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Fabio C. S. Nogueira

dblp:130/1031 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
0000-0001-5507-7142ORCID · 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 › proteomics
peptide-spectrum matching
0.212013
Effectively addressing complex proteomic search spaces with peptide spectrum matching · Bioinform. 2013
Bioinformatics and computational biology
proteomics
0.212013
Effectively addressing complex proteomic search spaces with peptide spectrum matching · Bioinform. 2013

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

sequence database search · 0.2b1-fragment ion sequencing · 0.2
YearPublicationVenuePosition
2013 Effectively addressing complex proteomic search spaces with peptide spectrum matching
abstract
SUMMARY: Protein identification by mass spectrometry is commonly accomplished using a peptide sequence matching search algorithm, whose sensitivity varies inversely with the size of the sequence database and the number of post-translational modifications considered. We present the Spectrum Identification Machine, a peptide sequence matching tool that capitalizes on the high-intensity b1-fragment ion of tandem mass spectra of peptides coupled in solution with phenylisotiocyanate to confidently sequence the first amino acid and ultimately reduce the search space. We demonstrate that in complex search spaces, a gain of some 120% in sensitivity can be achieved. AVAILABILITY: All data generated and the software are freely available for academic use at http://proteomics.fiocruz.br/software/sim. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Diogo B. Lima, Yasset Pérez-Riverol, Fabio C. S. Nogueira, Gilberto B. Domont, Jesus Noda, Felipe da Veiga Leprevost, Vladimir Besada, Felipe M. G. França, Valmir C. Barbosa, Aniel Sánchez, Paulo C. Carvalho
Bioinform.3