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Performance and Scalability of Parallel Systems
Performance and Scalability of Parallel Systems

... • Doubling the size of the problem means performing twice the amount of computation • Computation step: assume takes 1 time unit – message start-up time, per-word transfer time, and perhop time can be normalized w.r.t. unit computation time => W = Ts • for the fastest sequential algorithm on a sequ ...
Fast Matrix Rank Algorithms and Applications - USC
Fast Matrix Rank Algorithms and Applications - USC

... ci ∈ Fq to represent an element k−1 i=0 ci x in Fq k . The injective mapping f in the statement is just the identity mapping in this construction, i.e. f (c) = (c, 0, 0, . . . , 0). The overall preprocessing time is O(|A| + k2 log2 k log log k(log k + log q)) = O(|A|) field operations in Fqk . It fo ...
RNA-Seq Alignment v1.0 App Guide
RNA-Seq Alignment v1.0 App Guide

BitTorrent - VoD Framework
BitTorrent - VoD Framework

... • BT is a very popular peer to peer protocol with many implementations: – http://en.wikipedia.org/wiki/Comparison_of_Bit Torrent_clients ...
Biomart/ GENOME ALIGNMENT III
Biomart/ GENOME ALIGNMENT III

International Electrical Engineering Journal (IEEJ)
International Electrical Engineering Journal (IEEJ)

... **Department of Electrical Power & Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt Abstract- Economic load dispatch (ELD) in the operation of electric power system is an essential task, since it is required to determine the optimal output of electricity generating facilities, su ...
An Efficient Algorithm for Discovering Motifs in Large DNA
An Efficient Algorithm for Discovering Motifs in Large DNA

... suffix tree or De Bruijn graph, but they show poor time performance with the increase of and . Although DREME [20] can analyze very large data sets in minutes, it can only find short motifs. To process full-size ChIP-seq data sets efficiently, some algorithms based on word counting are proposed, such a ...
What`s new - JSI medical systems
What`s new - JSI medical systems

A large scale analysis of resistance gene
A large scale analysis of resistance gene

Computing intersections in a set of line segments: the Bentley
Computing intersections in a set of line segments: the Bentley

... consider the line segment intersection problem, which is defined as follows. We are given a set S = {L1 , L2 , . . . , Ln } of n line segments in the plane. Our task is to compute all pairs (Li , Lj ), i 6= j, of segments that intersect. ¡n¢ A trivial solution to this problem considers all 2 pairs ( ...
Dynamic Programming
Dynamic Programming

Analysis of Algorithms CS 465/665
Analysis of Algorithms CS 465/665

Computing the Greatest Common Divisor of - CECM
Computing the Greatest Common Divisor of - CECM

Essential Bioinformatics and Biocomputing (LSM2104
Essential Bioinformatics and Biocomputing (LSM2104

... Bioinformatics software Examples of bioinformatics software usage: After the discovery of a new gene or protein related to a disease, these questions are usually asked: • What is its function and structure? – Is it similar in sequence to a known gene or protein? (sequence similarity search) – Does ...
Evolving swarm intelligence for task allocation in a real time strategy
Evolving swarm intelligence for task allocation in a real time strategy

An rpoB signature sequence provides unique resolution for the
An rpoB signature sequence provides unique resolution for the

... Oscillatoria strains used in this study (indicated in bold in Supplementary Table S1, available with the online version of this paper) were supplied by the Pasteur Culture Collection of Cyanobacteria (PCC). All strains were incubated at 25 uC under white light (Osram Universal White) with a photosyn ...
Streaming algorithms for embedding and computing edit distance in
Streaming algorithms for embedding and computing edit distance in

... designing an embedding protocol, there is a major technical challenge when we do not have access to both of the strings at the same time and we should remove the mismatched characters. We do not know which one are those. Deleting symbols at random is unlikely to provide a good result. Moreover, we w ...
Streaming algorithms for embedding and computing edit distance in
Streaming algorithms for embedding and computing edit distance in

Cost-effective Outbreak Detection in Networks Jure Leskovec Andreas Krause Carlos Guestrin
Cost-effective Outbreak Detection in Networks Jure Leskovec Andreas Krause Carlos Guestrin

... big, well-known blogs. However, these usually have a large number of posts, and are time-consuming to read. We show, that, perhaps counterintuitively, a more cost-effective solution can be obtained, by reading smaller, but higher quality, blogs, which our algorithm can find. There are several possibl ...
Information Integration Over Time in Unreliable
Information Integration Over Time in Unreliable

... true updates Z, where P (Z(i + 1)|Z(i)) represents the transition probability for the value and the time of the (i + 1)th update given the value and the time of the ith update, independent of the first i − 1 updates. Note that this is semiMarkovian since the probability for the duration Z T (i+1)− Z ...
An Efficient Algorithm for Finding Similar Short Substrings from
An Efficient Algorithm for Finding Similar Short Substrings from

Range-Efficient Counting of Distinct Elements in a Massive Data
Range-Efficient Counting of Distinct Elements in a Massive Data

... traffic monitoring, this can be used to compute the number of distinct web pages requested from a web site or the number of distinct source addresses among all Internet protocol (IP) packets passing through a router. Further, the computation of many other aggregates of a data stream can be reduced to ...
Surveying Saccharomyces Genomes to Identify Functional Elements
Surveying Saccharomyces Genomes to Identify Functional Elements

Problem of the Week - Sino Canada School
Problem of the Week - Sino Canada School

... Since the second difference is constant we can represent the general term of the first sequence with a quadratic function. Let an = pn2 + qn + r. For n = 1, a1 = 2 = p(1)2 + q(1) + r. ∴ p + q + r = 2. (1) For n = 2, a2 = 5 = p(2)2 + q(2) + r. ∴ 4p + 2q + r = 5. (2) For n = 3, a3 = 12 = p(3)2 + q(3) ...
Multifractal characterisation of length sequences of coding and
Multifractal characterisation of length sequences of coding and

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Smith–Waterman algorithm

The Smith–Waterman algorithm performs local sequence alignment; that is, for determining similar regions between two strings or nucleotide or protein sequences. Instead of looking at the total sequence, the Smith–Waterman algorithm compares segments of all possible lengths and optimizes the similarity measure.The algorithm was first proposed by Temple F. Smith and Michael S. Waterman in 1981. Like the Needleman–Wunsch algorithm, of which it is a variation, Smith–Waterman is a dynamic programming algorithm. As such, it has the desirable property that it is guaranteed to find the optimal local alignment with respect to the scoring system being used (which includes the substitution matrix and the gap-scoring scheme). The main difference to the Needleman–Wunsch algorithm is that negative scoring matrix cells are set to zero, which renders the (thus positively scoring) local alignments visible. Backtracking starts at the highest scoring matrix cell and proceeds until a cell with score zero is encountered, yielding the highest scoring local alignment. One does not actually implement the algorithm as described because improved alternatives are now available that have better scaling (Gotoh, 1982) and are more accurate (Altschul and Erickson, 1986).
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