Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Positive Association between Aspirin-Intolerant Asthma and Genetic Polymorphisms of FSIP1: a Case-Case Study

<p>Abstract</p> <p>Background</p> <p>Aspirin-intolerant asthma (AIA), which is caused by non-steroidal anti-inflammatory drugs (NSAIDs) such as aspirin, causes lung inflammation and reversal bronchi reduction, leading to difficulty in breathing. Aspirin is known to affect various parts inside human body, ranging from lung to spermatogenesis. <it>FSIP1</it>, also known as <it>HDS10</it>, is a recently discovered gene that encodes fibrous sheath interacting protein 1, and is regulated by amyloid beta precursor protein (APP). Recently, it has been reported that a peptide derived from APP is cleaved by α disintegrin and metalloproteinase 33 (<it>ADAM33</it>), which is an asthma susceptibility gene. It has also been known that the <it>FSIP1 </it>gene is expressed in airway epithelium.</p> <p>Objectives</p> <p>Aim of this study is to find out whether <it>FSIP1 </it>polymorphisms affect the onset of AIA in Korean population, since it is known that AIA is genetically affected by various genes.</p> <p>Methods</p> <p>We conducted association study between 66 single nucleotide polymorphisms (SNPs) of the <it>FSIP1 </it>gene and AIA in total of 592 Korean subjects including 163 AIA and 429 aspirin-tolerant asthma (ATA) patients. Associations between polymorphisms of <it>FSIP1 </it>and AIA were analyzed with sex, smoking status, atopy, and body mass index (BMI) as covariates.</p> <p>Results</p> <p>Initially, 18 SNPs and 4 haplotypes showed associations with AIA. However, after correcting the data for multiple testing, only one SNP showed an association with AIA (corrected <it>P</it>-value = 0.03, OR = 1.63, 95% CI = 1.23-2.16), showing increased susceptibility to AIA compared with that of ATA cases. Our findings suggest that <it>FSIP1 </it>gene might be a susceptibility gene for aspirin intolerance in asthmatics.</p> <p>Conclusion</p> <p>Although our findings did not suggest that SNPs of <it>FSIP1 </it>had an effect on the reversibility of lung function abnormalities in AIA patients, they did show significant evidence of association between the variants in <it>FSIP1 </it>and AIA occurrence among asthmatics in a Korean population.</p

Cotranslational protein assembly imposes evolutionary constraints on homomeric proteins

Cotranslational protein folding can facilitate rapid formation of functional structures. However, it might also cause premature assembly of protein complexes, if two interacting nascent chains are in close proximity. By analyzing known protein structures, we show that homomeric protein contacts are enriched towards the C-termini of polypeptide chains across diverse proteomes. We hypothesize that this is the result of evolutionary constraints for folding to occur prior to assembly. Using high-throughput imaging of protein homomers in vivo in E. coli and engineered protein constructs with N- and C-terminal oligomerization domains, we show that, indeed, proteins with C-terminal homomeric interface residues consistently assemble more efficiently than those with N-terminal interface residues. Using in vivo, in vitro and in silico experiments, we identify features that govern successful assembly of homomers, which have implications for protein design and expression optimization

The complete genome sequence of Corynebacterium pseudotuberculosis FRC41 isolated from a 12-year-old girl with necrotizing lymphadenitis reveals insights into gene-regulatory networks contributing to virulence

Trost E, Ott L, Schneider J, et al. The complete genome sequence of Corynebacterium pseudotuberculosis FRC41 isolated from a 12-year-old girl with necrotizing lymphadenitis reveals insights into gene-regulatory networks contributing to virulence. BMC Genomics. 2010;11(1): 728

Neutrinos

229 pages229 pages229 pagesThe Proceedings of the 2011 workshop on Fundamental Physics at the Intensity Frontier. Science opportunities at the intensity frontier are identified and described in the areas of heavy quarks, charged leptons, neutrinos, proton decay, new light weakly-coupled particles, and nucleons, nuclei, and atoms

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe