5,659 research outputs found

    Multiple structural alignment for distantly related all b structures using TOPS pattern discovery and simulated annealing

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    Topsalign is a method that will structurally align diverse protein structures, for example, structural alignment of protein superfolds. All proteins within a superfold share the same fold but often have very low sequence identity and different biological and biochemical functions. There is often signi®cant structural diversity around the common scaffold of secondary structure elements of the fold. Topsalign uses topological descriptions of proteins. A pattern discovery algorithm identi®es equivalent secondary structure elements between a set of proteins and these are used to produce an initial multiple structure alignment. Simulated annealing is used to optimize the alignment. The output of Topsalign is a multiple structure-based sequence alignment and a 3D superposition of the structures. This method has been tested on three superfolds: the b jelly roll, TIM (a/b) barrel and the OB fold. Topsalign outperforms established methods on very diverse structures. Despite the pattern discovery working only on b strand secondary structure elements, Topsalign is shown to align TIM (a/b) barrel superfamilies, which contain both a helices and b strands

    Aligning Multiple Sequences with Genetic Algorithm

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    The alignment of biological sequences is a crucial tool in molecular biology and genome analysis. It helps to build a phylogenetic tree of related DNA sequences and also to predict the function and structure of unknown protein sequences by aligning with other sequences whose function and structure is already known. However, finding an optimal multiple sequence alignment takes time and space exponential with the length or number of sequences increases. Genetic Algorithms (GAs) are strategies of random searching that optimize an objective function which is a measure of alignment quality (distance) and has the ability for exploratory search through the solution space and exploitation of current results

    High quality techniques for Multiple Sequences Alignment

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    This paper describe different techniques we can use for multiple sequence alignment. we have analyze different techniques we can use and find which one is better .We have taken several example as parameter. There is different approachthat we can apply in various conditions. This paper is concerned with the efficient execution Multiple sequence alignment methods in multiple client environments Multiple order alignment (MSA) is in a computational form Expensive method, which is commonly used in Large databases of computational and molecular biology Protein and gene sequences are available for scientists Community frequent, these databases are accessed to execute multiple user MSA queries Data is in server

    WAR: Webserver for aligning structural RNAs

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    We present an easy-to-use webserver that makes it possible to simultaneously use a number of state of the art methods for performing multiple alignment and secondary structure prediction for noncoding RNA sequences. This makes it possible to use the programs without having to download the code and get the programs to run. The results of all the programs are presented on a webpage and can easily be downloaded for further analysis. Additional measures are calculated for each program to make it easier to judge the individual predictions, and a consensus prediction taking all the programs into account is also calculated. This website is free and open to all users and there is no login requirement. The webserver can be found at: http://genome.ku.dk/resources/war
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