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Akiyasu C. Yoshizawa

dblp:85/5955 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2015
0000-0002-0870-5502ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2

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 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural bioinformatics › macromolecular structure analysis
glycan structure analysis
0.212015
GlycanAnalysis Plug-in: a database search tool for N-glycan structures using mass spectrometry · Bioinform. 2015

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

diagnostic ion matching · 0.2database search · 0.2
YearPublicationVenuePosition
2015 GlycanAnalysis Plug-in: a database search tool for N-glycan structures using mass spectrometry
abstract
UNLABELLED: Tandem mass spectrometry (MS/MS or MS(n)) is a potent technique for characterizing N-glycan structures. GlycanAnalysis searches a glycan database to support the identification of glycan structures from MS/MS spectra. It also calculates diagnostic ions of glycan structures registered in a glycan database (GlycomeDB or KEGG GLYCAN) and searches for MS/MS spectra of N-glycans that match diagnostic ions to determine the structures. This program functions as a plug-in for Mass++, a freeware mass spectrum visualization and analysis program. AVAILABILITY AND IMPLEMENTATION: The executable files of Mass++ are available for free at http://www.first-ms3d.jp/english/. The GlycanAnalysis plug-in is included in the standard package of Mass++ for Windows. CONTACT: [email protected] or [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary material are available at Bioinformatics online.
Kentaro Morimoto, Takashi Nishikaze, Akiyasu C. Yoshizawa, Shigeki Kajihara, Ken Aoshima, Yoshiya Oda, Koichi Tanaka
Bioinform.3
2014 A simple peak detection and label-free quantitation algorithm for chromatography-mass spectrometry
abstract
BACKGROUND: Label-free quantitation of mass spectrometric data is one of the simplest and least expensive methods for differential expression profiling of proteins and metabolites. The need for high accuracy and performance computational label-free quantitation methods is still high in the biomarker and drug discovery research field. However, recent most advanced types of LC-MS generate huge amounts of analytical data with high scan speed, high accuracy and resolution, which is often impossible to interpret manually. Moreover, there are still issues to be improved for recent label-free methods, such as how to reduce false positive/negatives of the candidate peaks, how to expand scalability and how to enhance and automate data processing. AB3D (A simple label-free quantitation algorithm for Biomarker Discovery in Diagnostics and Drug discovery using LC-MS) has addressed these issues and has the capability to perform label-free quantitation using MS1 for proteomics study. RESULTS: We developed an algorithm called AB3D, a label free peak detection and quantitative algorithm using MS1 spectral data. To test our algorithm, practical applications of AB3D for LC-MS data sets were evaluated using 3 datasets. Comparisons were then carried out between widely used software tools such as MZmine 2, MSight, SuperHirn, OpenMS and our algorithm AB3D, using the same LC-MS datasets. All quantitative results were confirmed manually, and we found that AB3D could properly identify and quantify known peptides with fewer false positives and false negatives compared to four other existing software tools using either the standard peptide mixture or the real complex biological samples of Bartonella quintana (strain JK31). Moreover, AB3D showed the best reliability by comparing the variability between two technical replicates using a complex peptide mixture of HeLa and BSA samples. For performance, the AB3D algorithm is about 1.2 - 15 times faster than the four other existing software tools. CONCLUSIONS: AB3D is a simple and fast algorithm for label-free quantitation using MS1 mass spectrometry data for large scale LC-MS data analysis with higher true positive and reasonable false positive rates. Furthermore, AB3D demonstrated the best reproducibility and is about 1.2- 15 times faster than those of existing 4 software tools.
Ken Aoshima, Kentaro Takahashi, Masayuki Ikawa, Takayuki Kimura, Mitsuru Fukuda, Howell E. Parry, Yuichiro Fujita, Akiyasu C. Yoshizawa, Shin-ichi Utsunomiya, Shigeki Kajihara, Koichi Tanaka, Yoshiya Oda
BMC Bioinform.9