We describe two methods for constructing an optimal global alignment of, and an optimal local alignment between, a DNA sequence and a protein sequence. The alignment model of the methods addresses the problems of frameshifts and introns in the DNA sequence. The methods require computer memory proportional to the sequence lengths, so they can rigorously process very huge sequences. The simplifie...

This paper presents a new approach for the business and information systems (IS) alignment consisting of a framework, metamodel, process, and tools for implementing it in practice. The purpose of the approach is to fill in the gap between the existing conceptual business and IS alignment frameworks and the empirical business and IS alignment methods. The suggested approach is based on the SOA, ...

BACKGROUND Predicting new non-coding RNAs (ncRNAs) of a family can be done by aligning the potential candidate with a member of the family with known sequence and secondary structure. Existing tools either only consider the sequence similarity or cannot handle local alignment with gaps. RESULTS In this paper, we consider the problem of finding the optimal local structural alignment between a ...

In this paper we present an experimental toolbox for automatic tree-to-tree alignment based on local classification and alignment inference. The aligner implements a recurrent architecture for structural prediction using history features and a sequential classification procedure. The discriminative base classifier uses a log-linear model which enables simple integration of various features extr...

MOTIVATION Sequence alignment is one of the most popular tools of modern biology. NCBI's PSI-BLAST utilizes iterative model building in order to better detect distant homologs with greater sensitivity than non-iterative BLAST. However, PSI-BLAST's performance is limited by the fact that it relies on deterministic alignments. Using a semi-probabilistic alignment scheme such as Hybrid alignment s...

UNLABELLED Liquid chromatography coupled to mass spectrometry (LC-MS) is the dominant technological platform for proteomics. An LC-MS analysis of a complex biological sample can be visualized as a 'map' of which the positional coordinates are the mass-to-charge ratio (m/z) and chromatographic retention time (RT) of the chemical species profiled. Label-free quantitative proteomics requires the a...

Multiple sequence alignment remains one of the most powerful tools for assessing sequence relateness and the identification of structurally and functionally important protein regions. In this work, two new techniques are introduced to increase the sensitivity of dynamic programming and to enable checks for alignment consistency: Profile-preprocessed and secondary structure-induced alignments. B...

Abstract. Multiple sequence alignment (MSA) is one of the most basic and central tasks for many studies in modern biology. In this paper, we present a new progressive alignment algorithm for this very difficult problem. Given two groups A and B of aligned sequences, this algorithm uses Dynamic Programming and the sum-of-pairs objective function to determine an optimal alignment C of A and B. Th...

Schema integration has become a task of increasing importance. In this paper we give a guide on how to automatically optimally set the parameters of semantic alignment algorithms respectively tools for a wide range of use cases. We basically define a utility function to rate the results of alignment algorithms. Then we backtrack from the utility function first to concrete requirements for the r...

This paper presents genetic algorithm based solution for determing alignment of multiple molecular sequences. Two datasets from DNA families Canis_familiaris and galaxy dataset have been considered for experimental work & analysis. Genetic operators like cross over rate, mutation rate can be defined by the user. Experiments & observations were recorded w.r.t variable parameters like fixed popul...