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MSc Thesis Defense Announcement of Musab Naik:"Finding Binding Sites in ChIP-Seq Data via a Linear-time Multi-level Thresholding Algorithm "

Tuesday, September 8, 2020 - 10:30 to 12:00

SCHOOL OF COMPUTER SCIENCE 

The School of Computer Science is pleased to present… 

MSc Thesis Defense by: Musab Naik 

 
Date: Tuesday September 8,2020 
 
Time:  10:30 am – 12:00pm 
 
 

Abstract:  

Chromatin immunoprecipitation (ChIP–Seq) has emerged as a superior alternative to microarray technology as it provides higher resolution, less noise, greater coverage and wider dynamic range.  While ChIP-Seq enables probing of DNA-protein interaction over the entire genome, it requires the use of sophisticated tools to recognize hidden patterns and extract meaningful data.  Over the years, various attempts have resulted in several algorithms making use of different heuristics to accurately determine individual peaks corresponding to unique DNA-protein binding sites.  However, finding all the binding sites with high accuracy in a reasonable time is still a challenge.  
 
In this work, we propose the use of Multi-level thresholding algorithm, which we call LinMLTBS, used to identify the enriched regions on ChIP-Seq data.  Although various suboptimal heuristics have been proposed for multi-level thresholding, we emphasize on the use of an algorithm capable of obtaining an optimal solution, while maintaining linear-time complexity.  Testing various algorithm on various ENCODE project datasets shows that our approach attains higher accuracy relative to previously proposed peak finders while retaining a reasonable processing speed.  
 
Keywords: ChIP-Seq; protein binding sites; multi-level thresholding; between-class criterion; cluster validity indices; peak calling 
 

Thesis Committee:  

 
Internal Reader: Dr. Ahmad Biniaz             
 
External Reader: Dr. Huapeng Wu              
 
Advisor: Dr. Luis Rueda 
 
Chair: Dr. Xiaobu Yuan

MSc Thesis Defense Announcement Vector Institute of Artificial Intelligence approved AI seminar topic

 

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