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Web Services for DNA Sequence Analysis
16th International Workshop on Database and Expert Systems Applications (DEXA'05), 2006The standardized interface to sequence analysis tools is highly desirable to integrate bioinformatics applications. Currently existing software packages and programming toolkits (BioPerl, BioJava, etc.) used by bioinformaticians for DNA sequence analysis have limited support for exchanging and reusing data.
Denis Shestakov, Tapio Salakoski
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Analysis of repeating DNA sequences by reassociation.
Methods in enzymology, 1974Repetitive DNA occurs widely, if not universally, among higher organisms. A variety of procedures has been developed or adapted to examine its characteristics and a body of concepts and language has grown up to deal with its complexities. This chapter attempts to summarize this body of knowledge and technique.
Britten, Roy J. +2 more
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Computer analysis of DNA and protein sequences
European Journal of Biochemistry, 1991Some recent trends in the development of theoretical methods for DNA and protein sequence analysis are reviewed, with particular emphasis on the design of new databases, motif searches, sequence alignment algorithms and applications of neural networks.
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Computer support of DNA sequence analysis
Computer Programs in Biomedicine, 1981The paper describes a package of APL-programs suited for the management and the analysis of DNA sequence data. Most of the application programs are related to experimental work in a DNA sequencing laboratory: Search for overlapping DNA fragments to construct complete DNA sequences; search for restriction sites; computing fragment patterns when cutting ...
G, Osterburg, R, Sommer
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2009
In this chapter we introduce some of the elementary concepts for analyzing DNA sequences in terms of “words” of length 1 (bases), 2 (base pairs), 3 (triplets, such as codons), restriction sites, etc. The analysis uses some of the basic probability concepts that we have worked with in the previous chapter.
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In this chapter we introduce some of the elementary concepts for analyzing DNA sequences in terms of “words” of length 1 (bases), 2 (base pairs), 3 (triplets, such as codons), restriction sites, etc. The analysis uses some of the basic probability concepts that we have worked with in the previous chapter.
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Recent Advances in DNA Sequence Analysi
CRC Critical Reviews in Biochemistry, 1975(1975). Recent Advances in DNA Sequence Analysi. CRC Critical Reviews in Biochemistry: Vol. 2, No. 4, pp. 455-512.
Ray Wu +3 more
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Mitochondrial DNA sequence analysis in Sicily
American Journal of Human Biology, 2001AbstractThis study reports data on the sequences of the first hypervariable segment of a sample of the Sicilian population from Alia (Palermo, Italy). The results show the presence of 32 different haplotypes in the 49 individuals examined. The average number of pairwise nucleotide differences was 4.04, i.e., 1.17% per nucleotide.
Vona G +5 more
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Analysis of Variation in Chloroplast DNA Sequences
2013This chapter introduces and reviews methods for analyzing variation in chloroplast DNA, mainly by polymerase chain reaction (PCR) and subsequent revelation of polymorphisms. Sources for chloroplast primers are discussed, as well as methods such as Sanger sequencing, PCR followed by restriction fragment length polymorphism (RFLP), gel electrophoresis ...
Berthold, Heinze +2 more
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Prediction of Function in DNA Sequence Analysis
Journal of Computational Biology, 1995Recognition of function of newly sequenced DNA fragments is an important area of computational molecular biology. Here we present an extensive review of methods for prediction of functional sites, tRNA, and protein-coding genes and discuss possible further directions of research in this area.
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An expert network for DNA sequence analysis
IEEE Intelligent Systems, 1999The expert neural network system the author has developed for use in DNA sequence analysis combines a traditional symbolic expert system with an artificial neural network. The resulting hybrid system can accurately model underlying domain knowledge to improve accuracy, generalization performance, and information-processing speed.
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