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Genomic data analysis

I worked on a project for studing the drug resistant strains of Plasmodium falciparum (Malaria parasite). My role was to assemble and analyze different types of next generation sequencing data. Also, I have been a member of a team; consist of biologists and computer scientists, working on some crop genomes like Barley and Cowpea. The project includes sequencing, assembly, comparison, gene finding and all the necessary steps for a comprehensive study of these organisms. In addition, I got involved in a microarray analysis study for finding genes responsible for wound healing in mice.

Time series analysis

This is an initial step of a comprehensive study aiming to automate the process of discovering important biological features from a set of genomic tracks. Our goal is to explore multiple time series representing various genomic measures to discover different types of correlations like causality among them. We then want to find important patterns appear in a subset of the TSs and predict the location of interesting features along the target genome by combing the correlations and patterns. Also, I had the chance of involving in a project for analysing mice vocalization (in form of time series). The goal was to detect mice with brain strik based on the ovserved patterns in their voice.

Assembly algorithms

Assembly algorithms for next generation sequencing data will be the main part of my thesis. We studied the effect of depth of coverage on the quality of NGS assemblies. Based on the findings, we proposed a method to improve the quality of assembly of ultra deep sequeces. We are working on an algorithm to merge several draft assemblies and create a combined high quality assembly.