An optimized TOPS+ comparison method for enhanced TOPS models

This article has been made available through the Brunel Open Access Publishing Fund.Background Although methods based on highly abstract descriptions of protein structures, such as VAST and TOPS, can perform very fast protein structure comparison, the results can lack a high degree of biological significance. Previously we have discussed the basic mechanisms of our novel method for structure comparison based on our TOPS+ model (Topological descriptions of Protein Structures Enhanced with Ligand Information). In this paper we show how these results can be significantly improved using parameter optimization, and we call the resulting optimised TOPS+ method as advanced TOPS+ comparison method i.e. advTOPS+. Results We have developed a TOPS+ string model as an improvement to the TOPS [1-3] graph model by considering loops as secondary structure elements (SSEs) in addition to helices and strands, representing ligands as first class objects, and describing interactions between SSEs, and SSEs and ligands, by incoming and outgoing arcs, annotating SSEs with the interaction direction and type. Benchmarking results of an all-against-all pairwise comparison using a large dataset of 2,620 non-redundant structures from the PDB40 dataset [4] demonstrate the biological significance, in terms of SCOP classification at the superfamily level, of our TOPS+ comparison method. Conclusions Our advanced TOPS+ comparison shows better performance on the PDB40 dataset [4] compared to our basic TOPS+ method, giving 90 percent accuracy for SCOP alpha+beta; a 6 percent increase in accuracy compared to the TOPS and basic TOPS+ methods. It also outperforms the TOPS, basic TOPS+ and SSAP comparison methods on the Chew-Kedem dataset [5], achieving 98 percent accuracy. Software Availability: The TOPS+ comparison server is available at http://balabio.dcs.gla.ac.uk/mallika/WebTOPS/.This article is available through the Brunel Open Access Publishing Fun

Single nucleotide polymorphisms and breast cancer: not yet a success story

Numerous studies have examined low penetrance susceptibility polymorphisms in candidate genes, with some reporting significant findings. However, for the most part these associations could not be replicated in subsequent studies, suggesting that the original observations were due to chance. The failure to identify meaningful common genetic variation in relation to breast cancer should give us pause for thought and make us reconsider our current research strategies. The most recent directions of pooling samples to increase statistical power and pursuing whole genome screens may overcome some obstacles while also creating new challenges. Future studies should perhaps also consider alternative designs such as using surrogate (preferably continuous) markers of breast cancer, focusing on high-risk populations, and defining pathologically distinct outcomes

Single nucleotide polymorphisms and breast cancer: not yet a success story

Numerous studies have examined low penetrance susceptibility polymorphisms in candidate genes, with some reporting significant findings. However, for the most part these associations could not be replicated in subsequent studies, suggesting that the original observations were due to chance. The failure to identify meaningful common genetic variation in relation to breast cancer should give us pause for thought and make us reconsider our current research strategies. The most recent directions of pooling samples to increase statistical power and pursuing whole genome screens may overcome some obstacles while also creating new challenges. Future studies should perhaps also consider alternative designs such as using surrogate (preferably continuous) markers of breast cancer, focusing on high-risk populations, and defining pathologically distinct outcomes

Generating samples for association studies based on HapMap data

<p>Abstract</p> <p>Background</p> <p>With the completion of the HapMap project, a variety of computational algorithms and tools have been proposed for haplotype inference, tag SNP selection and genome-wide association studies. Simulated data are commonly used in evaluating these new developed approaches. In addition to simulations based on population models, empirical data generated by perturbing real data, has also been used because it may inherit specific properties from real data. However, there is no tool that is publicly available to generate large scale simulated variation data by taking into account knowledge from the HapMap project.</p> <p>Results</p> <p>A computer program (<it>gs</it>) was developed to quickly generate a large number of samples based on real data that are useful for a variety of purposes, including evaluating methods for haplotype inference, tag SNP selection and association studies. Two approaches have been implemented to generate dense SNP haplotype/genotype data that share similar local <it>linkage disequilibrium </it>(LD) patterns as those in human populations. The first approach takes haplotype pairs from samples as inputs, and the second approach takes patterns of haplotype block structures as inputs. Both quantitative and qualitative traits have been incorporated in the program. Phenotypes are generated based on a disease model, or based on the effect of a quantitative trait nucleotide, both of which can be specified by users. In addition to single-locus disease models, two-locus disease models have also been implemented that can incorporate any degree of epistasis. Users are allowed to specify all nine parameters in a 3 × 3 penetrance table. For several commonly used two-locus disease models, the program can automatically calculate penetrances based on the population prevalence and marginal effects of a disease that users can conveniently specify.</p> <p>Conclusion</p> <p>The program <it>gs </it>can effectively generate large scale genetic and phenotypic variation data that can be used for evaluating new developed approaches. It is freely available from the authors' web site at <url>http://www.eecs.case.edu/~jxl175/gs.html</url>.</p

No evidence for association between polymorphisms in GRM3 and schizophrenia

BACKGROUND: Three studies have previously reported data that were interpreted by the authors as supportive of association between schizophrenia and polymorphisms in the gene encoding the metabotropic glutamate receptor GRM3. METHODS: In a bid to examine this hypothesis, we examined seven SNPs spanning GRM3 in a UK case-control sample (schizophrenic cases n = 674, controls n = 716). These included all SNPs previously reported to be associated, alone or in haplotypes, with schizophrenia in European or European American samples. RESULTS: Our data showed no evidence for association with single markers, or 2, 3, 4 and 5 marker haplotypes, nor did any specific haplotypes show evidence for association according to previously observed patterns. CONCLUSION: Examination of our own data and those of other groups leads us to conclude that at present, GRM3 should not be viewed as a gene for which there is replicated evidence for association with schizophrenia

Large Anomalous Hall effect in a silicon-based magnetic semiconductor

Magnetic semiconductors are attracting high interest because of their potential use for spintronics, a new technology which merges electronics and manipulation of conduction electron spins. (GaMn)As and (GaMn)N have recently emerged as the most popular materials for this new technology. While Curie temperatures are rising towards room temperature, these materials can only be fabricated in thin film form, are heavily defective, and are not obviously compatible with Si. We show here that it is productive to consider transition metal monosilicides as potential alternatives. In particular, we report the discovery that the bulk metallic magnets derived from doping the narrow gap insulator FeSi with Co share the very high anomalous Hall conductance of (GaMn)As, while displaying Curie temperatures as high as 53 K. Our work opens up a new arena for spintronics, involving a bulk material based only on transition metals and Si, and which we have proven to display a variety of large magnetic field effects on easily measured electrical properties.Comment: 19 pages with 5 figure