Literature DB >> 34902131

Alignment of Microarray Data.

Francesco Cauteruccio1.   

Abstract

The aim in microarray data analysis is to discover patterns of gene expression and to identify similar genes. Simply comparing new gene sequences to known DNA sequences often does not reveal the function of a new gene; thus, more sophisticated techniques are in order. Nowadays, data mining techniques, and in particular the clustering process, play an important role in bioinformatics. To analyze vast amounts of data can be difficult; thus, a way to cluster similar data is needed. This chapter is devoted to illustrate the general data mining approach used in microarray data analysis, combining clustering, alignment and similarity, and to highlight a novel similarity measure capable of capturing hidden correlations between data.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Data analysis; Edit distance; Microarray; Multiparameterized edit distance; Sequence alignment

Mesh:

Year:  2022        PMID: 34902131     DOI: 10.1007/978-1-0716-1839-4_14

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  11 in total

Review 1.  Pattern recognition techniques in microarray data analysis: a survey.

Authors:  Faramarz Valafar
Journal:  Ann N Y Acad Sci       Date:  2002-12       Impact factor: 5.691

Review 2.  Microarray data normalization and transformation.

Authors:  John Quackenbush
Journal:  Nat Genet       Date:  2002-12       Impact factor: 38.330

3.  Gridline: automatic grid alignment in DNA microarray scans.

Authors:  Peter Bajcsy
Journal:  IEEE Trans Image Process       Date:  2004-01       Impact factor: 10.856

Review 4.  Survey of clustering algorithms.

Authors:  Rui Xu; Donald Wunsch
Journal:  IEEE Trans Neural Netw       Date:  2005-05

5.  Sequential patterns mining and gene sequence visualization to discover novelty from microarray data.

Authors:  A Sallaberry; N Pecheur; S Bringay; M Roche; M Teisseire
Journal:  J Biomed Inform       Date:  2011-04-16       Impact factor: 6.317

6.  An automated string-based approach to extracting and characterizing White Matter fiber-bundles.

Authors:  Francesco Cauteruccio; Claudio Stamile; Giorgio Terracina; Domenico Ursino; Dominique Sappey-Marinier
Journal:  Comput Biol Med       Date:  2016-07-30       Impact factor: 4.589

7.  Automatic detection of childhood absence epilepsy seizures: toward a monitoring device.

Authors:  Jonas Duun-Henriksen; Rasmus E Madsen; Line S Remvig; Carsten E Thomsen; Helge B D Sorensen; Troels W Kjaer
Journal:  Pediatr Neurol       Date:  2012-05       Impact factor: 3.372

8.  QuickBundles, a Method for Tractography Simplification.

Authors:  Eleftherios Garyfallidis; Matthew Brett; Marta Morgado Correia; Guy B Williams; Ian Nimmo-Smith
Journal:  Front Neurosci       Date:  2012-12-11       Impact factor: 4.677

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