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Time-Series Analysis and Applicaitons in Cancer Research

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  • Fri, 09/22/2017 - 11:00am - 12:00pm




Computer Science Colloquium Series
Abedalrhman Alkhateeb

Date:  Friday, September 22nd, 2017
Time: 11:00 am
Location: Chrysler Hall North, G100

Abstract: Time-Series analysis is a very important application of machine learning. Time series are present in many aspects of data analysis in which cancer genomics is not an exception. Time series applications are mainly used for monitoring gene expression throughout time, though they can model various cancer problems for further analysis. Analyzing cancer development as a function over time provides a better understanding of the disease for diagnosis, treatment and prognosis.  However, continuous values of a function over time may not be available. Therefore, different measurements of a function at different time points can be used to interpolate the function, such as regression methods. 

In this talk, we discuss two different cancer problems, namely prostate cancer progression and breast cancer survivability. These two problems are modeled using time series and hierarchically clustered to detect outlier profiles of genes or transcripts. These outlier profiles trend differently than the majority of the genes or transcripts. Relevant outliers are then validated and considered as potential biomarkers for both problems. Studying those biomarkers can also yield additional insight into the molecular mechanisms of progression or survivability of the disease which may help in diagnosis, prognosis and treatment of the disease.

Bio: Abed Alkhateeb is a Ph.D. student in the Pattern Recognition and Bioinformatics lab in the School of Computer Science, working under the supervision of Dr. Luis Rueda. He completed his Bachelor in the department of Computer Science at University of Jordan, and his M.Sc. in computer science in the School of Computer Science at the University of Windsor. He has had positions in Blackberry as Business Systems Developer, and before doing his PhD in Analyst/Programmer in Emara-tech and UAE University in United Arab Emirates. Abed’s research interests include data mining, machine learning, bioinformatics, and RNA sequencing and cancer progression. He has many publications and presentations in most top-ranked conferences in bioinformatics and in reputable journals. Abed has recently obtained the Ontario Government Scholarship and the Faculty of Science Going Above and Beyond award, among other awards.

 



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