Browsing by Author "Sav, Sinem"

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Efsanenin doğduğu yer : Çarşı
(Bilkent University, 2014) Gitmez, Ali Onur; Karayiğit, Hakkı Ozan; Görgen, Hatice İdil; Gökyürek, Kıvanç; Sav, Sinem
Open Access
Examining the annealing schedules for RNA design algorithm
(IEEE, 2016-07) Erhan, H. E.; Sav, Sinem; Kalashnikov, S.; Tsang, H. H.
RNA structures are important for many biological processes in the cell. One important function of RNA are as catalytic elements. Ribozymes are RNA sequences that fold to form active structures that catalyze important chemical reactions. The folded structure for these RNA are very important; only specific conformations maintain these active structures, so it is very important for RNA to fold in a specific way. The RNA design problem describes the prediction of an RNA sequence that will fold into a given RNA structure. Solving this problem allows researchers to design RNA; they can decide on what folded secondary structure is required to accomplish a task, and the algorithm will give them a primary sequence to assemble. However, there are far too many possible primary sequence combinations to test sequentially to see if they would fold into the structure. Therefore we must employ heuristics algorithms to attempt to solve this problem. This paper introduces SIMARD, an evolutionary algorithm that uses an optimization technique called simulated annealing to solve the RNA design problem. We analyzes three different cooling schedules for the annealing process: 1) An adaptive cooling schedule, 2) a geometric cooling schedule, and 3) a geometric cooling schedule with warm up. Our results show that an adaptive annealing schedule may not be more effective at minimizing the Hamming distance between the target structure and our folded sequence's structure when compared with geometric schedules. The results also show that warming up in a geometric cooling schedule may be useful for optimizing SIMARD. © 2016 IEEE.
Open Access
Investigation of multi-objective optimization criteria for RNA design
(IEEE, 2017-12) Hampson, D. J. D.; Sav, Sinem; Tsang, H. H.
RNA design is the inverse of RNA folding and it appears to be NP-hard. In RNA design, a secondary structure is given and the goal is to find a nucleotide sequence that will fold into this structure. To find such sequence(s) involves exploring the exponentially large sequence space. In literature, heuristic algorithms are the standard technique for tackling the RNA design. Heuristic algorithms enable effective and efficient exploration of the high-dimensional sequence-structure space when searching for candidates that fold into a given target structure. The main goal of this paper is to investigate the use of multi-objective criteria in SIMARD and Quality Pre-selection Strategy (QPS). The objectives that we optimize are Hamming distance (between designed structure and target structure) and thermodynamic free energy. We examine the different combinations of optimization criteria, and attempt to draw conclusions about the relationships between them. We find that energy is a poor primary objective but makes an excellent secondary objective. We also find that using multi-objective pre-selection produces viable solutions in far fewer steps than was previously possible with SIMARD. © 2016 IEEE.
Open Access
Privacy-preserving computation and robust watermarking techniques for healthcare data
(2018-07) Sav, Sinem
Health and genomic data is sensitive in terms of carrying private information about individuals. One can infer inherited/genetic disorders, their occurrence probabilities, information about race, and kinship by analyzing an individual's genomic data. Furthermore, health data which is mostly collected by hospitals or other health institutions carries private information about individuals including the diseases they have at present or indicators of future diseases/disorders. While protecting such data, it is important to show that its utility is preserved and maximized since the data is used in researches. Regarding these facts, homomorphic encryption-based scheme (using Paillier cryptosystem) for the protection of health data and a novel watermarking scheme based on belief propagation algorithm for the genomic data is proposed in this work. Homomorphic encryption is used for the health data to show the ability of performing mathematical operations on the encrypted data without decrypting it with a real-life use-case. We show its practicality with the correctness and performance results. In the second part of this thesis, a watermarking scheme for genomic data is proposed to overcome the liability issues due to unauthorized sharing by service providers (SPs). Robust-watermarking techniques ensure the detection of malicious parties with a high probability and we show the probabilistic limits of this detection with di erent experimental setups and evaluation metrics. Lastly, this scheme guarantees the following with a high probability: (i) the utility is preserved, (ii) it is robust against single or colluding SP attacks, and (iii) watermark addition is compatible with the nature of the data as the proposed method considers auxiliary information that a malicious SP may use in order to remove/modify watermarked points before leaking the data.
Open Access
SIMARD: a simulated annealing based RNA design algorithm with quality pre-selection strategies
(IEEE, 2017-12) Sav, Sinem; Hampson, D. J. D.; Tsang, H. H.
Most of the biological processes including expression levels of genes and translation of DNA to produce proteins within cells depend on RNA sequences, and the structure of the RNA plays vital role for its function. RNA design problem refers to the design of an RNA sequence that folds into given secondary structure. However, vast number of possible nucleotide combinations make this an NP-Hard problem. To solve the RNA design problem, a number of researchers have tried to implement algorithms using local stochastic search, context-free grammars, global sampling or evolutionary programming approaches. In this paper, we examine SIMARD, an RNA design algorithm that implements simulated annealing techniques. We also propose QPS, a mutation operator for SIMARD that pre-selects high quality sequences. Furthermore, we present experiment results of SIMARD compared to eight other RNA design algorithms using the Rfam datset. The experiment results indicate that SIMARD shows promising results in terms of Hamming distance between designed sequence and the target structure, and outperforms ERD in terms of free energy. © 2016 IEEE.