Motohiro Akikawa
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Motohiro Akikawa has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
Jhin-Huang Chen
1 shared publication- Kazuki Izawa
Division of Genome Safety Science, National Institute of Health Sciences (NIHS), Kawasaki City, Japan
1 shared publication - Kazuki Takabatake
Toshiba Digital Solutions Corporation, Kawasaki-shi 212-8585, Kanagawa, Japan
1 shared publication - Keisuke Yanagisawa
Department of Computer Science, School of Computing, Institute of Science Tokyo, W8-76, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan
1 shared publication - Masahito Ohue
Department of Computer Science School of Computing Institute of Science Tokyo Kanagawa Japan
1 shared publication Yusuke Ariyoshi
1 shared publication
Latest Publications
- Open Access
Improved Large-Scale Homology Search by Two-Step Seed Search Using Multiple Reduced Amino Acid Alphabets
Metagenomic analysis, a technique used to comprehensively analyze microorganisms present in the environment, requires performing high-precision homology searches on large amounts of sequencing data, the size of which has increased dramatically with the development of next-generation sequencing. NCBI BLAST is the most widely used software for performing homology searches, but its speed is insufficient for the throughput of current DNA sequencers. In this paper, we propose a new, high-performance homology search algorithm that employs a two-step seed search strategy using multiple reduced amino acid alphabets to identify highly similar subsequences. Additionally, we evaluated the validity of the proposed method against several existing tools. Our method was faster than any other existing program for ≤120,000 queries, while DIAMOND, an existing tool, was the fastest method for >120,000 queries.
Open AccessImproved Large-Scale Homology Search by Two-Step Seed Search Using Multiple Reduced Amino Acid Alphabets
Metagenomic analysis, a technique used to comprehensively analyze microorganisms present in the environment, requires performing high-precision homology searches on large amounts of sequencing data, the size of which has increased dramatically with the development of next-generation sequencing. NCBI BLAST is the most widely used software for performing homology searches, but its speed is insufficient for the throughput of current DNA sequencers. In this paper, we propose a new, high-performance homology search algorithm that employs a two-step seed search strategy using multiple reduced amino acid alphabets to identify highly similar subsequences. Additionally, we evaluated the validity of the proposed method against several existing tools. Our method was faster than any other existing program for ≤120,000 queries, while DIAMOND, an existing tool, was the fastest method for >120,000 queries.