Sharif Digital Repository

Decades ago, scientists and researchers found out proteins are not function isolated and act in multi protein complexes as complex networks. So, they started to study about proteins and their interaction in the term of protein-protein interaction, therefore, the number of publication in this field grows rapidly. This large amount of published articles (in scientific journals or web pages or books) are unstructured and it is hard to classify them manually. Also, study and read all of these documents is difficult for one person. Hence, it’s better to find a way which could help scientists and researcher to study these unstructured or semi-structured information more easily. The best way to... 

Interactions among proteins and resulted networks of such interactions have a central role in biology. Aligning these networks leads effective information such as finding conserved complexes and evolutionary relationships. The inofrmation provided by global alignment of these networks is more meaningful in comparison to local alignment. In the problem of global alignment, time complexity is one of the most important challenges. Today, multi-core processors are used to solve many time-consuming bioinformatics problems. In this thesis, after reviewing pervious approaches on global alignment of biological networks, we present two novel algorithm for this problem. The first one is designed for... 

Predicting protein function accurately is an important issue in the post genomic era. To achieve this goal, several approaches have been proposed deduce the function of unclassified proteins through sequence similarity, co expression profiles, and other information. Among these methods, the Global Optimization Method is an interesting and powerful tool that assigns functions to unclassified proteins based on their positions in a physical interaction network. To boost both the accuracy and speed of global optimization method, a new prediction method, Accurate Global Optimization Method (AGOM), is presented in this thesis, which employs optimal repetition method enhanced with frequency of... 

In examining protein-protein interaction networks, we often encounter similar and repetitive schemes. Examination of these designs, which often appear in the form of motifs and similar patterns, reveals important information such as the type of protein linkage and many of the internal similarities between these networks. The ability to recognize these similarities plays an important role in identifying the function of genes, recognizing the relationships between diseases, and making drugs. We know that exact algorithms for examining subgraph isomorphism are np-hard and time-consuming and infeasible in large networks; Therefore, in practice, approximate and heuristic algorithms are used and... 

Nuclear magnetic resonance is a spectroscopic method which is used to investigate characteristics of molecules with hydrogen and carbon chains. In this thesis we used, NMR spectrum extracted from 19 types of amino acids for investigating on feature generation for protein sequences. We processed NMR spectra based on Hydrogen and Carbon atoms in structure of the amino acids and after preprocessing we extracted features for each amino acid from the spectra. After that, we tried to cluster the amino acids with Fuzzy Clustering Method (FCM) then we generated feature vectors by extracting special descriptor for amino acids in sequence of proteins. In addition to NMR, we used the features of... 

Datasets extracted from gene expression microarrays contain information about the phenotypic behavior of organisms. Turning this information into knowledge, i.e. finding associative genes with a given phenotype, is a daunting task. This is due to the high dimensionality of the data as the number of features on a gene expression microarray is usually very large. Moreover, a phenotype may change the expression pattern of a set of genes rather than changing each gene’s expression independently. To tackle the second problem, integrating other sources of information such as Protein-Protein Interaction (PPI) networks is required. In this thesis, the PPI network extracted from the String database... 

One of the most important targets in bio-informatics is the analysis of biological networks. These networks are modeled by graphs. Comparing networks with mapping is a useful tool for analyzing. The mapping between the nodes of a network that preserves some topological and functional structures, is called network alignment. Network alignment has various applications in different fields; such as pattern recognition, social networks, biological networks, and etc. The alignment of the protein-protein interaction network is one of the substantial problems. There are many static algorithms for the alignment of PPI networks. Because of the developments of computer science in recent years,... 

The highly developed biological data collection methods enable scientists to capture protein-protein interaction (PPI) in the human body, which could be analyzed as biological networks such as protein-protein interaction networks. These networks reveal essential information about the biological process in human cells and can be used to identify genes associated with cancers. Effectively identifying disease-related genes would contribute to improving the treatment and diagnosis of various diseases. Current methods for identifying disease-related genes mainly focus on the hypothesis of guilt-by-association and do not consider the global information in the PPI network. Besides, most methods pay... 

Colorectal cancer (CRC) is one of the most common cause of cancer death worldwide. Identification of pivot genes in colorectal cancer can play an important role as biomarkers in predicting and early diagnosis and reducing the number of deaths caused by this disease. In this study, the aim of which is to discover pivot genes in colorectal cancer, six microarray datasets selected from the GEO database including 277 tumor tissue samples and 325 normal colon tissue samples. After data processing, differentially expressed genes and CRC-related genes were screened and 285 shared genes between them were identified for subsequent analysis. Based on 285 shared genes, the protein-protein interaction... 

Alignment of genetic sequences is a fundamental part of genetic and bio-science. Alignment of DNA and protein sequences has an effective role in accelerating and simplifying problems in Bioinformatics like predicting protein interactions. Smith-Waterman algorithm is a precise algorithm for performing local alignment, suffering from computation complexity. There are some implementations on CPU, GPU, and FPGA platforms in order to reduce the run time of this algorithm. FPGA implementation is considered because of low power consumption and high degree of parallelism. With using pipeline and hardware redundancy techniques, various architectures have been proposed and implemented. In the best...