Thesis

PHD THESIS

Developed and implemented a new statistical convergence assessment and burn-in estimation technique based on Estimated Sample Size (ESS) for multiple Markov chain Monte Carlo parameters for phylogenetic tree.
Developed software “VMCMC”, a visualization and statistical tool for Markov chain Monte Carlo analysis of phylogenetic trees.
Designed and implemented a synteny based algorithm “GenFamClust” that quantifies gene synteny and combines it with protein similarity to infer gene homology.
Compared and validated the accuracy, cluster size, similarity and differences between GenFamClust and other homology inference algorithms using Chordatic, Fungi and simulated datasets.
Applied “GenFamClust” algorithm on a large dataset consisting of whole genome species and inferred gene families and synteny conservation. The results are available in the database “GenFam”.

Determining the relationship between age and the degree of a gene class network graph.
Extended the original work to determine the relationship for pathway class graph as well.
Worked on a new notion of gene class and pathway class graphs.

Lip Synchronization with Speech signal, a mixture of many different domains of Computer Science.
Reflects my command of diverse Computer Science fields such as Digital Signal Processing, Computer Graphics, Artificial Intelligence and Artificial Neural Networks.