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Simona Soverini

dblp:37/10786 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0002-4508-0353ORCID · 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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › transcriptomics › RNA-seq analysis
fusion transcript detection
0.112012
Bellerophontes: an RNA-Seq data analysis framework for chimeric transcripts discovery based on accurate fusion model · Bioinform. 2012
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.112012
Bellerophontes: an RNA-Seq data analysis framework for chimeric transcripts discovery based on accurate fusion model · Bioinform. 2012

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

splicing-driven alignment · 0.1abundance estimation · 0.1
YearPublicationVenuePosition
2012 Bellerophontes: an RNA-Seq data analysis framework for chimeric transcripts discovery based on accurate fusion model
abstract
MOTIVATION: Next-generation sequencing technology allows the detection of genomic structural variations, novel genes and transcript isoforms from the analysis of high-throughput data. In this work, we propose a new framework for the detection of fusion transcripts through short paired-end reads which integrates splicing-driven alignment and abundance estimation analysis, producing a more accurate set of reads supporting the junction discovery and taking into account also not annotated transcripts. Bellerophontes performs a selection of putative junctions on the basis of a match to an accurate gene fusion model. RESULTS: We report the fusion genes discovered by the proposed framework on experimentally validated biological samples of chronic myelogenous leukemia (CML) and on public NCBI datasets, for which Bellerophontes is able to detect the exact junction sequence. With respect to state-of-art approaches, Bellerophontes detects the same experimentally validated fusions, however, it is more selective on the total number of detected fusions and provides a more accurate set of spanning reads supporting the junctions. We finally report the fusions involving non-annotated transcripts found in CML samples. AVAILABILITY AND IMPLEMENTATION: Bellerophontes JAVA/Perl/Bash software implementation is free and available at http://eda.polito.it/bellerophontes/.
Francesco Abate, Andrea Acquaviva, Giulia Paciello, Carmelo Foti, Elisa Ficarra, Alberto Ferrarini, Massimo Delledonne, Ilaria Iacobucci, Simona Soverini, Giovanni Martinelli, Enrico Macii
Bioinform.9