Search for: population-genetics
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    Haploblock Detection Based on Reads and Population Structure

    , M.Sc. Thesis Sharif University of Technology Akbari, Elahe (Author) ; Motahari, Abolfazl (Supervisor)
    Human is diploid specie that inherits a set of chromosomes from their mother and a set from their father. The process of separating the nucleotide content of a set of extracted maternal and paternal chromosomes for an individual or a population is called phasing the genome of the individual or the population. The placement of any two variants relative to each other in diploid species is possible in two forms: cis (placement of both variants on one chromosome), and trans (placement of variants on different chromosomes). Each of these conditions leads to different phenotypes. Thus, understanding how variants are placed relative to each other is a crucial problem in human biology which is... 

    Inferring Relation between World and Iranian Populations from Microarray Data

    , M.Sc. Thesis Sharif University of Technology Saberi, Sasan (Author) ; Hossein Khalaj, Babak (Supervisor) ; Motahhari, Abolfazl (Supervisor)
    One of the branches of genetic studies is population genetics. Each population has its own characteristics due to its evolutionary history, cultural characteristics and geography, which distinguish it from other populations. Scientific and technological advances in recent decades have led to the production of new generation sequencing machines and the creation of large genetic data. These data contain important genetic information and answers to many questions about the origin of humans, the history of populations and their evolutionary process. More and better understanding of the human genome and the distance between populations can help to better understand biological mechanisms and deal... 

    Inferring the Demographic History of Iranian Populations from Whole Exome Sequencing Data

    , M.Sc. Thesis Sharif University of Technology Heidari, Jalal (Author) ; Motahari, Abolfazl (Supervisor) ; Khalaj, Babak (Supervisor)
    One of the cornerstones of population genetics is finding ancestral relations between people of a population. Mutations and recombinations are two major signals that can be exploited to infer the population ancestral relationships. Next Generation Sequencing (NGS) has paved the way for achieving this endeavor by providing massive data including single nucleotide polymorphisms, insertions, and deletions as well as structural variations between individuals. In this thesis, the goal is to infer the ancestral structure of a given gene from thousands of NGS datasets. We also attempt to decode times of important events including mutations and recombinations. To this end, we first split a gene into... 

    Three self-adaptive multi-objective evolutionary algorithms for a triple-objective project scheduling problem

    , Article Computers and Industrial Engineering ; Volume 87 , September , 2015 , Pages 4-15 ; 03608352 (ISSN) Shahsavar, A ; Najafi, A. A ; Niaki, S. T. A ; Sharif University of Technology
    Elsevier Ltd  2015
    Finding a Pareto-optimal frontier is widely favorable among researchers to model existing conflict objectives in an optimization problem. Project scheduling is a well-known problem in which investigating a combination of goals eventuate in a more real situation. Although there are many different types of objectives based on the situation on hand, three basic objectives are the most common in the literature of the project scheduling problem. These objectives are: (i) the minimization of the makespan, (ii) the minimization of the total cost associated with the resources, and (iii) the minimization of the variability in resources usage. In this paper, three genetic-based algorithms are proposed... 

    Statistical association mapping of population-structured genetic data

    , Article IEEE/ACM Transactions on Computational Biology and Bioinformatics ; Volume 16, Issue 2 , 2019 , Pages 636-649 ; 15455963 (ISSN) Najafi, A ; Janghorbani, S ; Motahari, A ; Fatemizadeh, E ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Association mapping of genetic diseases has attracted extensive research interest during the recent years. However, most of the methodologies introduced so far suffer from spurious inference of the associated sites due to population inhomogeneities. In this paper, we introduce a statistical framework to compensate for this shortcoming by equipping the current methodologies with a state-of-the-art clustering algorithm being widely used in population genetics applications. The proposed framework jointly infers the disease-associated factors and the hidden population structures. In this regard, a Markov Chain-Monte Carlo (MCMC) procedure has been employed to assess the posterior probability...