Abstract
Biomarker plays an important role in early disease diagnosis including cancer. The World Health Organization defines a biomarker as any structure or process in the body that is measurable and affects the prognosis or outcome of the disease. Today, biomarkers can be identified using bioinformatics tools. The detection of biomarkers in the field of bioinformatics is considered more as a problem of feature selection. Many feature selection algorithms have been used for biomarker discovery however these algorithms do not have enough accuracy or have computational complexity. For this reason, the researchers discard the high accuracy algorithms because they are time consuming. We redesigned an efficient algorithm based on parallel algorithms. We used the Cancer Genome Atlas (TCGA) including breast cancer patients. The proposed algorithm has the same accuracy and increases the speed of algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
