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Peter C. Fineran

dblp:147/7107 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0002-4639-6704ORCID · 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 › functional genomics
CRISPR analysis
0.212014
Accurate computational prediction of the transcribed strand of CRISPR non-coding RNAs · Bioinform. 2014
Bioinformatics and computational biology
genomics
0.212014
Accurate computational prediction of the transcribed strand of CRISPR non-coding RNAs · Bioinform. 2014

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

weighted voting · 0.2sequence feature analysis · 0.2
YearPublicationVenuePosition
2014 Accurate computational prediction of the transcribed strand of CRISPR non-coding RNAs
abstract
MOTIVATION: CRISPR RNAs (crRNAs) are a type of small non-coding RNA that form a key part of an acquired immune system in prokaryotes. Specific prediction methods find crRNA-encoding loci in nearly half of sequenced bacterial, and three quarters of archaeal, species. These Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) arrays consist of repeat elements alternating with specific spacers. Generally one strand is transcribed, producing long pre-crRNAs, which are processed to short crRNAs that base pair with invading nucleic acids to facilitate their destruction. No current software for the discovery of CRISPR loci predicts the direction of crRNA transcription. RESULTS: We have developed an algorithm that accurately predicts the strand of the resulting crRNAs. The method uses as input CRISPR repeat predictions. CRISPRDirection uses parameters that are calculated from the CRISPR repeat predictions and flanking sequences, which are combined by weighted voting. The prediction may use prior coding sequence annotation but this is not required. CRISPRDirection correctly predicted the orientation of 94% of a reference set of arrays. AVAILABILITY AND IMPLEMENTATION: The Perl source code is freely available from http://bioanalysis.otago.ac.nz/CRISPRDirection.
Ambarish Biswas, Peter C. Fineran, Chris M. Brown
Bioinform.2