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Utpal Smart

dblp:281/7420 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
genomics
0.412020
Numt identification and removal with RtN! · Bioinform. 2020
Bioinformatics and computational biology › genomics
mitochondrial genomics
0.412020
Numt identification and removal with RtN! · Bioinform. 2020
Bioinformatics and computational biology › sequence analysis
read mapping
0.412020
Numt identification and removal with RtN! · Bioinform. 2020
Bioinformatics and computational biology › genomics
variant calling
0.412020
Numt identification and removal with RtN! · Bioinform. 2020

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

sequence similarity search · 0.4read categorization · 0.4
YearPublicationVenuePosition
2020 Numt identification and removal with RtN!
abstract
MOTIVATION: Assays in mitochondrial genomics rely on accurate read mapping and variant calling. However, there are known and unknown nuclear paralogs that have fundamentally different genetic properties than that of the mitochondrial genome. Such paralogs complicate the interpretation of mitochondrial genome data and confound variant calling. RESULTS: Remove the Numts! (RtN!) was developed to categorize reads from massively parallel sequencing data not based on the expected properties and sequence identities of paralogous nuclear encoded mitochondrial sequences, but instead using sequence similarity to a large database of publicly available mitochondrial genomes. RtN! removes low-level sequencing noise and mitochondrial paralogs while not impacting variant calling, while competing methods were shown to remove true variants from mitochondrial mixtures. AVAILABILITY AND IMPLEMENTATION: https://github.com/Ahhgust/RtN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
August E. Woerner, Jennifer Churchill Cihlar, Utpal Smart, Bruce Budowle
Bioinform.3