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The following topics are dealt with: protein-protein interaction; cancer informatics; disease informatics; protein folding; gene networks; biosequence analysis; biochemical modeling; microarray analysis; biological theory; medical informatics; RNA structure; and RNA function
Iris recognition is accepted as one of the most efficient biometric method. Implementing this method to the practical system requires the special image preprocessing where the iris feature extraction plays a crucial role. Recognition is preceeded by iris localization which consists in finding the iris boundaries as well as eyelids. In this paper the short introduction into iris localization and wavelet-based...
For many years, local circuit current through gap junctions has been seemed to be the main fundamental route for impulse transmission. In the last few years, some different evidences suggest another view on action potential propagation via myocardial cells. Some researches offered that myocardial cells may not require low-resistance connections for successful propagation of action potential. It seems...
This work presents differential evolution (DE), applied to the problem of protein folding, using the hydrophobic-polar model. Protein folding is a relevant problem in bioinformatics for which many heuristic algorithms have been proposed. DE is a relatively recent evolutionary algorithm, and has been used successfully to several engineering optimization problems, usually with continuous variables....
Knowledge of protein-protein interaction sites is vital to determine proteins' function and involvement in different pathways. Though a wide variety of methods has been proposed over the recent years in order to predict protein-protein interface residues, mainly based on single amino acid sequence inputs, each has its own drawbacks and limitations. We propose to use support vector machines (SVM) to...
In this paper, we propose a new method for inferring functional relationships between proteins from their phylogenetic profiles. The evolutionary bond energy algorithm (EBEA) enhances the greedy BEA clustering algorithm with genetic search. We conducted a series of experiments using phylogenetic profiles provided by the Cluster of Orthologous Groups of Proteins (COG) database. Experimental results...
Antibiotics have been given to food animals for several decades as a performance enhancer. For nearly as long there has been a concern that using these antimicrobials in production animals could lead to bacteria developing resistance to antibiotics and eventually escaping into the human population. While this risk is still undefined, it would be of benefit to minimize the ratio of resistant bacteria...
The vast number of expressed sequence tags (ESTs) in public databases provides an important resource for comparative and functional genomics. A variety of methods based on homology search or domain profile search have been developed to functionally annotate protein domains in ESTs. However, these methods either ignore potentially valuable information from the homologues beyond the top N hits, or they...
Hierarchical methods like Ward's and group average (Gave) and nonhierarchical methods like Jarvis Patrick's and k-means are preferred methods to cluster a diverse set of compounds for a number of drug targets (using fingerprints based descriptors). In this work the applications of fuzzy Kohonen neural network and other self-organizing map (SOM) algorithms to the clustering of chemical datasets are...
Scleroderma is an autoimmune disease of the connective tissues, which thickens and hardens the affected areas. Recently, researchers have found evidence that genes are important factors for this disease, and there exist consistent differences in the patterns of gene expressions of skin biopsies from affected and non-affected individuals. In this paper, we apply genetic programming (GP) on the gene...
In this paper we propose a new method for generating an informative QSAR model (called VSVR-QSAR) using Voronoi grid and support vector machines regression. The procedure enables researchers to understand the physicochemical meaning of the steric and electrostatics measurements and the inclusion of those measurements as latent variables in the generated QSAR model. The procedure proved to be comparable...
Protein-DNA interactions play a crucial role in transcriptional regulation and other biological processes. Quantitative predictive models of protein-DNA binding affinities can increase our understanding of molecular interaction and help validate putative transcription factor binding sites or other regulatory features. Such predictive models must take into account context-specific features associated...
A number of biclustering approaches have been developed to mitigate the limitations of standard clustering algorithms. They have different problem formulation, search strategy and computational complexity. We proposed a new biclustering method based on the framework of market basket analysis in which a bicluster is described as a frequent itemset. As a feasibility test, we compared it with several...
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