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PMD compensation in multilevel coded-modulation schemes with coherent detection using blast algorithm and iterative polarization cancellation

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OPTICS EXPRESS 2008年第19期16卷 14845-14852页

作者： Djordjevic, Ivan B. Xu, Lei Wang, Ting Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA NEC Labs Amer Princeton NJ 08540 USA

We present two PMD compensation schemes suitable for use in multilevel (M >= 2) block-coded modulation schemes with coherent detection. The first scheme is based on (a) under bar blast-type polarization-interference cancellation scheme, and the second scheme is based on iterative polarization cancellation. Both schemes use the LDPC codes as channel codes. The proposed PMD compensations schemes are evaluated by employing coded-OFDM and coherent detection. When used in combination with girth-10 LDPC codes those schemes outperform polarization-time coding based OFDM by 1 dB at BER of 10(-9), and provide two times higher spectral efficiency. The proposed schemes perform comparable and are able to compensate even 1200 ps of differential group delay with negligible penalty. (C) 2008 Optical Society of America.

关键词： .Multilevel LDPC Coherent Detection girth proposed schemes spectral efficiency polarization interference blast algorithm polarization cancellation PMD compensation schemes cancellation scheme

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blast algorithm Accelerator with Multi-seeds Detection and Parallel Extension

BLAST Algorithm Accelerator with Multi-seeds Detection and P...

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2012年互联网技术与应用国际学术会议

作者： Quanhua Shen Fei Xia Naval University of Engineering Electronic Engineering College Naval University of Engineering

1.引言序列比对与搜索是生物信息学基因组研究的基础,而blast(Basic Local Alignment Search Tool)[1]是序列比对研究领域最重要的研究工具之一。随着生物序列数据库规

关键词： Multi-seeds Detection Hardware Acceleration Biosequence searching blast algorithm FPGA

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blast: B-LAyered bad-character SHIFT tables for high-speed pattern matching

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IET INFORMATION SECURITY 2013年第3期7卷 195-202页

作者： Choi, Yoon-Ho Seo, Seung-Woo Kyonggi Univ Dept Convergence Secur Suwon 443370 South Korea Seoul Natl Univ Sch Elect Engn & Comp Sci Seoul 151744 South Korea

In this study, the authors propose a new multi-pattern matching algorithm, called blast (B-LAyered bad-character Shift Tables with a single-byte search unit), which considers space-time tradeoff in the context of shift values during the search. Here, the term bad character' is a character that causes a mismatch. While checking multiple bytes in scanning the text at a time, the blast algorithm overcomes the reduction of the average shift value in a typical search, which is caused by the dependency on the multi-byte search unit (MBSU) and the large frequency of the last character of the given patterns. From the theoretical analysis, the authors validate the correctness of the blast algorithm. Also, from the experimental results across different setups, the authors show that the blast algorithm provides the faster search time than the other algorithms. For example, the authors obtain an enhancement by as much as 212.41% on average for various numbers of attack patterns and attack traffic conditions compared with that of the modified Wu-Manber algorithm. In addition, it is shown that the blast algorithm drastically reduces the amount of memory required for constructing the shift table based on a MBSU from 64 KB to 1 KB.

关键词： search problems string matching text analysis computer network security B-layered bad-character SHIFT tables high-speed pattern matching multipattern matching algorithm space-time tradeoff shift values blast algorithm text scanning byte checking single-byte search unit single bad-character SHIFT table multibyte search unit MBSU pattern search time attack patterns attack traffic conditions Wu-Manber algorithm

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A Parallel Architecture for High Speed blast Using FPGA 22

A Parallel Architecture for High Speed BLAST Using FPGA

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22nd Iranian Conference on Electrical Engineering (ICEE)

作者： Mahmoodi, Mohammad Reza Nikaein, Hossein Fahimi, Zahra Isfahan Univ Technol Dept Elect & Comp Engn Esfahan Iran

ISBN: (纸本)9781479944095

Undoubtedly, Basic Local Alignment Search Tool is one of the most prevalent algorithms in sequence searching and bioinformatics. blast is an index-based approach in order to recognize an unknown string of DNA sequence and due to its high computational nature, different types of hardware configurations have been proposed. In this paper, the traditional algorithm is applied;however a new architecture is proposed to speed up the algorithm. The design consists of a workstation and a FPGA as an accelerator. The system is based on 41 parallel cores implemented on Xilinx XC4VFX100 FPGA device. The most appealing features of this design are its speed and long input streams. Queries and subjects up to thousands of characters are processed in this architecture and it is verified to be 75.1 faster than NCBI software run at 3GHz, Pentium4 system.

关键词： FPGA Sequence Searching blast algorithm Hardware Implementation

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A blast implementation in Hadoop MapReduce using low cost commodity hardware 1

A Blast implementation in Hadoop MapReduce using low cost co...

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1st International Conference on Intelligent Computing in Data Sciences (ICDS)

作者： Khawla, Tadist Fatiha, Mrabti Azeddine, Zahi Said, Najah Univ Sidi Mohammed Ben Abdellah Lab Signals Syst & Components Fes 30000 Morocco Univ Sidi Mohammed Ben Abdellah Lab Intelligent Syst & Applicat Fes 30000 Morocco

It is a known fact that health in all its kinds is the key to a successful society. The medical field is nowadays generating huge flows of data that need urgent, fast analyzing, and processing. A complete analysis of a patient's personal file is now a must in order to understand the different diseases and thus be able to find cures. Due to the amount of generated medical Data that is going out of hand, a desperate need to new Big Data technologies has manifested itself. In this paper, we offer an implementation of the blast (Basic local alignment tool) algorithm in Hadoop MapReduce using low commodity hardware to prove the ability of Big Data technologies to work on the medical field even with low budgets. (C) 2018 The Authors. Published by Elsevier B.V.

关键词： Healthcare Big Data blast algorithm Apache Hadoop

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Cyberparablast: the parallelized blast web server

CyberparaBLAST: the parallelized BLAST web server

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International Conference on Cyberworlds (CW 2003)

作者： Qi, YT Lin, F Nanyang Technol Univ Sch Comp Engn Bioinformat Res Ctr Singapore 639798 Singapore

ISBN: (纸本)0769519229

Retrieving homologous sequences from existing databases, for instance, is a fundamental routine for the bioinformatics research community. Programs of the NCBI blast family have been widely used for retrieving homologous sequences from existing databases. This article briefly introduces and evaluates a parallelized version of the blast algorithm using Message Passing Interface (MPI) on a multi-node compute cluster, parablast and its web server, Cyberparablast The Cyberparablast web server can be accessed through web browsers on intranet web servers' Cyberparablast enables the researchers Of institutes to query sequence databases in the real time when needed. Parallelized computing together with cyber access make the bioinformatics research more efficient with the aid of Cyberparablast.

关键词： biology computing online front-ends Web sites network servers message passing cyberparablast Web server homologous sequence retrieval database bioinformatics blast algorithm message passing interface MPI multi-node compute cluster Web browser Intranet Web server real-time

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Knotted vs. Unknotted Proteins: Evidence of Knot-Promoting Loops

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PLOS COMPUTATIONAL BIOLOGY 2010年第7期6卷 e1000864-e1000864页

作者： Potestio, Raffaello Micheletti, Cristian Orland, Henri SISSA I-34014 Trieste Italy DEMOCRITOS CNR IOM Trieste Italy Italian Inst Technol SISSA Unit Trieste Italy CEA Inst Phys Theor Gif Sur Yvette France

Knotted proteins, because of their ability to fold reversibly in the same topologically entangled conformation, are the object of an increasing number of experimental and theoretical studies. The aim of the present investigation is to assess, on the basis of presently available structural data, the extent to which knotted proteins are isolated instances in sequence or structure space, and to use comparative schemes to understand whether specific protein segments can be associated to the occurrence of a knot in the native state. A significant sequence homology is found among a sizeable group of knotted and unknotted proteins. In this family, knotted members occupy a primary sub-branch of the phylogenetic tree and differ from unknotted ones only by additional loop segments. These "knot-promoting'' loops, whose virtual bridging eliminates the knot, are found in various types of knotted proteins. Valuable insight into how knots form, or are encoded, in proteins could be obtained by targeting these regions in future computational studies or excision experiments.

关键词： Protein structure comparison Sequence alignment Phylogenetic analysis Protein structure Proteomic databases Protein folding Protein structure databases blast algorithm

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Remote homology search with hidden Potts models

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PLOS COMPUTATIONAL BIOLOGY 2020年第11期16卷 e1008085-e1008085页

作者： Wilburn, Grey W. Eddy, Sean R. Harvard Univ Dept Phys Cambridge MA 02138 USA Harvard Univ Howard Hughes Med Inst Dept Mol & Cellular Biol Cambridge MA 02138 USA Harvard Univ John A Paulson Sch Engn & Appl Sci Cambridge MA 02138 USA

Author summary Computational homology search and alignment tools are used to infer the functions and evolutionary histories of biological sequences. Most widely used tools for sequence homology searches, such as blast and HMMER, rely on primary sequence conservation alone. It should be possible to make more powerful search tools by also considering higher-order covariation patterns induced by 3D structure conservation. Recent advances in 3D protein structure prediction have used a class of statistical physics models called Potts models to infer pairwise correlation structure in multiple sequence alignments. However, Potts models assume alignments are given and cannot build new alignments, limiting their use in homology search. We have extended Potts models to include a probability model of insertion and deletion so they can be applied to sequence alignment and remote homology search using a new model we call a hidden Potts model (HPM). Tests of our prototype HPM software show promising results in initial benchmarking experiments, though more work will be needed to use HPMs in practical tools. Most methods for biological sequence homology search and alignment work with primary sequence alone, neglecting higher-order correlations. Recently, statistical physics models called Potts models have been used to infer all-by-all pairwise correlations between sites in deep multiple sequence alignments, and these pairwise couplings have improved 3D structure predictions. Here we extend the use of Potts models from structure prediction to sequence alignment and homology search by developing what we call a hidden Potts model (HPM) that merges a Potts emission process to a generative probability model of insertion and deletion. Because an HPM is incompatible with efficient dynamic programming alignment algorithms, we develop an approximate algorithm based on importance sampling, using simpler probabilistic models as proposal distributions. We test an HPM implementation on RNA stru

关键词： Sequence alignment Multiple alignment calculation RNA alignment RNA structure Computer software Protein structure comparison Riboswitches blast algorithm

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Structural Consensus among Antibodies Defines the Antigen Binding Site

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PLOS COMPUTATIONAL BIOLOGY 2012年第2期8卷 e1002388-e1002388页

作者： Kunik, Vered Peters, Bjoern Ofran, Yanay Bar Ilan Univ Goodman Fac Life Sci Ramat Gan Israel La Jolla Inst Allergy & Immunol Div Vaccine Discovery La Jolla CA USA

The Complementarity Determining Regions (CDRs) of antibodies are assumed to account for the antigen recognition and binding and thus to contain also the antigen binding site. CDRs are typically discerned by searching for regions that are most different, in sequence or in structure, between different antibodies. Here, we show that,20% of the antibody residues that actually bind the antigen fall outside the CDRs. However, virtually all antigen binding residues lie in regions of structural consensus across antibodies. Furthermore, we show that these regions of structural consensus which cover the antigen binding site are identifiable from the sequence of the antibody. Analyzing the predicted contribution of antigen binding residues to the stability of the antibody-antigen complex, we show that residues that fall outside of the traditionally defined CDRs are at least as important to antigen binding as residues within the CDRs, and in some cases, they are even more important energetically. Furthermore, antigen binding residues that fall outside of the structural consensus regions but within traditionally defined CDRs show a marginal energetic contribution to antigen binding. These findings allow for systematic and comprehensive identification of antigen binding sites, which can improve the understanding of antigenic interactions and may be useful in antibody engineering and B-cell epitope identification.

关键词： Sequence alignment blast algorithm Binding analysis Alanine Antigens T cell receptors Built structures Protein structure

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PLOS COMPUTATIONAL BIOLOGY 2008年第5期4卷 e1000063-e1000063页

作者： Song, Nan Joseph, Jacob M. Davis, George B. Durand, Dannie Carnegie Mellon Univ Dept Biol Sci Pittsburgh PA 15213 USA Carnegie Mellon Univ Sch Comp Sci Pittsburgh PA 15213 USA

We address the problem of homology identification in complex multidomain families with varied domain architectures. The challenge is to distinguish sequence pairs that share common ancestry from pairs that share an inserted domain but are otherwise unrelated. This distinction is essential for accuracy in gene annotation, function prediction, and comparative genomics. There are two major obstacles to multidomain homology identification: lack of a formal definition and lack of curated benchmarks for evaluating the performance of new methods. We offer preliminary solutions to both problems: 1) an extension of the traditional model of homology to include domain insertions;and 2) a manually curated benchmark of well-studied families in mouse and human. We further present Neighborhood Correlation, a novel method that exploits the local structure of the sequence similarity network to identify homologs with great accuracy based on the observation that gene duplication and domain shuffling leave distinct patterns in the sequence similarity network. In a rigorous, empirical comparison using our curated data, Neighborhood Correlation outperforms sequence similarity, alignment length, and domain architecture comparison. Neighborhood Correlation is well suited for automated, genome-scale analyses. It is easy to compute, does not require explicit knowledge of domain architecture, and classifies both single and multidomain homologs with high accuracy. Homolog predictions obtained with our method, as well as our manually curated benchmark and a web-based visualization tool for exploratory analysis of the network neighborhood structure, are available at http://***. Our work represents a departure from the prevailing view that the concept of homology cannot be applied to genes that have undergone domain shuffling. In contrast to current approaches that either focus on the homology of individual domains or consider only families with identical domain archit

关键词： Sequence alignment Protein domains blast algorithm Evolutionary genetics Multiple alignment calculation Gene duplication Genome analysis Genomics

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