Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for performing unsupervised learning tasks. Here we prove that principal components…
Papers in Bioinformatics
Bioinformatics papers in Biological Sciences, K
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Molecular dynamics simulations of a bacterial potassium channel (KcsA) embedded in a phospholipid bilayer reveal significant differences in interactions of the selectivity filter with K(+) compared with Na(+) ions. K(+) ions and water molecules…
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Fluorescent probes for monitoring mitochondrial membrane potential are frequently used for assessing mitochondrial function, particularly in the context of cell fate determination in biological and biomedical research. However, valid interpretation…
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MOTIVATION: A major challenge in gene expression analysis is effective data organization and visualization. One of the most popular tools for this task is hierarchical clustering. Hierarchical clustering allows a user to view relationships in scales…
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The absence of comprehensive measured kinetic values and the observed inconsistency in the available in vitro kinetic data has hindered the formulation of network-scale kinetic models of biochemical reaction networks. To meet this challenge we…
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We consider the k-core decomposition of network models and Internet graphs at the autonomous system (AS) level. The k-core analysis allows to characterize networks beyond the degree distribution and uncover structural properties and hierarchies due…
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We analytically describe the architecture of randomly damaged uncorrelated networks as a set of successively enclosed substructures-k-cores. The k-core is the largest subgraph where vertices have at least k interconnections. We find the structure of…
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Motivation: The clustering of expressed sequence tags (ESTs) is a crucial step in many sequence analysis studies that require a high level of redundancy. Chimeric sequences, while uncommon, can make achieving the optimal EST clustering a challenge.…
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Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for performing unsupervised learning tasks. Here we prove that principal components…
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K-means-type algorithms: a generalized convergence theorem and characterization of local optimality.The K-means algorithm is a commonly used technique in cluster analysis. In this paper, several questions about the algorithm are addressed. The clustering problem is first cast as a nonconvex mathematical program. Then, a rigorous proof of the…
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In the clinical application of genomic data analysis and modeling, a number of factors contribute to the performance of disease classification and clinical outcome prediction. This study focuses on the k-nearest neighbor (KNN) modeling strategy and…
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Background: Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method offers unique properties…
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BACKGROUND: Activation of the ras oncogene is commonly found in gastrointestinal tract cancers, but the role of ras in the development and progression of Barrett's oesophagus and associated cancers is uncertain. METHODS: The frequency of K-ras codon…
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Increased aerobic glycolysis and oxidative stress are important features of cancer cell metabolism, but the underlying biochemical and molecular mechanisms remain elusive. Using a tetracycline inducible model, we show that activation of K-ras(G12V)…
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Fine tuning of Ras activity is widely known as a mechanism to induce different cellular responses. Recently, we have shown that calmodulin (CaM) binds to K-Ras and that K-Ras phosphorylation inhibits its interaction with CaM. In this study we report…
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In recent years there is a growing interest in the study of sparse representation for signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described as sparse linear combinations of these atoms. Recent activity…
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The ATP analog K252a is a potent inhibitor for receptor tyrosine kinases of the Trk family. Here we show that nanomolar concentrations of K252a prevent HGF-mediated scattering in MLP-29 cells (30 nM), reduce Met-driven proliferation in GTL-16…
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Background: The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous…
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The number of complete and draft genomes is rapidly growing in recent years, and it has become increasingly important to automate the identification of functional properties and biological roles of genes in these genomes. In the KEGG database, genes…
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Background: The silkworm, Bombyx mori, is one of the most economically important insects in many developing countries owing to its large-scale cultivation for silk production. With the development of genomic and biotechnological tools, B. mori has…
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