S
Shintaro Akiyama
Publications - 7
Citations - 173
Shintaro Akiyama is an academic researcher. The author has contributed to research in topics: DNA sequencing & Sanger sequencing. The author has an hindex of 5, co-authored 7 publications receiving 96 citations.
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Journal ArticleDOI
A Practical Method to Detect SNVs and Indels From Whole Genome and Exome Sequencing Data
Daichi Shigemizu,Akihiro Fujimoto,Shintaro Akiyama,Tetsuo Abe,Kaoru Nakano,Keith A. Boroevich,Yujiro Yamamoto,Mayuko Furuta,Michiaki Kubo,Hidewaki Nakagawa,Tatsuhiko Tsunoda +10 more
TL;DR: A probabilistic multinomial method for the detection of single nucleotide variants (SNVs) as well as short insertions and deletions (indels) in whole genome sequencing and whole exome sequencing data for single sample calling is developed.
Journal ArticleDOI
Identification of potential blood biomarkers for early diagnosis of Alzheimer’s disease through RNA sequencing analysis
Daichi Shigemizu,Taiki Mori,Shintaro Akiyama,Sayuri Higaki,Hiroshi Watanabe,Takashi Sakurai,Shumpei Niida,Kouichi Ozaki +7 more
TL;DR: The findings indicate the discovery of potential biomarkers for early diagnosis of AD, and their further improvement may lead to future practical clinical use.
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Prognosis prediction model for conversion from mild cognitive impairment to Alzheimer’s disease created by integrative analysis of multi-omics data
Daichi Shigemizu,Shintaro Akiyama,Sayuri Higaki,Taiki Sugimoto,Takashi Sakurai,Keith A. Boroevich,Alok Sharma,Alok Sharma,Tatsuhiko Tsunoda,Tatsuhiko Tsunoda,Takahiro Ochiya,Shumpei Niida,Kouichi Ozaki +12 more
TL;DR: Accurate prediction of MCI-to-AD conversion would enable earlier intervention for MCI patients at high risk, potentially reducing conversion to AD.
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A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data.
Daichi Shigemizu,Shintaro Akiyama,Yuya Asanomi,Keith A. Boroevich,Alok Sharma,Tatsuhiko Tsunoda,Takashi Sakurai,Kouichi Ozaki,Takahiro Ochiya,Shumpei Niida +9 more
TL;DR: The proposed prediction model provides an effective tool for DLB classification and predicted candidate target genes from the miRNAs, including 6 functional genes included in the DHA signaling pathway associated with DLB pathology.
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IMSindel: An accurate intermediate-size indel detection tool incorporating de novo assembly and gapped global-local alignment with split read analysis
Daichi Shigemizu,Fuyuki Miya,Shintaro Akiyama,Shujiro Okuda,Keith A. Boroevich,Akihiro Fujimoto,Hidewaki Nakagawa,Kouichi Ozaki,Shumpei Niida,Yonehiro Kanemura,Nobuhiko Okamoto,Shinji Saitoh,Mitsuhiro Kato,Mami Yamasaki,Tatsuo Matsunaga,Hideki Mutai,Kenjiro Kosaki,Tatsuhiko Tsunoda +17 more
TL;DR: A new method is developed that predicts intermediate-size indels using BWA soft-clipped fragments (unmatched fragments in partially mapped reads) and unmapped reads and it is believed that this methodology will contribute to the discovery of intermediate- size indels associated with human disease.