Academic literature on the topic 'Alignment algorithm'

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Journal articles on the topic "Alignment algorithm"

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Hung, Che-Lun, and Yaw-Ling Lin. "Implementation of a Parallel Protein Structure Alignment Service on Cloud." International Journal of Genomics 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/439681.

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Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.
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WANG, YI, and KUO-BIN LI. "MULTIPLE SEQUENCE ALIGNMENT USING AN EXHAUSTIVE AND GREEDY ALGORITHM." Journal of Bioinformatics and Computational Biology 03, no. 02 (April 2005): 243–55. http://dx.doi.org/10.1142/s021972000500103x.

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We describe an exhaustive and greedy algorithm for improving the accuracy of multiple sequence alignment. A simple progressive alignment approach is employed to provide initial alignments. The initial alignment is then iteratively optimized against an objective function. For any working alignment, the optimization involves three operations: insertions, deletions and shuffles of gaps. The optimization is exhaustive since the algorithm applies the above operations to all eligible positions of an alignment. It is also greedy since only the operation that gives the best improving objective score will be accepted. The algorithms have been implemented in the EGMA (Exhaustive and Greedy Multiple Alignment) package using Java programming language, and have been evaluated using the BAliBASE benchmark alignment database. Although EGMA is not guaranteed to produce globally optimized alignment, the tests indicate that EGMA is able to build alignments with high quality consistently, compared with other commonly used iterative and non-iterative alignment programs. It is also useful for refining multiple alignments obtained by other methods.
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Arenas-Díaz, Edgar D., Helga Ochoterena, and Katya Rodríguez-Vázquez. "Multiple Sequence Alignment Using a Genetic Algorithm and GLOCSA." Journal of Artificial Evolution and Applications 2009 (August 27, 2009): 1–10. http://dx.doi.org/10.1155/2009/963150.

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Algorithms that minimize putative synapomorphy in an alignment cannot be directly implemented since trivial cases with concatenated sequences would be selected because they would imply a minimum number of events to be explained (e.g., a single insertion/deletion would be required to explain divergence among two sequences). Therefore, indirect measures to approach parsimony need to be implemented. In this paper, we thoroughly present a Global Criterion for Sequence Alignment (GLOCSA) that uses a scoring function to globally rate multiple alignments aiming to produce matrices that minimize the number of putative synapomorphies. We also present a Genetic Algorithm that uses GLOCSA as the objective function to produce sequence alignments refining alignments previously generated by additional existing alignment tools (we recommend MUSCLE). We show that in the example cases our GLOCSA-guided Genetic Algorithm (GGGA) does improve the GLOCSA values, resulting in alignments that imply less putative synapomorphies.
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WANG, ZHUOZHI, and KAIZHONG ZHANG. "MULTIPLE RNA STRUCTURE ALIGNMENT." Journal of Bioinformatics and Computational Biology 03, no. 03 (June 2005): 609–26. http://dx.doi.org/10.1142/s0219720005001296.

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Ribonucleic Acid (RNA) structures can be viewed as a special kind of strings where characters in a string can bond with each other. The question of aligning two RNA structures has been studied for a while, and there are several successful algorithms that are based upon different models. In this paper, by adopting the model introduced in Wang and Zhang,19 we propose two algorithms to attack the question of aligning multiple RNA structures. Our methods are to reduce the multiple RNA structure alignment problem to the problem of aligning two RNA structure alignments. Meanwhile, we will show that the framework of sequence center star alignment algorithm can be applied to the problem of multiple RNA structure alignment, and if the triangle inequality is met in the scoring matrix, the approximation ratio of the algorithm remains to be [Formula: see text], where n is the total number of structures.
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BACKOFEN, ROLF, and SEBASTIAN WILL. "LOCAL SEQUENCE-STRUCTURE MOTIFS IN RNA." Journal of Bioinformatics and Computational Biology 02, no. 04 (December 2004): 681–98. http://dx.doi.org/10.1142/s0219720004000818.

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Ribonuclic acid (RNA) enjoys increasing interest in molecular biology; despite this interest fundamental algorithms are lacking, e.g. for identifying local motifs. As proteins, RNA molecules have a distinctive structure. Therefore, in addition to sequence information, structure plays an important part in assessing the similarity of RNAs. Furthermore, common sequence-structure features in two or several RNA molecules are often only spatially local, where possibly large parts of the molecules are dissimilar. Consequently, we address the problem of comparing RNA molecules by computing an optimal local alignment with respect to sequence and structure information. While local alignment is superior to global alignment for identifying local similarities, no general local sequence-structure alignment algorithms are currently known. We suggest a new general definition of locality for sequence-structure alignments that is biologically motivated and efficiently tractable. To show the former, we discuss locality of RNA and prove that the defined locality means connectivity by atomic and non-atomic bonds. To show the latter, we present an efficient algorithm for the newly defined pairwise local sequence-structure alignment (lssa) problem for RNA. For molecules of lengthes n and m, the algorithm has worst-case time complexity of O(n2·m2· max (n,m)) and a space complexity of only O(n·m). An implementation of our algorithm is available at . Its runtime is competitive with global sequence-structure alignment.
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Mirzaei, Soraya, Jafar Razmara, and Shahriar Lotfi. "GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins." BioImpacts 11, no. 4 (July 8, 2020): 271–79. http://dx.doi.org/10.34172/bi.2021.37.

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Introduction: Similarity analysis of protein structure is considered as a fundamental step to give insight into the relationships between proteins. The primary step in structural alignment is looking for the optimal correspondence between residues of two structures to optimize the scoring function. An exhaustive search for finding such a correspondence between two structures is intractable. Methods: In this paper, a hybrid method is proposed, namely GADP-align, for pairwise protein structure alignment. The proposed method looks for an optimal alignment using a hybrid method based on a genetic algorithm and an iterative dynamic programming technique. To this end, the method first creates an initial map of correspondence between secondary structure elements (SSEs) of two proteins. Then, a genetic algorithm combined with an iterative dynamic programming algorithm is employed to optimize the alignment. Results: The GADP-align algorithm was employed to align 10 ‘difficult to align’ protein pairs in order to evaluate its performance. The experimental study shows that the proposed hybrid method produces highly accurate alignments in comparison with the methods using exactly the dynamic programming technique. Furthermore, the proposed method prevents the local optimal traps caused by the unsuitable initial guess of the corresponding residues. Conclusion: The findings of this paper demonstrate that employing the genetic algorithm along with the dynamic programming technique yields highly accurate alignments between a protein pair by exploring the global alignment and avoiding trapping in local alignments.
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Zhou, Bin, and Wei Wang. "Fast Compass Alignment Algorithm of FOG SINS under Sway Condition." Applied Mechanics and Materials 321-324 (June 2013): 2171–76. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.2171.

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Through research on initial alignment problem of fiber optic gyro SINS in the sway condition, this paper proposed a rapid compass alignment scheme with variable parameters, which can accomplish rapid initial alignment. Firstly, analysted SINS compass alignment principle, and gave a concrete realization method which has the same calculation procedure with full damping navigation algorithm. This method makes the alignment and navigation to use the same set of algorithms, and can effectively reduce algorithm complexity. Simulation and repeatedly sway test results show that the alignment algorithm is effective. The alignment precision and instrument accuracy is consistent, it can meet the requirements of the initial alignment.
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Ravi, Sujith, and Kevin Knight. "Does GIZA++ Make Search Errors?" Computational Linguistics 36, no. 3 (September 2010): 295–302. http://dx.doi.org/10.1162/coli_a_00008.

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Word alignment is a critical procedure within statistical machine translation (SMT). Brown et al. (1993) have provided the most popular word alignment algorithm to date, one that has been implemented in the GIZA (Al-Onaizan et al., 1999) and GIZA++ (Och and Ney 2003) software and adopted by nearly every SMT project. In this article, we investigate whether this algorithm makes search errors when it computes Viterbi alignments, that is, whether it returns alignments that are sub-optimal according to a trained model.
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Kuchaiev, Oleksii, Tijana Milenković, Vesna Memišević, Wayne Hayes, and Nataša Pržulj. "Topological network alignment uncovers biological function and phylogeny." Journal of The Royal Society Interface 7, no. 50 (March 24, 2010): 1341–54. http://dx.doi.org/10.1098/rsif.2010.0063.

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Sequence comparison and alignment has had an enormous impact on our understanding of evolution, biology and disease. Comparison and alignment of biological networks will probably have a similar impact. Existing network alignments use information external to the networks, such as sequence, because no good algorithm for purely topological alignment has yet been devised. In this paper, we present a novel algorithm based solely on network topology, that can be used to align any two networks. We apply it to biological networks to produce by far the most complete topological alignments of biological networks to date. We demonstrate that both species phylogeny and detailed biological function of individual proteins can be extracted from our alignments. Topology-based alignments have the potential to provide a completely new, independent source of phylogenetic information. Our alignment of the protein–protein interaction networks of two very different species—yeast and human—indicate that even distant species share a surprising amount of network topology, suggesting broad similarities in internal cellular wiring across all life on Earth.
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Lin, F., Q. Chen, and L. M. Peng. "REW– exit-wave reconstruction and alignments for focus-variation high-resolution transmission electron microscopy images." Journal of Applied Crystallography 40, no. 3 (May 15, 2007): 614. http://dx.doi.org/10.1107/s0021889807008588.

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A Windows-based computer program has been developed for exit-wave reconstruction and experimental high-resolution transmission electron microscopy image alignment. While the exit-wave reconstruction is performed mainly using the maximum-likelihood method, image alignments may be carried out using several algorithms, including the time-consuming but robust genetic algorithm.
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Dissertations / Theses on the topic "Alignment algorithm"

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Starrett, Dean. "Optimal Alignment of Multiple Sequence Alignments." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/194840.

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An essential tool in biology is the alignment of multiple sequences. Biologists use multiple sequence alignments for tasks such as predicting protein structure and function, reconstructing phylogenetic trees, and finding motifs. Constructing high-quality multiple alignments is computationally hard, both in theory and in practice, and is typically done using heuristic methods. The majority of state-of-the-art multiple alignment programs employ a form and polish strategy, where in the construction phase, an initial multiple alignment is formed by progressively merging smaller alignments, starting with single sequences. Then in a local-search phase, the resulting alignment is polished by repeatedly splitting it into smaller alignments and re-merging. This merging of alignments, the basic computational problem in the construction and local-search phases of the best multiple alignment heuristics, is called the Aligning Alignments Problem. Under the sum-of-pairs objective for scoring multiple alignments, this problem may seem to be a simple extension of two-sequence alignment. It is proven here, however, that with affine gap costs (which are recognized as necessary to get biologically-informative alignments) the problem is NP-complete when gaps are counted exactly. Interestingly, this form of multiple alignment is polynomial-time solvable when we relax the exact count, showing that exact gap counts themselves are inherently hard in multiple sequence alignment. Unlike general multiple alignment however, we show that Aligning Alignments with affine gap costs and exact counts is tractable in practice, by demonstrating an effective algorithm and a fast implementation. Our software AlignAlign is both time- and space-efficient on biological data. Computational experiments on biological data show instances derived from standard benchmark suites can be optimally aligned with surprising efficiency, and experiments on simulated data show the time and space both scale well.
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Jiang, Tianwei. "Sequence alignment : algorithm development and applications /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?ECED%202009%20JIANG.

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Benli, Ozturk Esra. "A Practical Alignment Algorithm For Cassegrain Type Telescopes." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614573/index.pdf.

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Focal plane corrected Cassegrain type optical systems have been widely used in various fields. The axial alignment of complex optical systems is not easy and a practical alignment method is needed for such systems. Tilts, decenters and axial motion of elements or group of elements in the system are the typical alignment parameters. Interferometric measurement is an effective way to see the errors caused by the misalignment of each element in an optical system. In this thesis, alignment of a Cassegrain type telescope will be examined by using interferometric measurements and modulation transfer function simulations.
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Zhang, Emily H. "An efficient score alignment algorithm and its applications." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113457.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 89-90).
String alignment and comparison in Computer Science is a well-explored space with classic problems such as Longest Common Subsequence that have practical application in bioinformatic genomic sequencing and data comparison in revision control systems. In the field of musicology, score alignment and comparison is a problem with many similarities to string comparison and alignment but also vast differences. In particular we can use ideas in string alignment and comparison to compare a music score in the MIDI format with a music score generated from Optical Musical Recognition (OMR), both of which have incomplete or wrong information, and correct errors that were introduced in the OMR process to create an improved third score. This thesis creates a set of algorithms that align and compare MIDI and OMR music scores to produce a corrected version of the OMR score that borrows ideas from classic computer science string comparison and alignment algorithm but also incorporates optimizations and heuristics from music theory.
by Emily H. Zhang.
M. Eng.
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Zhang, Xiaodong. "A Local Improvement Algorithm for Multiple Sequence Alignment." Ohio University / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1049485762.

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Schwartz, Bonnie Jo. "An Evolutionary Programming Algorithm for Automatic Chromatogram Alignment." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1175715183.

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Zhang, Ching. "Genetic algorithm approaches for efficient multiple molecular sequence alignment." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0013/NQ30660.pdf.

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Hameed, A. "Parallelization of the AAE algorithm." Thesis, Honours thesis, University of Tasmania, 2007. https://eprints.utas.edu.au/3270/1/ahThesis.pdf.

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The exact algorithm formulated by Kececioglu and Starrett (2004) provides a solution to the NP-complete problem of aligning alignments in most biological cases. This work investigates potential speedups that may be gained through the parallelization of the dynamic programming phase of this particular algorithm. Results indicate it is possible to improve the run time performance of the algorithm over non-trivial alignments that compose to a matrix of greater than 10^5 cells.
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Ahmed, Nova. "Parallel Algorithm for Memory Efficient Pairwise and Multiple Genome Alignment in Distributed Environment." Digital Archive @ GSU, 2004. http://digitalarchive.gsu.edu/cs_theses/2.

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The genome sequence alignment problems are very important ones from the computational biology perspective. These problems deal with large amount of data which is memory intensive as well as computation intensive. In the literature, two separate algorithms have been studied and improved – one is a Pairwise sequence alignment algorithm which aligns pairs of genome sequences with memory reduction and parallelism for the computation and the other one is the multiple sequence alignment algorithm that aligns multiple genome sequences and this algorithm is also parallelized efficiently so that the workload of the alignment program is well distributed. The parallel applications can be launched on different environments where shared memory is very well suited for these kinds of applications. But shared memory environment has the limitation of memory usage as well as scalability also these machines are very costly. A better approach is to use the cluster of computers and the cluster environment can be further enhanced to a grid environment so that the scalability can be improved introducing multiple clusters. Here the grid environment is studied as well as the shared memory and cluster environment for the two applications. It can be stated that for carefully designed algorithms the grid environment is comparable for its performance to other distributed environments and it sometimes outperforms the others in terms of the limitations of resources the other distributed environments have.
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Kim, Eagu. "Inverse Parametric Alignment for Accurate Biological Sequence Comparison." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/193664.

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For as long as biologists have been computing alignments of sequences, the question of what values to use for scoring substitutions and gaps has persisted. In practice, substitution scores are usually chosen by convention, and gap penalties are often found by trial and error. In contrast, a rigorous way to determine parameter values that are appropriate for aligning biological sequences is by solving the problem of Inverse Parametric Sequence Alignment. Given examples of biologically correct reference alignments, this is the problem of finding parameter values that make the examples score as close as possible to optimal alignments of their sequences. The reference alignments that are currently available contain regions where the alignment is not specified, which leads to a version of the problem with partial examples.In this dissertation, we develop a new polynomial-time algorithm for Inverse Parametric Sequence Alignment that is simple to implement, fast in practice, and can learn hundreds of parameters simultaneously from hundreds of examples. Computational results with partial examples show that best possible values for all 212 parameters of the standard alignment scoring model for protein sequences can be computed from 200 examples in 4 hours of computation on a standard desktop machine. We also consider a new scoring model with a small number of additional parameters that incorporates predicted secondary structure for the protein sequences. By learning parameter values for this new secondary-structure-based model, we can improve on the alignment accuracy of the standard model by as much as 15% for sequences with less than 25% identity.
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Books on the topic "Alignment algorithm"

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Nguyen, Ken, Xuan Guo, and Yi Pan. Multiple Biological Sequence Alignment: Scoring Functions, Algorithms and Applications. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119273769.

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Perrey, Sören W. Fast approximation to the NP-hard problem of multiple sequence alignment. Palmerston North, N.Z: Faculty of Information and Mathematical Sciences, Massey University, 1996.

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Cevelev, Aleksandr. Strategic development of railway transport logistics. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1194747.

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The monograph is devoted to the methodology of material and technical support of railway transport. According to the types of activities, the nature of the material and technical resources used, technologies, means and management systems, Russian railways belong to the category of high-tech industries that must have high quality and technical level, reliability and technological efficiency in operation. For this reason, the logistics system itself, both in structure and in the algorithm of the functions performed as a whole, needs a serious improvement in the quality of its work. The economic situation in Russia requires a revision of the principles and mechanisms of management based on the corporate model of supply chain management, focused on logistics knowledge. In the difficult economic conditions of the current decade, it is necessary to improve the quality of the supply organization of enterprises and structural divisions of railway transport, directly related to the implementation of the process approach, the advantage of which is a more detailed regulation of management actions and their mutual coordination. In order to increase the efficiency of its activities and develop the management system, Russian Railways is developing a lean production system aimed at further expanding the implementation of the principles of customer orientation, ideology and corporate culture. At the present time, the solution of many issues is impossible without a cybernetic approach to the formulation of problems of material and technical support and logistics analysis of information technologies, to the implementation of the developed algorithms and models of development strategies and concepts for improving the business processes of the production system. The management strategy, or the general plan for the implementation of activities for the management of material resources, is based on a fundamental assessment of the alignment and correlation of forces and factors operating in the economic and political field, taking into account the impact on the specific form of the management strategy. The materials will be useful to the heads and specialists of the directorates of the MTO, CDZs and can be used in the scientific research of bachelors, masters and postgraduates interested in the economics of railway transport and supply logistics.
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Schwikowski, Benno. A New algorithmic approach to the construction of multiple alignments and evolutionary trees. Sankt Augustin, Germany: GMD-Forschungszentrum Informationstechnik, 1998.

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Alcon, Timothy. An alignment algorithm for linguistic comparison. 1998.

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Algorithms for automatic alignment of arrays. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1996.

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DeBlasio, Dan, and John Kececioglu. Parameter Advising for Multiple Sequence Alignment. Springer, 2019.

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Parameter Advising for Multiple Sequence Alignment. Springer, 2018.

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Bock, Juergen. Ontology Alignment using Biologically-inspired Optimisation Algorithms. KIT Scientific Publishing, 2013.

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Pan, Yi, Xuan Guo, and Ken Nguyen. Multiple Biological Sequence Alignment: Scoring Functions, Algorithms and Evaluation. Wiley & Sons, Incorporated, John, 2016.

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Book chapters on the topic "Alignment algorithm"

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Borah, Samarjeet, and Krishna Bikram Shah. "GLobal Alignment Tool (GLAT) – A Proposed Protein Alignment Algorithm." In Advances in Intelligent and Soft Computing, 885–90. New Delhi: Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0491-6_81.

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Kayed, Mohammed. "Peer Matrix Alignment: A New Algorithm." In Advances in Knowledge Discovery and Data Mining, 268–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30220-6_23.

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Tan, Chao, and Jihong Guan. "A Feature Space Alignment Learning Algorithm." In Lecture Notes in Computer Science, 795–800. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32695-0_75.

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Luo, Bin, and Edwin R. Hancock. "Procrustes Alignment with the EM Algorithm." In Computer Analysis of Images and Patterns, 623–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48375-6_74.

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Lundén, Daniel, Gizem Çaylak, Fredrik Ronquist, and David Broman. "Automatic Alignment in Higher-Order Probabilistic Programming Languages." In Programming Languages and Systems, 535–63. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30044-8_20.

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AbstractProbabilistic Programming Languages (PPLs) allow users to encode statistical inference problems and automatically apply an inference algorithm to solve them. Popular inference algorithms for PPLs, such as sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC), are built around checkpoints—relevant events for the inference algorithm during the execution of a probabilistic program. Deciding the location of checkpoints is, in current PPLs, not done optimally. To solve this problem, we present a static analysis technique that automatically determines checkpoints in programs, relieving PPL users of this task. The analysis identifies a set of checkpoints that execute in the same order in every program run—they are aligned. We formalize alignment, prove the correctness of the analysis, and implement the analysis as part of the higher-order functional PPL Miking CorePPL. By utilizing the alignment analysis, we design two novel inference algorithm variants: aligned SMC and aligned lightweight MCMC. We show, through real-world experiments, that they significantly improve inference execution time and accuracy compared to standard PPL versions of SMC and MCMC.
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Benzaid, Billel, Riccardo Dondi, and Nadia El-Mabrouk. "Duplication-Loss Genome Alignment: Complexity and Algorithm." In Language and Automata Theory and Applications, 116–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37064-9_12.

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Hess, Guillermo Nudelman, Cirano Iochpe, and Silvana Castano. "An Algorithm and Implementation for GeoOntologies Alignment." In Advances in Geoinformatics, 151–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73414-7_9.

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Shatsky, Maxim, Ruth Nussinov, and Haim J. Wolfson. "MultiProt — A Multiple Protein Structural Alignment Algorithm." In Lecture Notes in Computer Science, 235–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45784-4_18.

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Gavarraju, Lakshmi Naga Jayaprada, Jeevana Jyothi Pujari, and K. Karteeka Pavan. "Sequence Alignment by Advanced Differential Evolutionary Algorithm." In Computational Intelligence Techniques in Health Care, 69–81. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0308-0_6.

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Mokaddem, Ahmed, and Mourad Elloumi. "New Distances for Improving Progressive Alignment Algorithm." In Advances in Computing and Information Technology, 243–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-31552-7_26.

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Conference papers on the topic "Alignment algorithm"

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Guo, Lei, Lijian Zhou, Shaohui Jia, Li Yi, Haichong Yu, and Xiaoming Han. "An Automatic Segmentation Algorithm Used in Pipeline Integrity Alignment Sheet Design." In 2010 8th International Pipeline Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/ipc2010-31036.

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Pipeline segmentation design is the first step to design alignment sheet. In this step, several rectangular boxes are used to cover pipeline and each box will become the basic unit of alignment sheet design. After studying various pipeline alignment sheet mapping technologies, the author found that traditional manual design method, which can take advantage of designers’ subjectivity, causes low work efficiency. By reviewing and studying existing works at home and abroad, the author believed that it is possible and feasible to develop an automatic segmentation algorithm based on existing curve simplification algorithms to improve to improve the efficiency of pipeline section design and alignment sheet mapping. Based on several classical curve simplification algorithms, the author proposed the automatic segmentation algorithm, which automatically adjusts the location of rectangular boxes according to the number of pipeline/circle intersection points and pipeline/ rectangular box intersection points. Finally, through comparing time and result with the traditional manual method, the author proved the algorithm’s effectiveness and feasibility.
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Bergkoetter, Matthew D., and Alden S. Jurling. "Data analysis algorithm for double-pass testing of the Roman Space Telescope." In Optical System Alignment, Tolerancing, and Verification XIII, edited by José Sasián and Richard N. Youngworth. SPIE, 2020. http://dx.doi.org/10.1117/12.2567347.

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Kundeti, Vamsi, and Sanguthevar Rajasekaran. "A local structural alignment algorithm with Variable Length Alignment Fragment Pairs." In 2008 8th IEEE International Conference on Bioinformatics and BioEngineering (BIBE). IEEE, 2008. http://dx.doi.org/10.1109/bibe.2008.4696705.

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Le, Li, Chen Hongchang, and Liu Lixiong. "Sequence Alignment Algorithm in Similarity Measurement." In 2009 International Forum on Information Technology and Applications (IFITA). IEEE, 2009. http://dx.doi.org/10.1109/ifita.2009.119.

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Abdel-Mannan, Osama, A. Ben Hamza, and Amr Youssef. "Incremental Line Tangent Space Alignment Algorithm." In 2007 Canadian Conference on Electrical and Computer Engineering. IEEE, 2007. http://dx.doi.org/10.1109/ccece.2007.300.

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Haibin, Sun, Sun Yi, Jing Xiaojun, and Sun Songlin. "An improvement ISAR range alignment algorithm." In 2013 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2013. http://dx.doi.org/10.1109/globalsip.2013.6736984.

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Zhang, Ke-liang, Xiao-fei Zhang, and He-yan Huang. "A Multilayered Bilingual Word-Alignment Algorithm." In Sixth International Conference on Advanced Language Processing and Web Information Technology (ALPIT 2007). IEEE, 2007. http://dx.doi.org/10.1109/alpit.2007.108.

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Nakajima, Shinichi, Yuho Kanaya, Akira Takahashi, Koji Yoshida, and Hideo Mizutani. "Improving the measurement algorithm for alignment." In 26th Annual International Symposium on Microlithography, edited by Neal T. Sullivan. SPIE, 2001. http://dx.doi.org/10.1117/12.436780.

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Peng, Fan, Tan Yao, Zhenhui Wang, Jeffrey Zheng, and Guangyu Yue. "New Hash-based Sequence Alignment Algorithm." In BIC 2022: 2022 2nd International Conference on Bioinformatics and Intelligent Computing. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3523286.3524539.

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Hosni, Soumaya, Ahmed Mokaddem, and Mourad Elloumi. "A New Progressive Multiple Sequence Alignment Algorithm." In 2012 23rd International Workshop on Database and Expert Systems Applications (DEXA). IEEE, 2012. http://dx.doi.org/10.1109/dexa.2012.8.

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Reports on the topic "Alignment algorithm"

1

Sun, Yipeng, and Chris Adolphsen. Linac Alignment Algorithm: Analysis on 1-to-1 Steering. Office of Scientific and Technical Information (OSTI), August 2011. http://dx.doi.org/10.2172/1022483.

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Damasio, Hanna. Collaborative Research Developing, Testing and Validating Brain Alignment Algorithm using Geometric Analysis. Fort Belvoir, VA: Defense Technical Information Center, November 2013. http://dx.doi.org/10.21236/ada594406.

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Assmann, R. Quadrupole Alignment and Trajectory Correction for Future Linear Colliders: SLC Tests of a Dispersion-Free Steering Algorithm. Office of Scientific and Technical Information (OSTI), June 2004. http://dx.doi.org/10.2172/826964.

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Rangwala, Huzefa, and George Karypis. Incremental Window-based Protein Sequence Alignment Algorithms. Fort Belvoir, VA: Defense Technical Information Center, March 2006. http://dx.doi.org/10.21236/ada444856.

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Guan, X., and E. C. Uberbacher. A multiple divide-and-conquer (MDC) algorithm for optimal alignments in linear space. Office of Scientific and Technical Information (OSTI), June 1994. http://dx.doi.org/10.2172/10168027.

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CARR, ROBERT D., GIUSEPPE LANCIA, and SORIN ISTRAIL. Branch-and-Cut Algorithms for Independent Set Problems: Integrality Gap and An Application to Protein Structure Alignment. Office of Scientific and Technical Information (OSTI), September 2000. http://dx.doi.org/10.2172/764804.

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Tenenbaum, P. Beam-Based Alignment of the NLC Main Linac, Part One: Single-Bunch Comparative Study of Three Algorithms(LCC-0013). Office of Scientific and Technical Information (OSTI), April 2004. http://dx.doi.org/10.2172/826898.

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Downard, Alicia, Stephen Semmens, and Bryant Robbins. Automated characterization of ridge-swale patterns along the Mississippi River. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40439.

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The orientation of constructed levee embankments relative to alluvial swales is a useful measure for identifying regions susceptible to backward erosion piping (BEP). This research was conducted to create an automated, efficient process to classify patterns and orientations of swales within the Lower Mississippi Valley (LMV) to support levee risk assessments. Two machine learning algorithms are used to train the classification models: a convolutional neural network and a U-net. The resulting workflow can identify linear topographic features but is unable to reliably differentiate swales from other features, such as the levee structure and riverbanks. Further tuning of training data or manual identification of regions of interest could yield significantly better results. The workflow also provides an orientation to each linear feature to support subsequent analyses of position relative to levee alignments. While the individual models fall short of immediate applicability, the procedure provides a feasible, automated scheme to assist in swale classification and characterization within mature alluvial valley systems similar to LMV.
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Gur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor, and Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, January 2016. http://dx.doi.org/10.32747/2016.7600047.bard.

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Project objectives: 1) Characterization of variation for yield heterosis in melon using Half-Diallele (HDA) design. 2) Development and implementation of image-based yield phenotyping in melon. 3) Characterization of genetic, epigenetic and transcriptional variation across 25 founder lines and selected hybrids. The epigentic part of this objective was modified during the course of the project: instead of characterization of chromatin structure in a single melon line through genome-wide mapping of nucleosomes using MNase-seq approach, we took advantage of rapid advancements in single-molecule sequencing and shifted the focus to Nanoporelong-read sequencing of all 25 founder lines. This analysis provides invaluable information on genome-wide structural variation across our diversity 4) Integrated analyses and development of prediction models Agricultural heterosis relates to hybrids that outperform their inbred parents for yield. First generation (F1) hybrids are produced in many crop species and it is estimated that heterosis increases yield by 15-30% globally. Melon (Cucumismelo) is an economically important species of The Cucurbitaceae family and is among the most important fleshy fruits for fresh consumption Worldwide. The major goal of this project was to explore the patterns and magnitude of yield heterosis in melon and link it to whole genome sequence variation. A core subset of 25 diverse lines was selected from the Newe-Yaar melon diversity panel for whole-genome re-sequencing (WGS) and test-crosses, to produce structured half-diallele design of 300 F1 hybrids (MelHDA25). Yield variation was measured in replicated yield trials at the whole-plant and at the rootstock levels (through a common-scion grafted experiments), across the F1s and parental lines. As part of this project we also developed an algorithmic pipeline for detection and yield estimation of melons from aerial-images, towards future implementation of such high throughput, cost-effective method for remote yield evaluation in open-field melons. We found extensive, highly heritable root-derived yield variation across the diallele population that was characterized by prominent best-parent heterosis (BPH), where hybrids rootstocks outperformed their parents by 38% and 56 % under optimal irrigation and drought- stress, respectively. Through integration of the genotypic data (~4,000,000 SNPs) and yield analyses we show that root-derived hybrids yield is independent of parental genetic distance. However, we mapped novel root-derived yield QTLs through genome-wide association (GWA) analysis and a multi-QTLs model explained more than 45% of the hybrids yield variation, providing a potential route for marker-assisted hybrid rootstock breeding. Four selected hybrid rootstocks are further studied under multiple scion varieties and their validated positive effect on yield performance is now leading to ongoing evaluation of their commercial potential. On the genomic level, this project resulted in 3 layers of data: 1) whole-genome short-read Illumina sequencing (30X) of the 25 founder lines provided us with 25 genome alignments and high-density melon HapMap that is already shown to be an effective resource for QTL annotation and candidate gene analysis in melon. 2) fast advancements in long-read single-molecule sequencing allowed us to shift focus towards this technology and generate ~50X Nanoporesequencing of the 25 founders which in combination with the short-read data now enable de novo assembly of the 25 genomes that will soon lead to construction of the first melon pan-genome. 3) Transcriptomic (3' RNA-Seq) analysis of several selected hybrids and their parents provide preliminary information on differentially expressed genes that can be further used to explain the root-derived yield variation. Taken together, this project expanded our view on yield heterosis in melon with novel specific insights on root-derived yield heterosis. To our knowledge, thus far this is the largest systematic genetic analysis of rootstock effects on yield heterosis in cucurbits or any other crop plant, and our results are now translated into potential breeding applications. The genomic resources that were developed as part of this project are putting melon in the forefront of genomic research and will continue to be useful tool for the cucurbits community in years to come.
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