Efficient Algorithm for Network Motifs Discovery

, M.Sc. Thesis Sharif University of Technology Hazrati, Sattar (Author) ; Izadi, Mohammad (Supervisor)

Abstract

Network Motifs are subgraphs that appear more frequently in real networks than randomize networks. Frequent replication of a subgraph could imply evolution, network performance or some other particular reasons. From algorithmic perspective, network motif discovery in a graph is a difficult problem. Since, at least it includes the whole graph isomorphism. Hence, for solving this problem in practice, we need computable graphs. The existing algorithms so far, have high running times and memory usages. In this thesis, we present a new algorithm called CGQ. Within this algorithm, we use both QuateXelero and G-Trie algorithms which respectively have better performance in census of real networks...

Motif Finding in DNA Sequences by Using Machine Learning Approach

, M.Sc. Thesis Sharif University of Technology Haghir Ebrahimabadi, Mohammad (Author) ; Fatemizadeh, Emadeddin (Supervisor)

Abstract

Motifs are patterns which can be extracted from specific subsequences of promoter region of some related genes. Transcription factor proteins bind to these subsequences and play a significant role in gene expression regulation.
Motif discovery is a challenging problem in molecular biology and has been attracting researcher’s attention for years. Different kind of data and computational methods have been used to unravel this problem, but there is still room for improvement. In this study, our goal was to develop a method with the ability to identify all the TFBS signals, including known and unknown, inside the input set of sequences. We developed a clustering method specialized as part...

Urban Mobility Pattern Estimation Using O-D Surveys and Mobile Phone Data: A Case Study of Shiraz City

, M.Sc. Thesis Sharif University of Technology Nouri, Meysam (Author) ; Shafahi, Yousef (Supervisor)

Abstract

Activity bases models of travel demand considers travel demand as a derived demand to fulfill activities. Development of these models cause better understanding of the mechanism of travel through Integrity, interdependencies, higher temporal and spatial aggregation, and behavioral basis. Although these models requires of spatial and temporal data with high resolution of huge number of peoples. Gathering this data through surveys require great labor and time. Mobile phone data of cellular network have high spatial-temporal resolution used for billing purposes and can be used as a supplementary source of data to develop activity based models. This research uses mobility patterns called motifs...