Sharif Digital Repository

At the molecular level, proteins control almost all the biochemical reactions in the cells. In order for proteins to function, they must be able to fold into their unique 3D structure. Deformation of protein structure due to some environmental phenomena such as pH, high temperature, and stress may cause unfolding of proteins and finally result in formation of protein fibrils called "amyloid". Amyloid has been found in a number of human diseases such as Alzheimer, type II diabetes, and Parkinson. Recently pyridazine has been under spotlight due to its unique chemical properties such as high dipole moment and higher solubility in biological solvents. In this study, we aim at using a... 

The goal of crowd labeling is to find labels of given samples using humans’ mind power.Since crowds are not necessarily experts, their provided labels are rather noisy and erroneous.This challenge is usually resolved by collecting multiple labels for each sample and aggregating them to estimate its true label. Although this mechanism leads to high-quality labels, it is not actually cost effective. Adaptive methods consider that only some samples are challenging and require more labels. They spend the budget more wisely, and iteratively collect the required labels. Using adaptive methods approach, we utilize statistical latent models to model and analyze the collected labels and low-rank... 

A number of questions from a variety of areas of mathematics lead one to the problem of analyzing the topology of a simplicial complex. However, there are few general techniques available to aid us in this study. On the other hand, some very general theories have been developed for the study of smooth manifolds. One of the most powerful, and useful, of these theories is Morse Theory. We present a combinatorial adaptation of Morse Theory, which we call discrete Morse theory that may be applied to any simplicial complex (or more general cell complex). Our goal is to present an overview of the subject of discrete Morse Theory that is sufficient both to understand the major applications of the... 

Online social networks have become very popular in recent years. Most people usually get involved in multiple social networks to enjoy new contents and different social interactions. Many new social networks try to attract users of other existing networks to increase the number of their users. Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new internetwork link, known as anchor link, is formed between the source and target networks. In this thesis, we concentrate on predicting the formation of such anchor links between heterogeneous social networks. Unlike conventional link prediction problems in which the... 

Social networks play an important role in the spread of information, news and users’decisions. An important type of these networks are location-based networks where users can post the time and location of their checks in different places. Check-ins of a user may incentivize her friends to visit the same location in the near future.This phenomena is called diffusion process. Previous works often assume that the generation of an event just increases the probability of subsequent events in a near future. Even though the assumption is quite valid in the social networks like Twitter,it is not the sufcient assumption in spatio-temporal social networks where the users’physical limitations and... 

Bioorthogonal chemistry defines any reaction, inside or outside the living systems, without interfering with native chemical processes and 3dimensional structure of proteins. In these types of reactions water is the sole solvent; a neutral pH is required; the temperature must be up to 40 oC. The kinetics of reactions must be on the hour scale and the nontoxic reagents with low concentration must be used. One of the simplest methods of visualizing protein molecule is covalent attachment of fluorescein to protein. In this work several fluorescent compounds were synthesized. These novel compounds include acylchloride fluorescein, N-hydroxysuccinimide fluorescein, thiophenol fluorescein, and... 

The most important factor in protein's function and its 3D structure is folding. Misfolding or native folding perturbation in some peptides and proteins force them get into amyloid fibril aggregation. It has been observed that these aggregations are the cause of some debilitative diseases especially ones that are related to aging like Alzheimer disease, Hantington's disease, typeII diabets etc. Recently it has been shown that specific regions in human catalase protein interact with some amyloid fibrils, such as Aß, IAPP, PrP etc. Inteins are self-splicing protein enzymes, which excise themselves from the mature protein and join the two flanking adjacent sequences by a new peptide bond in a... 

In recent years, machine learning has been widely used to solve various computational problems. One of the most fundamental and integral type of these issues is the problem of classification, in which the data samples of different types such as image, voice, or video are classified into different categories. Since these data types are inherently sequential, the problem of classifying sequential data, is of great importance. This problem has a wide range of applications, including but not restricted to, handwriting recognition, voice recognition, malware detection, and fraud detection in financial transactions. Regarding the fact that in many cases, the length of the sequence (which could be... 

Online social services and stores has become more popular in recent years . With the growing number of products and services available in these online stores and websites , recommendation systems play an important role in predicting which products and services are good for each user so that they can buy the product they need or use the online services they want without wasting their time to find the right ones . We propose a method called Temporal Socio-Content Poisson Factorization (TSCPF) which aims to recommend the most probable document to be read by each user at any given time . We model users’ behaviors and interests by using temporal point processes to capture temporal dynamics of... 

We consider a manifold M equipped with 1-forms eta(1)...eta(s) which satisfy certain contact like properties. We prove a generalization of the classical Darboux theorem for such manifolds  

In this thesis, we review the proof to standardness of Einstein solvamanifolds which is based on some results from Geometric Invariant Theory and stratification of topological spaces. Standardness is a very simple and yet powerful algebraic condition on the lie algebra of a solvmanifold which yields to remarkable existence and uniqueness and obstruction results  

Expansion of using social networks for reading and sharing news on the one hand, allows for quick and easy access to the news, but on the other hand, increases the spread of fake news and misleads many users. Therefore, identifying the fake news and attempting to mitigate its spreading on social networks is one of the major research areas in recent years. An important issue in this regard is reducing the time gap between news release time and identifying it as fake and starting to take action. Many researches has been done on detection of fake news, but since there is a trade-off between minimizing the time gap and maximizing accuracy, work on these models continues. There are also different... 

Quorum Sensing is a cell-to-cell communication pr°Cess depending on cell concentration. Communication among bacterial cells °Ccurs through small molecular signals called autoinducers. The consequences of quorum sensing include the activation of pathogenic properties and activation of the gene for biofilm formation. Biofilms are aggregations of bacteria that adhere to surfaces through extracellular polymeric substances. Bacteria in the biofilm phase are much more resistant to antimicrobial agents than their free-swimming counterparts (i.e. the bacteria in planktonic form). In this study, first a series of coumarin derivatives were synthesized; but due to low solubility of the synthesized... 

Feature Extraction is an inseparable part of many machine learning algorithms. The extracted feature from the input data, while preserving the label information as much as possible, should make label inference more feasible than the input data itself. Additionally, in many machine learning, information theory, and privacy problems we have another constraint on eliminating sensitive, confounding, or unwanted information from the feature. That is why the problem of feature extraction with information regularization (preserving desired information and removing unwanted one) becomes an important issue that has been considered from different aspects, inter-connecting various fields.In this... 

Asparagainase is a therapeutic enzyme which has been a subject of research for decades. The enzyme catalyzes the hydrolysis of the amide group in asparagine and similar amides. Altering the substrate specificity and stabilization of this enzyme can increase its therapeutic properties. Moreover, asparaginases may be evolved to catalyze the hydrolysis of other similar compounds. These can be achieved through directed evolution and computational methods.In this study, the gene encoding L-asparaginase II enzyme from E. coli was amplified by polymerase chain reaction (PCR) and was cloned into an expression vector. The recombinant protein was expressed by an appropriate host secreting the... 

Single-cell RNA-sequencing has opened opportunities to unlock the cell transcriptome at cellular-level resolution and investigate cell population structures and cell-type-specific gene expression patterns. Previously, we were only able to perform bulk RNA sequencing regardless of the cell type composition of cell populations. Now, with the advancements in sequencing technologies, it is possible to extract cell-level and cell-type-specific sequences, related to each type of cell separately and in a scalable and high-throughput manner. For such large studies, logistical constraints inevitably dictate that data be generated separately i.e., at different times and with different operators.... 

The reductase enzymes perform an important function in the cell. These enzymes are usually coupled with other enzymes and participate in reactions such as halogenation, reduction of alkene, and carboxylic acids. These reactions are carried out by reproducing cofactors such as FADH2 and NAD+; however, there is no evidence that this enzyme alone can perform an organic reaction. In this work, we aim to examine whether recombinant flavin reductase can carry out organic reactions. In order to amplify the flavin reductase enzyme gene from the E. coli genome by PCR (Polymerase Chain Reaction) method, two synthetic primers were designed; The forward primer of the gene contained a cleavage site for... 

In this thesis, we have shown that unique subgraphs of a graph have a key role in structure of the graph. Using unique subgraph which is called “anchor” here, the reconstruction of graphs is explained. Using anchor, we have shown that almost every n-vertex graph is determined by its 3log(n)-vertex subgraphs. In the second part of the thesis, a novel randomized algorithm is proposed for the graph isomorphism problem which is very simple and fast. It solves this problem with running time O(n^{2.373} \log(n)) for any pair of $n$-vertex graphs whose adjacency matrices are not strongly co-det. Strongly co-det pair of matrices have very special symmetric structure which can be disarranged to be... 

Using automated assistants in medical applications has been increased in recent years. One of the most popular methods are artificial intelligence and deep learning methods which are specifically used in medical images analysis. Using these methods can improve the diagnosis accuracy, while performing in a faster time. So these methods can reduce the economical costs, error rate, and response time. But one important challenge in deep learning methods, is the interpretability of neural networks. In this research we focused on introducing an interpretability method for our pixel-wise segmentation network which is applied to the lung nodules dataset. In this research we first implemented a... 

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...