Autumn 2019 - 2020
Genome sequencing of organisms with what is called new generation sequencing technologies on a mass scale is one of the hot topics in biology.The high volume of obtained data and the low cost of these technologies make it possible to obtain a large number of short fragments in the genome of organisms. However, genome reconstruction with these short fragments is a difficult task that cannot be exploited without an efficient computational solution. Therefore, the problem of genome assembly is one of the most fundamental issues in bioinformatics. In the past decade, various algorithms for genome assembly have been developed from scratch based on reference to short length data, our main focus being genome based reference. In this work, we present a new framework that improves the quality of reconstructed genome sequences by solving the problem of multi-copy reads. To achieve this, we reduce the search space for reads mapped to the genome in a way that reduces the likelihood of misreadings. Evaluating the results of the implementation of the framework on simulated and real datasets shows that the error rate of the reconstructed genomes has decreased. Therefore, this framework can be used as a postprocessing tool in genome assembly.
represented by Farzane Salari Location : Amirkabir University Of Technology, Department Of Mathematics & Computer Science , room 313 Time : 07 Oct , 13 – 15
Cell-cycle phase is a decisive factor in determining the repair pathway of DNA double strand breaks (DSBs) by non-homologous end joining (NHEJ) or homologous recombination (HR). Recent experimental studies revealed that 53BP1 and BRCA1 are the key mediators of the DNA damage response (DDR) with antagonizing roles in choosing the appropriate DSB repair pathway in G1, S and G2 phases. Here, we present a stochastic model of biochemical kinetics involved in detecting and repairing DNA DSBs induced by ionizing radiation during the cell-cycle progression. A three-dimensional stochastic process is defined to monitor the cell-cycle phase and DSBs repair at times after irradiation. To estimate the model parameters, a Metropolis Monte Carlo (MMC) method is applied to perform maximum likelihood estimation utilizing the kinetics of γ-H2AX and RAD51 foci formation in G1, S and G2 phases.
The recruitment of DSB repair proteins is verified by comparing our model predictions with the corresponding experimental data on human cells after exposure to X and γ-radiation. Furthermore, the interaction between 53BP1 and BRCA1 is simulated for G1 and S/G2 phases determining the competition between NHEJ and HR pathways in repairing induced DSBs throughout the cell cycle. In accordance with recent biological data, the numerical results demonstrate that the maximum proportion of HR occurs in S phase cells and the high level of NHEJ takes place in G1 and G2 phases. Moreover, the stochastic realizations of the total yield of simple and complex DSBs ligation are compared for G1 and S/G2 damaged cells. Finally, the proposed stochastic model is validated when DSBs induced by different particles radiation such as iron, silicon, oxygen, proton and carbon.
represented by Fazeleh Sadat Mohseni-Salehi Location : Amirkabir University Of Technology, Department Of Mathematics & Computer Science , room 313 Time : 21 Oct , 13 – 15
De novo drug discovery is a time-consuming and expensive process. Nowadays, drug repositioning is utilized as a common strategy to discover a new drug indication for existing drugs. This strategy is mostly used in cases with a limited number of candidate pairs of drugs and diseases. In other words, they are not scalable to a large number of drugs and diseases. Most of the in-silico methods mainly focus on linear approaches while non-linear models are still scarce for new indication predictions. Therefore, applying non-linear computational approaches can offer an opportunity to predict possible drug repositioning candidates.
represented by Dr. Fatemeh Zare-Mirakabad Location : Amirkabir University Of Technology, Department Of Mathematics & Computer Science , room 313 Time : 04 Nov , 13 – 15