A Genome Wide Association Study (GWAS) is an important bioinformatics method to associate variants with traits, identify causes of diseases and increase plant and crop production. There are several optimizations for improving GWAS performance, including running applications in parallel. However, it can be difficult for researchers to utilize different data types and workflows using existing approaches. A potential solution for this problem is to model GWAS algorithms as a set of modular tasks. In this thesis, a modular pipeline architecture for GWAS applications is proposed that can leverage a parallel computing environment as well as store and retrieve data using a shared data cache. To show that the proposed architecture increases perform...
Abstract — In recent years our society has witnessed an unprecedented growth in computing power avai...
Abstract — Nowadays, multicore processor and GPUs have entered the mainstream of microprocessor dev...
Generalized linear mixed-effects models in the context of genome-wide association studies (GWAS) rep...
A Genome Wide Association Study (GWAS) is an important bioinformatics method to associate variants w...
A poster discussing the use of parallel processing techniques (Hadoop, mapreduce, ect.) in processin...
Kary Ocaña,1 Daniel de Oliveira2 1National Laboratory of Scientific Computing, Petrópo...
International audienceThis paper presents a joint effort between a group of computer scientists and ...
Genome wide association studies (GWAS) have proven their value, having found hundreds of thousands o...
Abstract Background In recent years, the demand for computational power in computational biology has...
The ever increasing pace of advancements in sequencing technologies has enabled rapid DNA/genome seq...
Generalizable approaches, models, and frameworks for irregular application scalability is an old yet...
Genomic datasets are growing dramatically as the cost of sequencing continues to decline and small s...
Motivation: High performance computing (HPC) clusters play a pivotal role in large-scale bioinformat...
The Genomic Data Commons (GDC) is a data platform for managing, processing, analyzing, and sharing c...
A revolution in personalized genomics will occur when scientists can sequence genomes of millions of...
Abstract — In recent years our society has witnessed an unprecedented growth in computing power avai...
Abstract — Nowadays, multicore processor and GPUs have entered the mainstream of microprocessor dev...
Generalized linear mixed-effects models in the context of genome-wide association studies (GWAS) rep...
A Genome Wide Association Study (GWAS) is an important bioinformatics method to associate variants w...
A poster discussing the use of parallel processing techniques (Hadoop, mapreduce, ect.) in processin...
Kary Ocaña,1 Daniel de Oliveira2 1National Laboratory of Scientific Computing, Petrópo...
International audienceThis paper presents a joint effort between a group of computer scientists and ...
Genome wide association studies (GWAS) have proven their value, having found hundreds of thousands o...
Abstract Background In recent years, the demand for computational power in computational biology has...
The ever increasing pace of advancements in sequencing technologies has enabled rapid DNA/genome seq...
Generalizable approaches, models, and frameworks for irregular application scalability is an old yet...
Genomic datasets are growing dramatically as the cost of sequencing continues to decline and small s...
Motivation: High performance computing (HPC) clusters play a pivotal role in large-scale bioinformat...
The Genomic Data Commons (GDC) is a data platform for managing, processing, analyzing, and sharing c...
A revolution in personalized genomics will occur when scientists can sequence genomes of millions of...
Abstract — In recent years our society has witnessed an unprecedented growth in computing power avai...
Abstract — Nowadays, multicore processor and GPUs have entered the mainstream of microprocessor dev...
Generalized linear mixed-effects models in the context of genome-wide association studies (GWAS) rep...