Bildiri Koleksiyonu
Recent Submissions
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Self-immobilized putrescine oxidase biocatalyst system engineered with a metal binding peptide
(American Chemical Society, 2020)Abstract Flavin oxidases are valuable biocatalysts for the oxidative synthesis of a wide range of compounds, while at the same time reduce oxygen to hydrogen peroxide. Compared to other redox enzymes, their ability to use ... -
Bio-functionalized (Ag-Ser) nanoparticle synthesis and characterization for biomedical platforms
(2021)[No abstrack available] -
A novel gene selection algorithm for cancer identification based on random forest and particle swarm optimization
(IEEE, 2015)In order to achieve informative gene from thousands of candidate genes contributing to the symptom of cancer, two novel gene selection approaches for classification of multiclass microarray datasets are proposed. In the ... -
Prediction of splice site using adaBoost with a new sequence encoding approach
(IEEE, 2016)The Biological sequence data are increasing rapidly, so there is a vital need of effective method for gene detection. Predicting of splice site is an important part of gene finding. Therefore, attempts to improve the ... -
Biomarker discovery based on BBHA and adaboostM1 on microarray data for cancer classification
(IEEE, 2016)In this paper, a new approach based on Binary Black Hole Algorithm (BBHA) and Adaptive Boosting version M1 (AdaboostM1) is proposed for finding genes that can classify the group of cancers correctly. In this approach, BBHA ... -
A novel method for splice sites prediction using sequence component and hidden markov model
(IEEE, 2016)With increasing growth of DNA sequence data, it has become an urgent demand to develop new methods to accurately predict the genes. The performance of gene detection methods mainly depend on the efficiency of splice site ... -
Splice sites prediction of Human genome using AdaBoost
(IEEE, 2016)With the rapid growth of huge amounts of DNA sequence, gene prediction has become a challenging problem in bioinformatics. Splice sites prediction plays a key role in identification of genes. Hence, development of new ... -
Gene selection and classification approach for microarray data based on random forest ranking and BBHA
(IEEE, 2016)In this paper, a novel approach based on Binary Black Hole Algorithm (BBHA) and Random Forest Ranking (RFR) is proposed for gene selection and classification of microarray data. In this approach, RFR and BBHA are used to ... -
Random forest in splice site prediction of human genome
(Springer, 2016)With the rapid growth of huge amounts of DNA sequence, genes identification has become an important task in bioinformatics. To detect genes, it is important to accurately predict splice sites, i.e. exon intron boundaries. ... -
Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization
(Institute of Electrical and Electronics Engineers Inc., 2015)Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 ... -
An application of black hole algorithm and decision tree for medical problem
(Institute of Electrical and Electronics Engineers Inc., 2015)In this study, we propose a novel method for medical data classification, it is the integration of new heuristic algorithm that get inspired the black hole phenomenon called as Black Hole Algorithm (BHA) and decision tree ...
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