DocumentCode :
3714659
Title :
Developing automated pipeline for identifying disease-related genomic variants
Author :
Chad Hayden; Dan Li;Kenji Yoshigoe;Mary Yang
fYear :
2015
Firstpage :
1789
Lastpage :
1789
Abstract :
Summary form only given. Advances in Next-Generation Sequencing technologies have opened unprecedented opportunities for identifying disease-associated genetic variations using whole genome / whole exome sequencing data. Precisely detecting all disease-related variants using computational tools is important but challenging. Presently such software tools have not been well developed. It is difficult to comprehensively and exactly capture genomic variations for systematic understanding of complex disease initialization and progression, such as cancer.
Keywords :
"Genomics","Bioinformatics"
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/BIBM.2015.7359964
Filename :
7359964
Link To Document :
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