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Proteins can be classified among the four structural classes of All-Alpha, All-Beta, Alpha+Beta and Alpha/Beta which are further subdivided into 27 folds. Protein fold classification problem is cited in the literature as a challenging unbalanced classification problem with the accuracy results being as low as 51.1% on the bench mark data set of Ding et al. and highest accuracy at 60.5% using 2500...
Protein is the primary element of organism and takes part in almost all the biological processes such as metabolism and neurological regulation. Generally, proteins are interacting with each other while they exert biological role in vivo. The exploration upon protein-protein interactions (PPIs) of the specific biological process could provide valuable information to the study of the relevant field...
Decisions of multiple hypotheses are combined in ensemble learning to produce more accurate and less risky results. In this article, we present a novel ensemble machine learning approach for the development of robust thermo stable protein discrimination. But unlike widely used ensemble approaches in which bootstrapped training data are used, we keep the original data unchanged. Instead, we build an...
MicroRNAs are one type of noncoding RNA that regulate their target mRNAs before mRNAs are translated into proteins. Although it has been demonstrated that the regulation is through partial binding of the seed region of a miRNA and its targets, the mechanism of this process is not fully discovered. Some biological experiments have shown that even perfect base pairing in the seed region does not always...
Classification, or supervised learning, is one of the major data mining processes. Protein classification focuses on predicting the function or the structure of new proteins. This can be done by classifying a new protein to a given family with previously known characteristics. There are many approaches available for classification tasks, such as statistical techniques, decision trees and the neural...
Ortholog detection methods present a powerful approach for finding genes that participate in similar biological processes across different organisms, extending our understanding of interactions between genes across different pathways, and understanding the evolution of gene families. We exploit features derived from the alignment of protein-protein interaction networks to reconstruct KEGG orthologs...
Recently, pattern analysis of mass spectra of blood samples has attracted attention as a promising approach to early detection of cancer. However, many questions have been raised about the reliability of the reported results due to the ldquoblack boxrdquo methods employed. The main objective of this paper is to introduce a simple framework of rule building procedure which results limited number of...
We investigate automatic classification of protein crystallization imagery, and evaluate the performance of several modern mathematical tools when applied to the problem. For feature extraction, we try a combination of geometric and texture features; for classification algorithms, the support vector machine (SVM) is compared with an automatic decision-tree classifier. Experimental results from 520...
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