Dias, L. A. | Search bioRxiv

bioRxiv2021

Parallel Implementation of Smith-Waterman Algorithm on FPGA

In bioinformatics, alignment is an essential technique for finding similarities between biological sequences. Usually, the alignment is performed with the Smith-Waterman (SW) algorithm, a well-known sequence alignment technique of high-level precision based on dynamic programming. However, given the massive data volume in biological databases and their continuous exponential increase, high-speed data processing is necessary. Therefore, this work proposes a parallel hardware design for the SW algorithm with a systolic array structure to accelerate the Forward and Backtracking steps. For this purpose, the architecture calculates and stores the paths in the Forward stage for pre-organizing the alignment, which reduces the complexity of the Backtracking stage. The backtracking starts from the maximum score position in the matrix and generates the optimal SW sequence alignment path. The architecture was validated on Field-Programmable Gate Array (FPGA), and synthesis analyses have shown that the proposed design reaches up to 79.5 Giga Cell Updates per Second (GCPUS).

bioinformatics↗

bioRxiv2017

Skin biomarkers for cystic fibrosis: a potential noninvasive approach for patient screening.

BackgroundCystic fibrosis is a disabling genetic disease with an increased prevalence in populations with European heritage. Currently, the most used technique for collection of cystic fibrosis samples and diagnosis is provided through uncomfortable tests, with uncertain results, mostly based on chloride concentration in sweat. Since cystic fibrosis mutation induces many metabolic changes in patients, exploring these alterations might be an alternative to visualize potential biomarkers that could be used as interesting tools for further diagnostic upgrade, prioritizing simplicity, low cost and quickness.\n\nMethodsThis contribution describes an accurate strategy to provide potential biomarkers related to cystic fibrosis, which may be understood as a potential tool for new diagnostic approaches and/or for monitoring disease evolution. Therefore, the present proposal consists of using skin imprints on silica plates as a way of sample collection, followed by direct-infusion high-resolution mass spectrometry and multivariate data analysis, intending to identify metabolic changes in skin composition of cystic fibrosis patients.\n\nResultsMetabolomics analysis allowed identifying chemical markers that can be traced back to cystic fibrosis in patients skin imprints, differently from control subjects. Seven chemical markers from several molecular classes were elected, represented by bile acids, a glutaric acid derivative, thyrotropin releasing hormone, an inflammatory mediator, a phosphatidic acid, and diacylglycerol isomers, all reflecting metabolic disturbances that occur due to of cystic fibrosis.\n\nConclusionThe comfortable method of sample collection combined with the identified set of biomarkers represent potential tools that open the range of possibilities to manage cystic fibrosis and follow the disease evolution. This exploratory approach points to new perspectives about cystic fibrosis management and maybe to further development of a new diagnostic assay based on them.

biochemistry↗