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Aleksandar Radovanovic

dblp:44/7245 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0002-8749-7608ORCID · reported

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene regulation
gene regulation analysis
0.312017
bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli · Bioinform. 2017
Bioinformatics and computational biology › gene regulation › promoter analysis
promoter prediction
0.312017
bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli · Bioinform. 2017
Bioinformatics and computational biology › genome annotation
prokaryotic genome annotation
0.112017
bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli · Bioinform. 2017

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

position weight matrix · 0.3machine learning classification · 0.3
YearPublicationVenuePosition
2017 bTSSfinder: a novel tool for the prediction of promoters in cyanobacteria and Escherichia coli
abstract
Motivation: The computational search for promoters in prokaryotes remains an attractive problem in bioinformatics. Despite the attention it has received for many years, the problem has not been addressed satisfactorily. In any bacterial genome, the transcription start site is chosen mostly by the sigma (σ) factor proteins, which control the gene activation. The majority of published bacterial promoter prediction tools target σ 70 promoters in Escherichia coli . Moreover, no σ-specific classification of promoters is available for prokaryotes other than for E. coli . Results: Here, we introduce bTSSfinder, a novel tool that predicts putative promoters for five classes of σ factors in Cyanobacteria (σ A , σ C , σ H , σ G and σ F ) and for five classes of sigma factors in E. coli (σ 70 , σ 38 , σ 32 , σ 28 and σ 24 ). Comparing to currently available tools, bTSSfinder achieves higher accuracy (MCC = 0.86, F 1 -score = 0.93) compared to the next best tool with MCC = 0.59, F 1 -score = 0.79) and covers multiple classes of promoters. Availability and Implementation: bTSSfinder is available standalone and online at http://www.cbrc.kaust.edu.sa/btssfinder . Contacts: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Ilham A. Shahmuradov, Rozaimi Mohamad Razali, Salim Bougouffa, Aleksandar Radovanovic, Vladimir B. Bajic
Bioinform.4