Name
Abstract | ||
|---|---|---|
Circular RNAs (CircRNAs) are a widespread form of Non-Coding RNAs (ncRNAs). Although circular RNAs have been known for a long time, it is only recently that their therapeutic implications are being investigated. Research has shown that they are suitable candidates to be genetic biomarkers for different types of cancer since they are implied in Carcinogenesis. However, their identification involves a computationally intensive and very long process. This represents a serious obstacle to their ability to provide a fast and accurate life-saving diagnosis. Here we present Circular RNA FPGA Aligner (circFa), a hardware implementation of an alignment algorithm designed for the circular RNAs identification protocol. Our solution aims to reduce diagnosis time and produces a pharmacological therapy tailored to the specific patient using his genetic information. CircFA implements the same scalable version of the Smith-Waterman (SW) algorithm with affine gaps employed by Bowtie2, a state of the art tool for sequence alignment, on Field Programmable Gate Array (FPGA). Our design shows a speedup over the software version of SW of 8.8x, and a speedup of 1.95x over a parallelized multicore version of the same software. Our architecture also shows a significant increase in power efficiency with an increase of 80.96x and 17.96x with respect to the single core and multicore software respectively. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/BHI.2019.8834539 | 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI) |
Keywords | Field | DocType |
circular RNA FPGA aligner,noncoding RNAs,carcinogenesis,pharmacological therapy,Bowtie2,field programmable gate array,parallelized multicore version,cancer,genetic biomarkers,therapeutic implications,circFA,Smith-Waterman algorithm,genetic information | Affine transformation,Single-core,Computer science,Parallel computing,Field-programmable gate array,Circular RNA,Software,Multi-core processor,Speedup,Scalability | Conference |
ISSN | ISBN | Citations |
2641-3590 | 978-1-7281-0849-0 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alberto Zeni | 1 | 2 | 0.79 |
| Francesco Peverelli | 2 | 1 | 1.71 |
| Enrico Cabri | 3 | 0 | 0.34 |
| Lorenzo Di Tucci | 4 | 18 | 3.48 |
| Luca Cerina | 5 | 2 | 4.52 |
| Marco D. Santambrogio | 6 | 771 | 91.15 |