SPACE: an algorithm to predict and quantify alternatively spliced isoforms using microarrays

Exon and exon+junction microarrays are promising tools for studying alternative splicing. Current analytical tools applied to these arrays lack two relevant features: the ability to predict unknown spliced forms and the ability to quantify the concentration of known and unknown isoforms. SPACE is an...

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Published inGenome biology Vol. 9; no. 2; pp. R46 - 1908
Main Authors Anton, Miguel A, Gorostiaga, Dorleta, Guruceaga, Elizabeth, Segura, Victor, Carmona-Saez, Pedro, Pascual-Montano, Alberto, Pio, Ruben, Montuenga, Luis M, Rubio, Angel
Format Journal Article
LanguageEnglish
Published London BioMed Central 29.02.2008
Subjects
Online AccessGet full text
ISSN1474-760X
1465-6906
1474-7596
1474-760X
1465-6914
DOI10.1186/gb-2008-9-2-r46

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Abstract Exon and exon+junction microarrays are promising tools for studying alternative splicing. Current analytical tools applied to these arrays lack two relevant features: the ability to predict unknown spliced forms and the ability to quantify the concentration of known and unknown isoforms. SPACE is an algorithm that has been developed to (1) estimate the number of different transcripts expressed under several conditions, (2) predict the precursor mRNA splicing structure and (3) quantify the transcript concentrations including unknown forms. The results presented here show its robustness and accuracy for real and simulated data.
AbstractList SPACE is an algorithm developed to predict and quantify the pre-mRNA splicing structure of transcripts using exon and ‘exon plus junction’ microarray data. Exon and exon+junction microarrays are promising tools for studying alternative splicing. Current analytical tools applied to these arrays lack two relevant features: the ability to predict unknown spliced forms and the ability to quantify the concentration of known and unknown isoforms. SPACE is an algorithm that has been developed to (1) estimate the number of different transcripts expressed under several conditions, (2) predict the precursor mRNA splicing structure and (3) quantify the transcript concentrations including unknown forms. The results presented here show its robustness and accuracy for real and simulated data.
Exon and exon+junction microarrays are promising tools for studying alternative splicing. Current analytical tools applied to these arrays lack two relevant features: the ability to predict unknown spliced forms and the ability to quantify the concentration of known and unknown isoforms. SPACE is an algorithm that has been developed to (1) estimate the number of different transcripts expressed under several conditions, (2) predict the precursor mRNA splicing structure and (3) quantify the transcript concentrations including unknown forms. The results presented here show its robustness and accuracy for real and simulated data.Exon and exon+junction microarrays are promising tools for studying alternative splicing. Current analytical tools applied to these arrays lack two relevant features: the ability to predict unknown spliced forms and the ability to quantify the concentration of known and unknown isoforms. SPACE is an algorithm that has been developed to (1) estimate the number of different transcripts expressed under several conditions, (2) predict the precursor mRNA splicing structure and (3) quantify the transcript concentrations including unknown forms. The results presented here show its robustness and accuracy for real and simulated data.
Exon and exon+junction microarrays are promising tools for studying alternative splicing. Current analytical tools applied to these arrays lack two relevant features: the ability to predict unknown spliced forms and the ability to quantify the concentration of known and unknown isoforms. SPACE is an algorithm that has been developed to (1) estimate the number of different transcripts expressed under several conditions, (2) predict the precursor mRNA splicing structure and (3) quantify the transcript concentrations including unknown forms. The results presented here show its robustness and accuracy for real and simulated data.
ArticleNumber R46
Author Guruceaga, Elizabeth
Pio, Ruben
Segura, Victor
Montuenga, Luis M
Pascual-Montano, Alberto
Anton, Miguel A
Rubio, Angel
Carmona-Saez, Pedro
Gorostiaga, Dorleta
AuthorAffiliation 1 CEIT and TECNUN, University of Navarra, San Sebastián, Spain
5 Department of Biochemistry, University of Navarra, Pamplona, Spain
4 Center for Applied Medical Research, University of Navarra, Pamplona, Spain
3 Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid 28040, Spain
2 Integromics SL, Madrid, Spain
6 Department of Histology and Pathology, University of Navarra, Pamplona, Spain
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Keywords Additional Data File
Reverse Transcription Polymerase Chain Reaction
Exon Cassette
Multiplicative Noise
Probe Expression
Language English
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Snippet Exon and exon+junction microarrays are promising tools for studying alternative splicing. Current analytical tools applied to these arrays lack two relevant...
SPACE is an algorithm developed to predict and quantify the pre-mRNA splicing structure of transcripts using exon and 'exon plus junction' microarray data....
SPACE is an algorithm developed to predict and quantify the pre-mRNA splicing structure of transcripts using exon and ‘exon plus junction’ microarray data....
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StartPage R46
SubjectTerms Algorithms
Alternative Splicing
Animal Genetics and Genomics
Animals
Bioinformatics
Biomedical and Life Sciences
Computational Biology - methods
Computer Simulation
Evolutionary Biology
Exons
Human Genetics
Humans
Life Sciences
messenger RNA
Method
microarray technology
Microbial Genetics and Genomics
Oligonucleotide Array Sequence Analysis
Plant Genetics and Genomics
Protein Isoforms - genetics
RNA precursors
Transcription, Genetic
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Title SPACE: an algorithm to predict and quantify alternatively spliced isoforms using microarrays
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