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    afpCOOL: a tool for antifreeze protein prediction

    , Article Heliyon ; Volume 4, Issue 7 , 2018 ; 24058440 (ISSN) Eslami, M ; Shirali Hossein Zade, R ; Takalloo, Z ; Mahdevar, G ; Emamjomeh, A ; Sajedi, R. H ; Zahiri, J ; Sharif University of Technology
    Elsevier Ltd  2018
    Abstract
    Various cold-adapted organisms produce antifreeze proteins (AFPs), which prevent the freezing of cell fluids by inhibiting the growth of ice crystals. AFPs are currently being recognized in various organisms, living in extremely low temperatures. AFPs have several important applications in increasing freeze tolerance of plants, maintaining the tissue in frozen conditions and producing cold-hardy plants by applying transgenic technology. Substantial differences in the sequence and structure of the AFPs, pose a challenge for researchers to identify these proteins. In this paper, we proposed a novel method to identify AFPs, using supportive vector machine (SVM) by incorporating 4 types of... 

    A novel panel of blood-based microRNAs capable of discrimination between benign breast disease and breast cancer at early stages

    , Article RNA Biology ; 2021 ; 15476286 (ISSN) Sadeghi, H ; Kamal, A ; Ahmadi, M ; Najafi, H ; Sharifi Zarchi, A ; Haddad, P ; Shayestehpour, B ; Kamkar, L ; Salamati, M ; Geranpayeh, L ; Lashkari, M ; Totonchi, M ; Sharif University of Technology
    Taylor and Francis Ltd  2021
    Abstract
    Breast cancer (BC) as a leading cause of cancer death among women, exhibits a wide range of genetic heterogeneity in affected individuals. Satisfactory management of BC depends on early diagnosis and proper monitoring of patients’ response to therapy. In this study, we aimed to assess the relation between the expression patterns of blood-based microRNAs (miRNAs) with demographic characteristics of the patients with BC in an attempt to find novel diagnostic markers for BC with acceptable precision in clinical applications. To this end, we performed comprehensive statistical analysis of the data of the Cancer Genome Atlas (TCGA) database and the blood miRNome dataset (GSE31309). As a result,... 

    A novel pattern matching algorithm for genomic patterns related to protein motifs

    , Article Journal of Bioinformatics and Computational Biology ; Volume 18, Issue 1 , 2020 Foroughmand Araabi, M. H ; Goliaei, S ; Goliaei, B ; Sharif University of Technology
    World Scientific Publishing Co. Pte Ltd  2020
    Abstract
    Patterns on proteins and genomic sequences are vastly analyzed, extracted and collected in databases. Although protein patterns originate from genomic coding regions, very few works have directly or indirectly dealt with coding region patterns induced from protein patterns. Results: In this paper, we have defined a new genomic pattern structure suitable for representing induced patterns from proteins. The provided pattern structure, which is called "Consecutive Positions Scoring Matrix (CPSSM)", is a replacement for protein patterns and profiles in the genomic context. CPSSMs can be identified, discovered, and searched in genomes. Then, we have presented a novel pattern matching algorithm... 

    Using Transductive Learning Classification in Bioinformatics

    , M.Sc. Thesis Sharif University of Technology Tajari, Hossein (Author) ; Beigy, Hamid (Supervisor)
    Abstract
    Classification is one of the most important problems in machine learning area. Reliable and successful classification is essential for diagnosing patients for further treatment. In many applications such as bioinformatics unlabeled data is abundant and available. However labeling data is much more difficult and expensive to obtain. This dissertation presents a novel transductive approach for the development of robust microarray data classification. The transduction problem is to estimate the value of classification function at the given points in the working set. This contrasts with the standard inductive learning problem of estimating the classification method at all possible values and... 

    Investigation on penetration of saffron components through lipid bilayer bound to spike protein of SARS-CoV-2 using steered molecular dynamics simulation

    , Article Heliyon ; Volume 6, Issue 12 , December , 2020 Kordzadeh, A ; Ramazani Saadatabadi, A ; Hadi, A ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    A coronavirus identified as COVID-19 is the reason for an infection outbreak which is started in December 2019. NO completely effective drugs and treatments are not recognized for this virus. Recently, saffron and its compounds were used to treat different viral diseases. Saffron extract and its major ingredients have shown antiviral effects. In this study, the steered molecular dynamics simulation was used for investigating the effect of four main components of saffron that include: crocin, crocetin, safranal, and picrocrocin as candidate for drug molecules, on COVID-19. The binding energies between drug molecules and spike protein and the main protease of the virus were evaluated. The... 

    An Efficient Model For Considering the Effects Of Drug On Cancer Cells

    , M.Sc. Thesis Sharif University of Technology Nikahd, Mojtaba (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    The development of technologies and some defects in medicine caused to emerge a new approach called precision medicine. Unlike the traditional medicine, medical experts do best treatment for each patient based on his genetic characteristics in this approach. Predicting drug response on cancer cell lines is one of the most vital challenges in this area. Various approaches have been proposed to construct predicting models while the substantial distinctions between resistant and sensitive cell lines had been neglected in them. Here, we propose a new approach for constructing the predictive model. In our approach, we utilized the distinctions between sensitive and resistant cell lines and also... 

    Biological Network Alignment using Multi-Core Processors

    , M.Sc. Thesis Sharif University of Technology Tavakoli Neyshabur, Behnam (Author) ; Ghodsi, Mohammad (Supervisor)
    Abstract
    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... 

    Inferring Signaling Pathways from RNAi Data Using Machine Learning

    , M.Sc. Thesis Sharif University of Technology Mazloomian, Alborz (Author) ; Beigy, Hamid (Supervisor)
    Abstract
    One of the standing problems in Molecular Biology and Bioinformatics is uncovering signaling pathways. Discovering the causes of many cancer-like diseases and developing better treatments for them, requires a better understanding of the behavior of cellular processes. Understanding signaling pathways can help to realize cellular processes. Due to the fast increase of possible signaling pathways when the number of components increases, the problem seems to have an inherent complexity. One of the recent methods for generating data relating to such networks is RNA interference technique. In this thesis we use data which are provided by this method. We propose two methods to infer signaling... 

    Protein Function Prediction using Protein Interaction Networks

    , M.Sc. Thesis Sharif University of Technology Babapour Khosravi, Niloufar (Author) ; Fatemizadeh, Emadoddin (Supervisor)
    Abstract
    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... 

    DNA Classification Using Optical Processing based on Alignment-free Methods

    , M.Sc. Thesis Sharif University of Technology Kalhor, Reza (Author) ; Koohi, Somayyeh (Supervisor)
    Abstract
    In this research, an optical processing method for DNA classification is presented in order to overcome the problems in the previous methods. With improving in the operational capacity of the sequencing process, which has increased the number of genomes, comparing sequences with a complete database of genomes is a serious challenge to computational methods. Most current classification programs suffer from either slow classification speeds, large memory requirements, or both. To achieve high speed and accuracy at the same time, we suggest using optical processing methods. The performance of electronic processing-based computing, especially in the case of large data processing, is usually... 

    Analysis of Gene Expression Data in Bioinformatics Data Sets Using Machine Learning Approaches

    , M.Sc. Thesis Sharif University of Technology Bagherian, Misagh (Author) ; Beigy, Hamid (Supervisor)
    Abstract
    As a robust and accurate classification of tumors is necessary for successful treatment of cancer, classification of DNA microarray data has been widely used in successful diagnosis of cancers and some other biological diseases. But the main challenge in classification of microarray data is the extreme asymmetry between the dimensionality of features (usually thousands or even tens of thousands of genes) and that of tissues (few hundreds of samples). Because of such curse of dimensionality, a class prediction model could be very successful in classifying one type of dataset but may fail to perform well in some other ones. Overfitting is another problem that prevents conventional learning... 

    Bayesian Filtering Approach to Improve Gene Regulatory Networks Inference Using Gene Expression Time Series

    , M.Sc. Thesis Sharif University of Technology Fouladi, Ramouna (Author) ; Fatemizadeh, Emadoddin (Supervisor) ; Arab, Shahriar (Co-Advisor)
    Abstract
    Gene regulatory modeling in different species is one of the main aims of Bioinformatics. Regarding the limitations of the data available and the perspectives which should be taken into account for modeling such networks, proposed methods up to now have not yet been successful in yielding a comprehensive model. In one of the recent researches, the Gene regulation process is considered as a nonlinear dynamic stochastic process and described by state space equations. Afterwards, in order for the unknown parameters to be estimated, Extended Kalman Filtering is used. In this thesis, first of all, Gene complexes are taken into consideration instead of genes and afterwards, Extended Kalman... 

    Distributed Processing of Next Generation Sequencing Data Set

    , M.Sc. Thesis Sharif University of Technology Hadadian Nejad Yousefi, Mostafa (Author) ; Goudarzi, Maziar (Supervisor) ; Motahari, Abolfazl (Supervisor)
    Abstract
    DNA analysis plays a significant role in fields such as pharmacy, agriculture, genealogy, and forensics. Next generation sequencing datasets cover a gene several times due to a large number of readings. Therefore, the initial data volume is several times the amount of memory required to store the DNA strand. First, the DNA sequence of a sample should be made using the primary data, and then the difference should be found by comparing the sample DNA sequence with the reference DNA sequence. By finding these differences, one can extract the characteristics of the tested species. The extracted properties are precious for genetics researchers. For example, they can produce drugs that are... 

    Erratum to A linear genetic programming approach for the prediction of solar global radiation

    , Article Neural Computing and Applications ; Volume 23, Issue 3-4 , 2013 , Pages 1205- ; 09410643 (ISSN) Shavandi, H ; Saeidi Ramiyani, S ; Sharif University of Technology
    2013

    Molecular dynamics simulation of supercoiled DNA rings

    , Article Macromolecules ; Volume 48, Issue 1 , December , 2015 , Pages 164-172 ; 00249297 (ISSN) Fathizadeh, A ; Schiessel, H ; Ejtehadi, M. R ; Sharif University of Technology
    American Chemical Society  2015
    Abstract
    DNA supercoiling is a widespread phenomenon in biology. Here we introduce a coarse-grained DNA model and study supercoiled DNA rings via a rigid body molecular dynamics simulation. Our model allows us to investigate these structures in more detail than previously. The simulations are performed on rings of one to six kilobase pairs length and are compared to available experimental data and former simulation studies. The current study provides new additional information about some of the geometrical parameters of the supercoiled DNA rings. It also shows how enforcing a supercoiled DNA ring to two-dimensional space changes its geometrical parameters. Finally, our molecular dynamics method... 

    Overcoming drug resistance by co-targeting

    , Article Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010, 18 December 2010 through 21 December 2010 ; December , 2010 , Pages 198-202 ; 9781424483075 (ISBN) Ayati, M ; Taheri, G ; Arab, S ; Wong, L ; Eslahchi, C ; Sharif University of Technology
    2010
    Abstract
    Removal or suppression of key proteins in an essential pathway of a pathogen is expected to disrupt the pathway and prohibit the pathogen from performing a vital function. Thus disconnecting multiple essential pathways should disrupt the survival of a pathogen even when it has multiple pathways to drug resistance. We consider a scenario where the drug-resistance pathways are unknown. To disrupt these pathways, we consider a cut set S of G, where G is a connected simple graph representing the protein interaction network of the pathogen, so that G-S splits to two partitions such that the endpoints of each pathway are in different partitions. If the difference between the sizes of the two... 

    Analyzing mixing quality in a curved centrifugal micromixer through numerical simulation

    , Article Chemical Engineering and Processing: Process Intensification ; 2017 ; 02552701 (ISSN) Shamloo, A ; Vatankhah, P ; Akbari, A ; Sharif University of Technology
    Elsevier B.V 
    Abstract
    The Lab On a CD (LOCD), also known as Centrifugal Microfluidics, has evolved into a sophisticated platform for performing biomedical assays due to its marvelous miniaturization and accurate simulation of biological reactions. Among the numerous applications of the LOCD is fluid mixing. In this paper a centrifugal, serpentine micromixer is simulated and reformed toward better mixing performance. The micromixer was chosen to be curved as a curved design was found to be thrice as functional and compact as a rectilinear design, mixing-wise. The two angular velocity and opening radius parameters were originally hypothesized to affect mixing performance. Effect of angular velocity was studied over... 

    Analyzing mixing quality in a curved centrifugal micromixer through numerical simulation

    , Article Chemical Engineering and Processing: Process Intensification ; Volume 116 , 2017 , Pages 9-16 ; 02552701 (ISSN) Shamloo, A ; Vatankhah, P ; Akbari, A ; Sharif University of Technology
    Elsevier B.V  2017
    Abstract
    The Lab On a CD (LOCD), also known as Centrifugal Microfluidics, has evolved into a sophisticated platform for performing biomedical assays due to its marvelous miniaturization and accurate simulation of biological reactions. Among the numerous applications of the LOCD is fluid mixing. In this paper a centrifugal, serpentine micromixer is simulated and reformed toward better mixing performance. The micromixer was chosen to be curved as a curved design was found to be thrice as functional and compact as a rectilinear design, mixing-wise. The two angular velocity and opening radius parameters were originally hypothesized to affect mixing performance. Effect of angular velocity was studied over... 

    Enhanced Waddington landscape model with cell-cell communication can explain molecular mechanisms of self-organization

    , Article Bioinformatics ; Volume 35, Issue 20 , 2019 , Pages 4081-4088 ; 13674803 (ISSN) Fooladi, H ; Moradi, P ; Sharifi Zarchi, A ; Hosein Khalaj, B ; Berger, B ; Sharif University of Technology
    Oxford University Press  2019
    Abstract
    The molecular mechanisms of self-organization that orchestrate embryonic cells to create astonishing patterns have been among major questions of developmental biology. It is recently shown that embryonic stem cells (ESCs), when cultured in particular micropatterns, can self-organize and mimic the early steps of pre-implantation embryogenesis. A systems-biology model to address this observation from a dynamical systems perspective is essential and can enhance understanding of the phenomenon. Results: Here, we propose a multicellular mathematical model for pattern formation during in vitro gastrulation of human ESCs. This model enhances the basic principles of Waddington epigenetic landscape... 

    Graph traversal edit distance and extensions

    , Article Journal of Computational Biology ; Volume 27, Issue 3 , 2020 , Pages 317-329 Ebrahimpour Boroojeny, A ; Shrestha, A ; Sharifi Zarchi, A ; Gallagher, S. R ; Sahinalp, S. C ; Chitsaz, H ; Sharif University of Technology
    Mary Ann Liebert Inc  2020
    Abstract
    Many problems in applied machine learning deal with graphs (also called networks), including social networks, security, web data mining, protein function prediction, and genome informatics. The kernel paradigm beautifully decouples the learning algorithm from the underlying geometric space, which renders graph kernels important for the aforementioned applications. In this article, we give a new graph kernel, which we call graph traversal edit distance (GTED). We introduce the GTED problem and give the first polynomial time algorithm for it. Informally, the GTED is the minimum edit distance between two strings formed by the edge labels of respective Eulerian traversals of the two graphs....