scholarly journals Remote homolog detection using local sequence-structure correlations

2004 ◽  
Vol 57 (3) ◽  
pp. 518-530 ◽  
Author(s):  
Yuna Hou ◽  
Wynne Hsu ◽  
Mong Li Lee ◽  
Christopher Bystroff
Keyword(s):  
Sequence Structure ◽  
Remote Homolog ◽  
Structure Correlations ◽  
Local Sequence

Local sequence-structure correlations in proteins

1996 ◽  
Vol 7 (4) ◽  
pp. 417-421 ◽  
Author(s):  
Christopher Bystroff ◽  
Kim T Simons ◽  
Karen F Han ◽  
David Baker
Keyword(s):  
Sequence Structure ◽  
Structure Correlations ◽  
Local Sequence

LOCAL SEQUENCE-STRUCTURE MOTIFS IN RNA

2004 ◽  
Vol 02 (04) ◽  
pp. 681-698 ◽  
Author(s):  
ROLF BACKOFEN ◽  
SEBASTIAN WILL
Keyword(s):  
Information Structure ◽  
Structure Alignment ◽  
General Definition ◽  
Local Alignment ◽  
Sequence Information ◽  
Sequence Structure ◽  
Worst Case ◽  
Rna Molecules ◽  
Alignment Algorithms ◽  
Local Sequence

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.

scholarly journals An Optimization Synchronization Algorithm for TDDM Signal

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Fang Liu ◽  
Yongxin Feng
Keyword(s):  
Spread Spectrum ◽  
Sequence Structure ◽  
Estimation Formula ◽  
Synchronization Algorithm ◽  
Local Sequence ◽  
Threshold Mechanism ◽  
Global Navigation Satellite ◽  
Time Division ◽  
Synchronization Accuracy ◽  
Better Than

The time division data modulation (TDDM) mechanism is recommended to improve the communications quality and enhance the antijamming capability of the spread spectrum communication system, which will be used in the next generation global navigation satellite (GNSS) systems. According to the principle and the characteristics of TDDM signal, an optimization synchronization algorithm is proposed. In the new algorithm, the synchronization accuracy and environmental adaptability have been improved with the special local sequence structure, the multicorrelation processing, and the proportion threshold mechanism. Thus, the inversion estimation formula was established. The simulation results demonstrate that the new algorithm can eliminate the illegibility threat in the synchronization process and can adapt to a lower SNR. In addition, this algorithm is better than the traditional algorithms in terms of synchronization accuracy and adaptability.

scholarly journals Universal Architectural Concepts Underlying Protein Folding Patterns

2021 ◽  
Vol 7 ◽  
Author(s):  
Arun S. Konagurthu ◽  
Ramanan Subramanian ◽  
Lloyd Allison ◽  
David Abramson ◽  
Peter J. Stuckey ◽  
...  
Keyword(s):  
Structure Prediction ◽  
Protein Structures ◽  
Data Bank ◽  
Rational Drug Design ◽  
Basis Set ◽  
Sequence Structure ◽  
Information Theoretic ◽  
Protein Architecture ◽  
Structure Correlations ◽  
Rational Drug

What is the architectural “basis set” of the observed universe of protein structures? Using information-theoretic inference, we answer this question with a dictionary of 1,493 substructures—called concepts—typically at a subdomain level, based on an unbiased subset of known protein structures. Each concept represents a topologically conserved assembly of helices and strands that make contact. Any protein structure can be dissected into instances of concepts from this dictionary. We dissected the Protein Data Bank and completely inventoried all the concept instances. This yields many insights, including correlations between concepts and catalytic activities or binding sites, useful for rational drug design; local amino-acid sequence–structure correlations, useful for ab initio structure prediction methods; and information supporting the recognition and exploration of evolutionary relationships, useful for structural studies. An interactive site, Proçodic, at http://lcb.infotech.monash.edu.au/prosodic (click), provides access to and navigation of the entire dictionary of concepts and their usages, and all associated information. This report is part of a continuing programme with the goal of elucidating fundamental principles of protein architecture, in the spirit of the work of Cyrus Chothia.

Measurements of protein sequence-structure correlations

2004 ◽  
Vol 57 (4) ◽  
pp. 804-810 ◽  
Author(s):  
Gavin E. Crooks ◽  
Jason Wolfe ◽  
Steven E. Brenner
Keyword(s):  
Protein Sequence ◽  
Sequence Structure ◽  
Structure Correlations
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