ReviewAdvances and applications in bioinformatics and chemistry : AABC2015
Parallel computing in genomic research: advances and applications.
Review in Advances and applications in bioinformatics and chemistry : AABC, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Tick genomics through a Nanopore: a low-cost approach for tick genomics.BMC genomics · 2025Article
- Genome assembly composition of the String "ACGT" array: a review of data structure accuracy and performance challenges.PeerJ. Computer science · 2023Article
- Laniakea@ReCaS: exploring the potential of customisable Galaxy on-demand instances as a cloud-based service.BMC bioinformatics · 2021Article
- Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation.JAMA network open · 2020Observational
- Comparative Genomic Analysis of Ochratoxin A Biosynthetic Cluster in Producing Fungi: New Evidence of a Cyclase Gene Involvement.Frontiers in microbiology · 2020Article
- A GPU-accelerated algorithm for biclustering analysis and detection of condition-dependent coexpression network modules.Scientific reports · 2017Article
- The Importance of Endophenotypes to Evaluate the Relationship between Genotype and External Phenotype.International journal of molecular sciences · 2017Review
- A Review of Recent Advancement in Integrating Omics Data with Literature Mining towards Biomedical Discoveries.International journal of genomics · 2017Review
- Gene, Environment and Methylation (GEM): a tool suite to efficiently navigate large scale epigenome wide association studies and integrate genotype and interaction between genotype and environment.BMC bioinformatics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Today's genomic experiments have to process the so-called "biological big data" that is now reaching the size of Terabytes and Petabytes. To process this huge amount of data, scientists may require weeks or months if they use their own workstations. Parallelism techniques and high-performance computing (HPC) environments can be applied for reducing the total processing time and to ease the management, treatment, and analyses of this data. However, running bioinformatics experiments in HPC environments such as clouds, grids, clusters, and graphics processing unit requires the expertise from scientists to integrate computational, biological, and mathematical techniques and technologies. Several solutions have already been proposed to allow scientists for processing their genomic experiments using HPC capabilities and parallelism techniques. This article brings a systematic review of literature that surveys the most recently published research involving genomics and parallel computing. Our objective is to gather the main characteristics, benefits, and challenges that can be considered by scientists when running their genomic experiments to benefit from parallelism techniques and HPC capabilities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.