On the Complexity of Multiple Sequence Alignment

Wang, Lusheng; Jiang, Tao

doi:10.1089/cmb.1994.1.337

Cited by 781 publications

(441 citation statements)

References 15 publications

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“…It is known as the multiple sequence alignment of the set, and is often considered the "Holy Grail" in computational biology [22]. Multiple sequence alignment is NP-complete [23], which prevents its computation for more than a few short sequences.…”

Section: Nltsmentioning

confidence: 99%

Non-linear temporal scaling of surgical processes

Forestier¹,

Petitjean²,

Riffaud³

et al. 2014

Artificial Intelligence in Medicine

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Objective. Surgery is one of the riskiest and most important medical acts that is performed today. Understanding the ways in which surgeries are similar or different from each other is of major interest. Desires to improve patient outcomes and surgeon training, and to reduce the costs of surgery, all motivate a better understanding of surgical practices. To facilitate this, surgeons have started recording the activities that are performed during surgery. New methods have to be developed to be able to make the most of this extremely rich and complex data. The objective of this work is to enable the simultaneous comparison of a set of surgeries, in order to be able to extract high-level information about surgical practices. Material and Method.We introduce Non-Linear Temporal Scaling (NLTS): a method to realign a set of surgeries along their intrinsic timeline. Experiments are carried out on a set of lumbar disc neurosurgeries. We assess our method both on a highly standardised phase of the surgery (closure) and on the whole surgery.Results. Experiments show that NLTS makes it possible to consistently derive standards of surgical practice and to understand differences between groups of surgeries. We take the training of * Corresponding author -ENSISA -Universite de Haute Alsace, 12 rue des freres Lumiere, 68093 Mulhouse, France, Tel.:+33 3 8933 6963, Fax.:+33 3 8942 3282Email addresses: germain.forestier@uha.fr (Germain Forestier), francois.petitjean@monash.edu (François Petitjean), laurent.riffaud@chu-rennes.fr (Laurent Riffaud), pierre.jannin@univ-rennes1.fr (Pierre Jannin) Preprint submitted to Artificial Intelligence in MedicineSeptember 16, 2013 surgeons as the common theme for the evaluation of the results and highlight, for example, the main differences between the practices of junior and senior surgeons in the removal of a lumbar disc herniation.Conclusion. NLTS realigns a set of sequences along their intrinsic timeline, which makes it possible to extract standards of surgical practices.Supplementary material. The computer code implementing the proposed methods.

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Section: Nltsmentioning

confidence: 99%

Non-linear temporal scaling of surgical processes

Forestier¹,

Petitjean²,

Riffaud³

et al. 2014

Artificial Intelligence in Medicine

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“…Unfortunately, this problem is known to be NP-Hard (Wang and Jiang, 1994), meaning that no polynomial time solution exists (unless P=NP). In other words, the search for vertex median sequences is as hard as the phylogeny search problem over The tree alignment minimization assigns medians {S 7 .…”

Section: The Tree-alignment Problemmentioning

confidence: 99%

Phylogenetic Hypotheses and the Utility of Multiple Sequence Alignment

Wheeler¹,

Giribet

2009

Sequence AlignmentMethods, Models, Concepts, and Strategies

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“…Since this method is an all-againstall distance evaluation based and is not based on alignment, its time complexity compares favorably with the current Multiple Sequence Alignments. There is no doubt that an optimal multi sequence alignment is more desirable though it is NP-hard [15]. More practical methods such as ClustallW [16,17] use progressive alignment methods for which the time complexity is still O(mL + L 2 ) to which clustering adds an additional term of (m 2 log(m)) where m and L represent the number and length of the aligned sequences respectively.…”

Section: Fig 2 Algorithmic Operation Of the Emm Differentiatormentioning

confidence: 99%

Sequence transformation to a complex signature form for consistent phylogenetic tree using Extensible Markov Model

Kotamarti

Hahsler

Raiford

et al. 2010

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

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Abstract-Phylogenetic tree analysis using molecular sequences continues to expand beyond the 16S rRNA marker. By addressing the multi-copy issue known as the intra-heterogeneity, this paper restores the focus in using the 16S rRNA marker. Through use of a novel learning and model building algorithm, the multiple gene copies are integrated into a compact complex signature using the Extensible Markov Model (EMM). The method clusters related sequence segments while preserving their inherent order to create an EMM signature for a microbial organism. A library of EMM signatures is generated from which samples are drawn for phylogenetic analysis. By matching the components of two signatures, referred to as quasi-alignment, the differences are highlighted and scored. Scoring quasi-alignments is done using adapted Karlin-Altschul statistics to compute a novel distance metric. The metric satisfies conditions of identity, symmetry, triangular inequality and the four point rule required for a valid evolution distance metric. The resulting distance matrix is input to PHYologeny Inference Package (PHYLIP) to generate phylogenies using neighbor joining algorithms. Through control of clustering in signature creation, the diversity of similar organisms and their placement in the phylogeny is explained. The experiments include analysis of genus Burkholderia, a random microbial sample spanning several phyla and a diverse sample that includes RNA of Eukaryotic origin. The NCBI sequence data for 16S rRNA is used for validation.

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On the Complexity of Multiple Sequence Alignment

Cited by 781 publications

References 15 publications

Non-linear temporal scaling of surgical processes

Non-linear temporal scaling of surgical processes

Phylogenetic Hypotheses and the Utility of Multiple Sequence Alignment

Sequence transformation to a complex signature form for consistent phylogenetic tree using Extensible Markov Model

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