Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis of multiple hypotheses and scenarios takes too long on a single desktop computer. In this chapter, we discuss techniques for scaling computations through parallelization of calculations, after giving a quick overview of advanced programming techniques. Unfortunately, parallel programming is difficult and requires special software design. The alternative, especially attractive for legacy software, is to introduce poor man's parallelization by running whole programs in parallel as separate processes, using job schedulers. Such pipelines are often deployed on bioinformatics computer clusters. Recent advances in PC virtualization have made it po...
A poster discussing the use of parallel processing techniques (Hadoop, mapreduce, ect.) in processin...
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...
Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis...
Kary Ocaña,1 Daniel de Oliveira2 1National Laboratory of Scientific Computing, Petrópo...
Biological, clinical, and pharmacological research now often involves analyses of genomes, transcrip...
International audienceBiotechnology progresses lead to an exponential growth of genomic data. This m...
The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in...
This document surveys the computational strategies followed to parallelize the most used software in...
Abstract Background With the advent of high throughput genomics and high-resolution imaging techniqu...
Bioinformatics and computational biology are driven by growing volumes of data in biological systems...
Because of the ever-increasing application of next-generation sequencing (NGS) in research, and the ...
A revolution in personalized genomics will occur when scientists can sequence genomes of millions of...
The impending advent of population-scaled sequencing cohorts involving tens of millions of individua...
[[abstract]]Interest on biotechnology has increased dramatically. With the completion of sequencing ...
A poster discussing the use of parallel processing techniques (Hadoop, mapreduce, ect.) in processin...
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...
Genomic data analysis in evolutionary biology is becoming so computationally intensive that analysis...
Kary Ocaña,1 Daniel de Oliveira2 1National Laboratory of Scientific Computing, Petrópo...
Biological, clinical, and pharmacological research now often involves analyses of genomes, transcrip...
International audienceBiotechnology progresses lead to an exponential growth of genomic data. This m...
The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in...
This document surveys the computational strategies followed to parallelize the most used software in...
Abstract Background With the advent of high throughput genomics and high-resolution imaging techniqu...
Bioinformatics and computational biology are driven by growing volumes of data in biological systems...
Because of the ever-increasing application of next-generation sequencing (NGS) in research, and the ...
A revolution in personalized genomics will occur when scientists can sequence genomes of millions of...
The impending advent of population-scaled sequencing cohorts involving tens of millions of individua...
[[abstract]]Interest on biotechnology has increased dramatically. With the completion of sequencing ...
A poster discussing the use of parallel processing techniques (Hadoop, mapreduce, ect.) in processin...
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...