Related papers: GenPairX: A Hardware-Algorithm Co-Designed Acceler…
The computational problem of inferring the full haplotype of a cell starting from read sequencing data is known as haplotype assembly, and consists in assigning all heterozygous Single Nucleotide Polymorphisms (SNPs) to exactly one of the…
Communication and networking research introduces new protocols and standards with an increasing number of researchers relying on real experiments rather than simulations to evaluate the performance of their new protocols. A number of…
Motivation: The ability to generate massive amounts of sequencing data continues to overwhelm the processing capability of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design and…
Short-read DNA sequencing instruments can yield over 1e+12 bases per run, typically composed of reads 150 bases long. Despite this high throughput, de novo assembly algorithms have difficulty reconstructing contiguous genome sequences using…
Biological machine learning is often bottlenecked by a lack of scaled data. One promising route to relieving data bottlenecks is through high throughput screens, which can experimentally test the activity of $10^6-10^{12}$ protein sequences…
Huge numbers of short reads are being generated for mapping back to the genome to discover the frequency of transcripts, miRNAs, DNAase hypersensitive sites, FAIRE regions, nucleosome occupancy, etc. Since these reads are typically short…
Regular expression is important for many natural language processing tasks especially when used to deal with unstructured and semi-structured data. This work focuses on automatically generating regular expressions and proposes a novel…
High-throughput DNA sequencers are becoming indispensable in our understanding of diseases at molecular level, in marker-assisted selection in agriculture and in microbial genetics research. These sequencing instruments produce enormous…
Genomic sequence alignment is an important research topic in bioinformatics and continues to attract significant efforts. As genomic data grow exponentially, however, most of alignment methods face challenges due to their huge computational…
Data augmentation is widely used to enhance generalization in visual classification tasks. However, traditional methods struggle when source and target domains differ, as in domain adaptation, due to their inability to address domain gaps.…
With the recent move towards sequencing of accurate long reads, finding solutions that support efficient analysis of these reads becomes more necessary. The long execution time required for sequence alignment of long reads negatively…
As high-throughput sequencers become standard equipment outside of sequencing centers, there is an increasing need for efficient methods for pre-processing and primary analysis. While a vast literature proposes methods for HTS data…
Genome sequences contain hundreds of millions of DNA base pairs. Finding the degree of similarity between two genomes requires executing a compute-intensive dynamic programming algorithm, such as Smith-Waterman. Traditional von Neumann…
Current computational methods for exon-intron structure prediction from a cluster of transcript (EST, mRNA) data do not exhibit the time and space efficiency necessary to process large clusters of over than 20,000 ESTs and genes longer than…
Adequate read filtering is critical when processing high-throughput data in marker-gene-based studies. Sequencing errors can cause the mis-clustering of otherwise similar reads, artificially increasing the number of retrieved Operational…
This paper examines the use of a hierarchical coevolutionary genetic algorithm under different partnering strategies. Cascading clusters of sub-populations are built from the bottom up, with higher-level sub-populations optimising larger…
Motivation: Next-generation sequencing tools have enabled producing of huge amount of genomic information at low cost. Unfortunately, presence of sequencing errors in such data affects quality of downstream analyzes. Accuracy of them can be…
Generic matrix multiplication (GEMM) and one-dimensional convolution/cross-correlation (CONV) kernels often constitute the bulk of the compute- and memory-intensive processing within image/audio recognition and matching systems. We propose…
Providing architectural support is crucial for newly arising applications to achieve high performance and high system efficiency. Currently there is a trend in designing accelerators for special applications, while arguably a debate is…
Genomics is the foundation of precision medicine, global food security and virus surveillance. Exact-match is one of the most essential operations widely used in almost every step of genomics such as alignment, assembly, annotation, and…