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Microbial resistance to antibiotics is a rising concern among health care professionals, driving them to search for alternative therapies. In the past few years, antimicrobial peptides (AMPs) have attracted a lot of attention as a substitute for conventional antibiotics. Antimicrobial peptides have a broad spectrum of activity and can act as antibacterial,(More)
Because of the importance of proteins in inducing allergenic reactions, the ability of predicting their potential allergenicity has become an important issue. Bioinformatics presents valuable tools for analyzing allergens and these complementary approaches can help traditional techniques to study allergens. This work proposes a computational method for(More)
Many classifiers are designed with the assumption of well-balanced datasets. But in real problems, like protein classification and remote homology detection, when using binary classifiers like support vector machine (SVM) and kernel methods, we are facing imbalanced data in which we have a low number of protein sequences as positive data (minor class)(More)
Traditional antiviral therapies are expensive, limitedly available, and cause several side effects. Currently, designing antiviral peptides is very important, because these peptides interfere with the key stage of virus life cycle. Most of the antiviral peptides are derived from viral proteins for example peptide derived from HIV-1 capsid protein. Because(More)
We consider a class of random process signals which contain randomly position local similarities representing the texture of an object. Those repetitive parts may occur in speech, musical pieces and sonar signals. We suggest a warped time resolved spectrum kernel for extracting the subsequence similarity in time series in general, and as an example in(More)
In this paper, we implement a new method for classification of biological signals in general, and use it in the animal behavior classification as an example. The forced swimming test of rats or mice is a frequently used behavioral test to evaluate the efficacy of drugs in rats or mice. Frequently used features for that evaluation are obtained through(More)
G-protein coupled receptors (GPCRs) are a large superfam-ily of integral membrane proteins that transduce signals across the cell membrane. Because of that important property and other physiological roles undertaken by the GPCR family, they have been an important target of therapeutic drugs. The function of many GPCRs is not known and accurate(More)
This paper addresses the problem of object classification in a biosonar based mobile robot in a natural environment using a boosting method. We present an algorithm based on gradient boosting for biosanar-based robots that recognize different objects such as different trees via reflected sonar echoes. Gradient boosting is a machine learning approach, that(More)