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The two most common data-structures for genome indexing, FM-indices and hash-tables, exhibit a fundamental trade-off between memory footprint and performance. We present Ranger, a new indexing technique for nucleotide sequences that is both…
With the advance in genome sequencing technology, the lengths of deoxyribonucleic acid (DNA) sequencing results are rapidly increasing at lower prices than ever. However, the longer lengths come at the cost of a heavy computational burden…
Genomics is the critical key to enabling precision medicine, ensuring global food security and enforcing wildlife conservation. The massive genomic data produced by various genome sequencing technologies presents a significant challenge for…
Addressing the growing demands of artificial intelligence (AI) and data analytics requires new computing approaches. In this paper, we propose a reconfigurable hardware accelerator designed specifically for AI and data-intensive…
Genome sequence analysis is a powerful tool in medical and scientific research. Considering the inevitable sequencing errors and genetic variations, approximate string matching (ASM) has been adopted in practice for genome sequencing.…
High-throughput sequencing (HTS) technologies have revolutionized the field of genomics, enabling rapid and cost-effective genome analysis for various applications. However, the increasing volume of genomic data generated by HTS…
Genome-to-genome comparisons require designating anchor points, which are given by Maximum Exact Matches (MEMs) between their sequences. For large genomes this is a challenging problem and the performance of existing solutions, even in…
Aligning millions of short DNA or RNA reads, of 75 to 250 base pairs each, to a reference genome is a significant computation problem in bioinformatics. We present a flexible and fast FPGA-based short read alignment tool. Our aligner makes…
Motivation: Despite significant advances in Third-Generation Sequencing (TGS) technologies, Next-Generation Sequencing (NGS) technologies remain dominant in the current sequencing market. This is due to the lower error rates and richer…
Computational complexity is a key limitation of genomic analyses. Thus, over the last 30 years, researchers have proposed numerous fast heuristic methods that provide computational relief. Comparing genomic sequences is one of the most…
Genetic Programming (GP) is known to suffer from the burden of being computationally expensive by design. While, over the years, many techniques have been developed to mitigate this issue, data vectorization, in particular, is arguably…
Neural architectures and hardware accelerators have been two driving forces for the progress in deep learning. Previous works typically attempt to optimize hardware given a fixed model architecture or model architecture given fixed…
Huge amount of data in the form of strings are being handled in bio-computing applications and searching algorithms are quite frequently used in them. Many methods utilizing on both software and hardware are being proposed to accelerate…
Regular expression matching is essential for many applications, such as finding patterns in text, exploring substrings in large DNA sequences, or lexical analysis. However, sequential regular expression matching may be time-prohibitive for…
Genetic Programming (GP), an evolutionary learning technique, has multiple applications in machine learning such as curve fitting, data modelling, feature selection, classification etc. GP has several inherent parallel steps, making it an…
Genomics is changing our understanding of humans, evolution, diseases, and medicines to name but a few. As sequencing technology is developed collecting DNA sequences takes less time thereby generating more genetic data every day. Today the…
In view of the performance limitations of fully-decoupled designs for neural architectures and accelerators, hardware-software co-design has been emerging to fully reap the benefits of flexible design spaces and optimize neural network…
DNA read mapping is a ubiquitous task in bioinformatics, and many tools have been developed to solve the read mapping problem. However, there are two trends that are changing the landscape of readmapping: First, new sequencing technologies…
Sequence alignment is a fundamental process in computational biology which identifies regions of similarity in biological sequences. With the exponential growth in the volume of data in bioinformatics databases, the time, processing power,…
Motivation: Next generation methods of DNA sequencing produce relatively high rate of reading errors, which interfere with de novo genome assembly of newly sequenced organisms and particularly affect the quality of SNP detection important…