@inproceedings{b3aeaaf98f734edf939267828d22c876,
title = "Parallel implementation of motif-based clustering for HT-SELEX dataset",
abstract = "A clustering method for high-throughput sequencing with SELEX pools (HT-SELEX) is crucial for selecting different types of aptamer candidates. The fast and accurate clustering method is indispensable for an enormous sequence data produced by HT-SELSEX. We have already developed a fast motif-based clustering (FMBC) method for HT-SELEX data implemented by R language. FMBC exhibited high accuracy of sequence clustering compared with conventional methods, while the processing time of FMBC is longer than AptaCluster. This paper proposes the parallel implementation of FMBC using Python with multi-threading to improve the performance of FMBC. Experimental evaluation using the NCBI SRA data of SRR3279661 from BioProject PRJNA315881 demonstrated that parallel FMBC exhibited higher accuracy of clustering and shorter processing time than conventional methods.",
keywords = "Aptamer, Clustering, HT-SELEX, Parallel implementation, SELEX",
author = "Takayoshi Ono and Shintaro Kato and Koichi Ito and Hirotaka Minagawa and Katsunori Horii and Ikuo Shiratori and Iwao Waga and Takafumi Aoki",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 19th International Conference on Bioinformatics and Bioengineering, BIBE 2019 ; Conference date: 28-10-2019 Through 30-10-2019",
year = "2019",
month = oct,
doi = "10.1109/BIBE.2019.00018",
language = "English",
series = "Proceedings - 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering, BIBE 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "50--55",
booktitle = "Proceedings - 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering, BIBE 2019",
address = "United States",
}