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Emerging high throughput next-generation sequencing technologies provide the ability to sequence genomes at high coverage and low cost; thus, enabling numerous biological applications. The raw error rate present in reads generated by these technologies is viewed as a limiting factor for error sensitive applications such as de novo assembly and rare variant detection. Here we present two error correction...
Emerging microarray technologies allow affordable typing of very long genome sequences. A key challenge in analyzing such a huge amount of data is scalable and accurate computational inferring of haplotypes (that is, splitting of each genotype into a pair of corresponding haplotypes). In this paper, we first phase genotypes consisting only of two SNPs using genotypes frequencies adjusted to the random...
This paper addresses the computational challenge facing association analysis of case-control studies - searching an enormous amount of possible gene interactions. A complex risk factor (RF) is proposed to be modeled as close (weighted) match to a diplotype (e.g., no more than k mismatches) and the optimization formulation asks for RF with the maximum odds ratio. We have applied and cross-validated...
Recent improvements in high-throughput genotyping technology make possible genome-wide association studies and status prediction (classification) for common complex diseases. This paper addresses three challenges commonly facing such studies: (i) searching an enormous amount of possible gene interactions, (ii) validating reproducibility of associations and (iii) reliably predicting disease status...
Recent improvements in the accessibility of high-throughput genotyping have brought a deal of attention to genome-wide association studies for common complex diseases. Although, such diseases can be caused by multi-loci interactions, locus-by-locus studies are prevailing. Recently, two-loci analysis has been shown promising (Marchini et al, 2005), and multi-loci analysis is expected to find even deeper...
Energy consumption in monitoring and communication protocols for wireless sensor networks became one of the most important performance objective. We assume a commonly accepted sensor network model in which sensors can interchange idle and active modes both for monitoring and communicating. We introduce a reliability requirement for distributed target-monitoring protocols and prove that previously...
Optimizing the energy consumption in monitoring and communication protocols for wireless sensor networks has become the most important performance objective. We explore the problem of maximizing sensor network lifetime, i.e., time during which the set of targets is covered. We propose centralized algorithms for lifetime maximization with provable approximation ratio for the realistic model studied...
Recent improvements in the accessibility of high-throughput genotyping have brought a great deal of attention to disease association and susceptibility studies. This paper explores possibility of applying combinatorial methods to disease susceptibility prediction. The proposed combinatorial methods as well as standard statistical methods are applied to publicly available genotype data on Crohn's disease...
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