 100%

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
single-cell analysis
0.512021
UCSC Cell Browser: visualize your single-cell data · Bioinform. 2021
Bioinformatics and computational biology › single-cell analysis
single-cell visualization
0.512021
UCSC Cell Browser: visualize your single-cell data · Bioinform. 2021
Bioinformatics and computational biology › gene expression analysis
gene expression visualization
0.112021
UCSC Cell Browser: visualize your single-cell data · Bioinform. 2021
Bioinformatics and computational biology › metagenomics
pathogen detection
0.112012
Rapid identification of non-human sequences in high-throughput sequencing datasets · Bioinform. 2012
High-performance computing
sequence alignment
0.012012
Rapid identification of non-human sequences in high-throughput sequencing datasets · Bioinform. 2012

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

web-based visualization · 0.5python package · 0.5assembly · 0.3alignment · 0.3
YearPublicationVenuePosition
2021 UCSC Cell Browser: visualize your single-cell data
abstract
SUMMARY: As the use of single-cell technologies has grown, so has the need for tools to explore these large, complicated datasets. The UCSC Cell Browser is a tool that allows scientists to visualize gene expression and metadata annotation distribution throughout a single-cell dataset or multiple datasets. AVAILABILITY AND IMPLEMENTATION: We provide the UCSC Cell Browser as a free website where scientists can explore a growing collection of single-cell datasets and a freely available python package for scientists to create stable, self-contained visualizations for their own single-cell datasets. Learn more at https://cells.ucsc.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Matthew L. Speir, Aparna Bhaduri, Nikolay S. Markov, Pablo A. Moreno, Tomasz J. Nowakowski, Irene Papatheodorou, Alex A. Pollen, Brian J. Raney, Lucas Seninge, W. James Kent, Maximilian Haeussler
Bioinform.2
2012 Rapid identification of non-human sequences in high-throughput sequencing datasets
abstract
UNLABELLED: Rapid identification of non-human sequences (RINS) is an intersection-based pathogen detection workflow that utilizes a user-provided custom reference genome set for identification of non-human sequences in deep sequencing datasets. In <2 h, RINS correctly identified the known virus in the dataset SRR73726 and is compatible with any computer capable of running the prerequisite alignment and assembly programs. RINS accurately identifies sequencing reads from intact or mutated non-human genomes in a dataset and robustly generates contigs with these non-human sequences (Supplementary Material). AVAILABILITY: RINS is available for free download at http://khavarilab.stanford.edu/resources.html.
Aparna Bhaduri, Kun Qu, Carolyn S. Lee, Alexander Ungewickell, Paul A. Khavari
Bioinform.1