Optimization of hadoop cluster for analyzing large-scale sequence data in bioinformatics
Annales mathematicae et informaticae, Tome 50 (2019), pp. 187-202.

Voir la notice de l'article provenant de la source Annales Mathematica et Informaticae website

@article{AMI_2019_50_a14,
     author = {\'Ad\'am T\'oth and Ramin Karimi},
     title = {Optimization of hadoop cluster for analyzing large-scale sequence data in bioinformatics},
     journal = {Annales mathematicae et informaticae},
     pages = {187--202},
     publisher = {mathdoc},
     volume = {50},
     year = {2019},
     doi = {10.33039/ami.2019.01.002},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.33039/ami.2019.01.002/}
}
TY  - JOUR
AU  - Ádám Tóth
AU  - Ramin Karimi
TI  - Optimization of hadoop cluster for analyzing large-scale sequence data in bioinformatics
JO  - Annales mathematicae et informaticae
PY  - 2019
SP  - 187
EP  - 202
VL  - 50
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/articles/10.33039/ami.2019.01.002/
DO  - 10.33039/ami.2019.01.002
LA  - en
ID  - AMI_2019_50_a14
ER  - 
%0 Journal Article
%A Ádám Tóth
%A Ramin Karimi
%T Optimization of hadoop cluster for analyzing large-scale sequence data in bioinformatics
%J Annales mathematicae et informaticae
%D 2019
%P 187-202
%V 50
%I mathdoc
%U http://geodesic.mathdoc.fr/articles/10.33039/ami.2019.01.002/
%R 10.33039/ami.2019.01.002
%G en
%F AMI_2019_50_a14
Ádám Tóth; Ramin Karimi. Optimization of hadoop cluster for analyzing large-scale sequence data in bioinformatics. Annales mathematicae et informaticae, Tome 50 (2019), pp. 187-202. doi : 10.33039/ami.2019.01.002. http://geodesic.mathdoc.fr/articles/10.33039/ami.2019.01.002/

Cité par Sources :