GBOOST statistics

info info

Citations per year

info

Popular tool citations

chevron_left Epistasis detection chevron_right
info

Tool usage distribution map

Tool usage distribution map
info info

Associated diseases

Associated diseases
Want to access the full stats & trends on this tool?

GBOOST specifications

Information


Unique identifier OMICS_10104
Name GBOOST
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C++
Parallelization CUDA
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Ling Sing Yung

Publication for GBOOST

GBOOST citations

 (10)
library_books

Learning from biomedical linked data to suggest valid pharmacogenes

2017
J Biomed Semantics
PMCID: 5399403
PMID: 28427468
DOI: 10.1186/s13326-017-0125-1

[…] this may motivate the investigation of other subgraph mining methods that may be more informative on the weights of substructures in the classification. one may consider techniques such as gboost [] that progressively collects informative patterns, or gspan [] that enumerates frequent subgraph used as features for classification., rf algorithm performs correctly (f-m =0.73) […]

library_books

Efficient Strategy to Identify Gene Gene Interactions and Its Application to Type 2 Diabetes

2016
PMCID: 5287119
PMID: 28154506
DOI: 10.5808/GI.2016.14.4.160

[…] equal to the maximum likelihood estimators for a log-linear model, and it is used to select pairs of snps with a specified threshold. there is an updated method, graphical processing units boost (gboost), which is a boost method implemented for a graphical processing units framework for enabling parallel computing to achieve massive assignment in a fast manner []. gboost achieves a 40-fold […]

library_books

Bioinformatics Identification of Drug Resistance Associated Gene Pairs in Mycobacterium tuberculosis

2016
Int J Mol Sci
PMCID: 5037696
PMID: 27618895
DOI: 10.3390/ijms17091417

[…] did not take gene-gene interactions into account, and the emergence of transmissible drug resistance is connected with multiple genetic mutations. in this study we use the bioinformatics software gboost (the hong kong university, clear water bay, kowloon, hong kong, china) to calculate the interactions of single nucleotide polymorphism (snp) pairs and identify gene pairs associated with drug […]

library_books

Understanding Epistatic Interactions between Genes Targeted by Non coding Regulatory Elements in Complex Diseases

2014
PMCID: 4330252
PMID: 25705156
DOI: 10.5808/GI.2014.12.4.181

[…] focused on dm, ht, and cad (myocardial infarction and cad) and considered people who did not have any disease as the controls ()., we applied gpu-based boolean operation-based screening and testing (gboost) to analyze epistatic interaction effects from the genomewide snp data []. stage i: screening-in the screening stage, boost evaluated all pairwise interactions using the kirkwood superposition […]

library_books

Detecting Epistatic Interactions in Metagenome Wide Association Studies by metaBOOST

2014
Biomed Res Int
PMCID: 4131565
PMID: 25165702
DOI: 10.1155/2014/398147

[…] such modules []. strategies based on high performance computing were also designed and extended to be used with graphics processing units (gpu), yielding such highly efficient method as boost and gboost [, ]., with these understandings, we proposed in this paper the first study of epistatic interactions in mgwa studies. more specifically, we designed a method called metaboost to detect […]

library_books

Stability of Bivariate GWAS Biomarker Detection

2014
PLoS One
PMCID: 4005767
PMID: 24787002
DOI: 10.1371/journal.pone.0093319

[…] of 2-fold cross-validation of exhaustive bivariate analysis on seven wellcome–trust case–control consortium gwas datasets, comparing the traditional test for association, the high-performance gboost method and the recently proposed gss statistic (available at http://bioinformatics.research.nicta.com.au/software/gwis/). we use spearman's correlation to measure the similarity […]


Want to access the full list of citations?
GBOOST institution(s)
Laboratory for Bioinformatics and Computational Biology, Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
GBOOST funding source(s)
This work was partially supported with grants RPC10EG04 and PCF004.09/10 from the Hong Kong University of Science and Technology.

GBOOST reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review GBOOST