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 in | Genome biology Vol. 9; no. 2; pp. R46 - 1908 | 
|---|---|
| Main Authors | , , , , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        London
          BioMed Central
    
        29.02.2008
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 1474-760X 1465-6906 1474-7596 1474-760X 1465-6914  | 
| DOI | 10.1186/gb-2008-9-2-r46 | 
Cover
| 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. | 
    
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| 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  | 
    
| AuthorAffiliation_xml | – name: 2 Integromics SL, Madrid, Spain – name: 3 Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, Madrid 28040, Spain – name: 4 Center for Applied Medical Research, University of Navarra, Pamplona, Spain – name: 6 Department of Histology and Pathology, University of Navarra, Pamplona, Spain – name: 5 Department of Biochemistry, University of Navarra, Pamplona, Spain – name: 1 CEIT and TECNUN, University of Navarra, San Sebastián, Spain  | 
    
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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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| 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 | 
    
| URI | https://link.springer.com/article/10.1186/gb-2008-9-2-r46 https://www.ncbi.nlm.nih.gov/pubmed/18312629 https://www.proquest.com/docview/2000164798 https://www.proquest.com/docview/20354060 https://www.proquest.com/docview/69136737 https://pubmed.ncbi.nlm.nih.gov/PMC2374713 https://genomebiology.biomedcentral.com/counter/pdf/10.1186/gb-2008-9-2-r46  | 
    
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