1426090
A parsimonious tree-grow method for haplotype inference
MOTIVATION
Haplotype information has become increasingly important in analyzing fine-scale molecular genetics data, such as disease genes mapping and drug design. Parsimony haplotyping is one of haplotyping problems belonging to NP-hard class.


RESULTS
In this paper, we aim to develop a novel algorithm for the haplotype inference problem with the parsimony criterion, based on a parsimonious tree-grow method (PTG). PTG is a heuristic algorithm that can find the minimum number of distinct haplotypes based on the criterion of keeping all genotypes resolved during tree-grow process. In addition, a block-partitioning method is also proposed to improve the computational efficiency. We show that the proposed approach is not only effective with a high accuracy, but also very efficient with the computational complexity in the order of O(m2n) time for n single nucleotide polymorphism sites in m individual genotypes.


AVAILABILITY
The software is available upon request from the authors, or from http://zhangroup.aporc.org/bioinfo/ptg/


CONTACT
chen@elec.osaka-sandai.ac.jp


SUPPLEMENTARY INFORMATION
Supporting materials is available from http://zhangroup.aporc.org/bioinfo/ptg/bti572supplementary.pdf
10936659
Haplotype reconstruction from SNP fragments by minimum error correction
MOTIVATION
Haplotype reconstruction based on aligned single nucleotide polymorphism (SNP) fragments is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. An important computational model of this problem is the minimum error correction (MEC) model, which has been mentioned in several literatures. The model retrieves a pair of haplotypes by correcting minimum number of SNPs in given genome fragments coming from an individual's DNA.


RESULTS
In the first part of this paper, an exact algorithm for the MEC model is presented. Owing to the NP-hardness of the MEC model, we also design a genetic algorithm (GA). The designed GA is intended to solve large size problems and has very good performance. The strength and weakness of the MEC model are shown using experimental results on real data and simulation data. In the second part of this paper, to improve the MEC model for haplotype reconstruction, a new computational model is proposed, which simultaneously employs genotype information of an individual in the process of SNP correction, and is called MEC with genotype information (shortly, MEC/GI). Computational results on extensive datasets show that the new model has much higher accuracy in haplotype reconstruction than the pure MEC model.
7324721
A technique for reducing synchronization overhead in large scale multiprocessors
A b s t r a c t The effectiveness of multiprocessing a single subroutine in a tightly coupled muir!processor system is highly dependent (among other factors) on the amount of overhead incurred due to synchronized references to shared data items by active processes. In this paper we present a technique to reduce this overhead. This is achieved by reducing the number of synchronized references issued by different processes. We describe the criteria used to identify the variables whose synchronized accesses will eliminate the need to synchronize references to other variables. Our technique can be implemented in optimizing compilers for mnltiprocessor machines. It can also be used when designing parallel algorithms for multiproeessors. We implemented the technique as a pass in the Parafrase system of the University of Illinois. Relevant measurements on all the subroutines of the EISPACK package are reported (61 subroutines). The results show that our technique is quite effective. For subroutines with interprocess communication, it reduced the number of memory references requiring synchronization by 10% in two thirds of these subroutines and by more than 30% for one third of the subroutines.
15936335
A divide-and-conquer 2.5-D floorplanning algorithm based on statistical wirelength estimation
An efficient and effective divide-and conquer 2.5D floorplanning algorithm is proposed for wirelength optimization. Modules are pre-partitioned into different dies with respect to the statistical wirelength estimation result. Then a floorplan is generated on each die for wirelength optimization. The new partitioning method successfully solves the conflict between wirelength minimization and inter-die via constraints. Experimental results show that our algorithm could provide noticeable improvement in the total wirelength compared to both 2D design and the previous 2.5D floorplanning algorithm.
5807481
Compiler algorithms for event variable synchronization
Event variable synchronization is a well known mecha nism for enforcing data dependences in a program that runs in parallel on a shared memory multiprocessor This paper presents compiler algorithms to automati cally generate event variable synchronization code Pre viously published algorithms dealt with single parallel loops in which dependence distances are constant and known by the compiler However loops in real appli cation programs are often arbitrarily nested Moreover compilers are often unable to determine dependence dis tances In contrast our algorithms generate synchro nization code based directly on array subscripts and do not require constant distances in data dependences The algorithms are designed for arbitrarily nested loops in cluding triangular or trapezoidal loops
5069727
Interprocedural Analysis for Parallel Programs
5391500
A High-Throughput Overlay Multicast Infrastructure with Network Coding
Network coding has been recently proposed in information theory as a new dimension of the information multicast problem that helps achieve optimal transmission rate or cost. End hosts in overlay networks are natural candidates to perform network coding, due to its available computational capabilities. In this paper, we seek to bring theoretical advances in network coding to the practice of high-throughput multicast in overlay networks. We have completed the first real implementation of network coding in end hosts, as well as decentralized algorithms to construct the routing strategies and to perform random code assignment. Our experiences suggest that approaching maximum throughput with network coding is not only theoretically sound, but also practically promising. We also present a number of unique challenges in designing and realizing coded data dissemination, and corresponding solution techniques to address them.