G-BLASTN statistics

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Citations per year

Number of citations per year for the bioinformatics software tool G-BLASTN
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Tool usage distribution map

This map represents all the scientific publications referring to G-BLASTN per scientific context
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Associated diseases

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Popular tool citations

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Protocols

G-BLASTN specifications

Information


Unique identifier OMICS_02263
Name G-BLASTN
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Parallelization CUDA
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Publication for G-BLASTN

G-BLASTN citations

 (15)
library_books

GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence

2018
Front Genet
PMCID: 5913331
PMID: 29719549
DOI: 10.3389/fgene.2018.00124

[…] ervation drops (). Hence, methods for the prediction of sRNA homologs (reviewed in reference ) are based on sequence comparison or the combination of sequence and structure information. Tools like, e.g., BLASTn () or profile hidden Markov models (; ) use the primary sequence for predictions. Probabilistic models (covariance models, CM) as implemented in Infernal () utilize the conserved sequence a […]

library_books

How to Name and Classify Your Phage: An Informal Guide

2017
Viruses
PMCID: 5408676
PMID: 28368359
DOI: 10.3390/v9040070

[…] to the same species differ from each other by less than 5% at the nucleotide level. This can be calculated by comparing your sequence to existing phage genomes. There are several tools to do this (e.g., BLASTN [], PASC [], Gegenees [], or EMBOSS Stretcher), but each comparison needs to be checked for genomic synteny. While it is common for larger dsDNA phages to differ in their genome organizatio […]

library_books

Alignment free \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{ 69pt} \begin{document} }{}$d_2^*$\end{document} oligonucleotide frequency dissimilarity measure improves prediction of hosts from metagenomically derived viral sequences

2016
Nucleic Acids Res
PMCID: 5224470
PMID: 27899557
DOI: 10.1093/nar/gkw1002

[…] that use sequence homology of viruses to host genomes, (ii) co-variation analysis of viruses and hosts, and 3) sequence composition methods. The first group of methods relies on homology searches (e.g. blastn, blastx, exact short word matches) between a query virus and host genomes. Viruses and hosts can share genes or short sequence elements due to horizontal gene transfer, the sharing of short […]

library_books

gmos: Rapid Detection of Genome Mosaicism over Short Evolutionary Distances

2016
PLoS One
PMCID: 5112998
PMID: 27846272
DOI: 10.1371/journal.pone.0166602

[…] ve modeling processes and the requirement of multiple sequence alignment as input. Although efficient general purpose tools for local pairwise alignments that handle complete genomes are available, e.g., BLASTN [] and MegaBLAST [], they are not directly applicable for detecting recombination, as they tend to maximize extension of the local alignment along every subject genome without considering a […]

library_books

GPU Acceleration of Sequence Homology Searches with Database Subsequence Clustering

2016
PLoS One
PMCID: 4970815
PMID: 27482905
DOI: 10.1371/journal.pone.0157338

[…] the GPU-based Smith-Waterman algorithms, and showed that when it is based on 1 GPU, it works 4- to 5-fold faster than does SSEARCH [], which is a CPU-based Smith-Waterman algorithm, with 4 CPU cores. G-BLASTN [] is one of the GPU-based BLAST with 1 GPU achieves 7.2-fold acceleration relative to the MEGABLAST mode of NCBI-BLAST [] with 4 CPU cores and 1.6-fold acceleration relative to the BLASTN mo […]

call_split

Comparison of Acceleration Techniques for Selected Low Level Bioinformatics Operations

2016
Front Genet
PMCID: 4748744
PMID: 26904094
DOI: 10.3389/fgene.2016.00005
call_split See protocol

[…] to multiple computers as well.Additionally, adapted versions of BLAST running on special purpose hardware (FPGA: TimeLogic ®Tera-BLAST ™; TimeLogic Division, ; GPU: GPU-BLAST; Vouzis and Sahinidis, , G-BLASTN; Zhao and Chu, ) exist. […]


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G-BLASTN institution(s)
Department of Computer Science, Hong Kong Baptist University, Hong Kong, China; Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong, China

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