A segmental maximum a posteriori approach to genome-wide copy number profiling

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

A segmental maximum a posteriori approach to genome-wide copy number profiling. / Andersson, Robin; Bruder, Carl E G; Piotrowski, Arkadiusz; Menzel, Uwe; Nord, Helena; Sandgren, Johanna; Hvidsten, Torgeir R; Diaz de Ståhl, Teresita; Dumanski, Jan P; Komorowski, Jan.

In: Bioinformatics (Online), Vol. 24, No. 6, 15.03.2008, p. 751-8.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Andersson, R, Bruder, CEG, Piotrowski, A, Menzel, U, Nord, H, Sandgren, J, Hvidsten, TR, Diaz de Ståhl, T, Dumanski, JP & Komorowski, J 2008, 'A segmental maximum a posteriori approach to genome-wide copy number profiling', Bioinformatics (Online), vol. 24, no. 6, pp. 751-8. https://doi.org/10.1093/bioinformatics/btn003

APA

Andersson, R., Bruder, C. E. G., Piotrowski, A., Menzel, U., Nord, H., Sandgren, J., Hvidsten, T. R., Diaz de Ståhl, T., Dumanski, J. P., & Komorowski, J. (2008). A segmental maximum a posteriori approach to genome-wide copy number profiling. Bioinformatics (Online), 24(6), 751-8. https://doi.org/10.1093/bioinformatics/btn003

Vancouver

Andersson R, Bruder CEG, Piotrowski A, Menzel U, Nord H, Sandgren J et al. A segmental maximum a posteriori approach to genome-wide copy number profiling. Bioinformatics (Online). 2008 Mar 15;24(6):751-8. https://doi.org/10.1093/bioinformatics/btn003

Author

Andersson, Robin ; Bruder, Carl E G ; Piotrowski, Arkadiusz ; Menzel, Uwe ; Nord, Helena ; Sandgren, Johanna ; Hvidsten, Torgeir R ; Diaz de Ståhl, Teresita ; Dumanski, Jan P ; Komorowski, Jan. / A segmental maximum a posteriori approach to genome-wide copy number profiling. In: Bioinformatics (Online). 2008 ; Vol. 24, No. 6. pp. 751-8.

Bibtex

@article{d54ecf753a3f4459980ea757df4d0085,
title = "A segmental maximum a posteriori approach to genome-wide copy number profiling",
abstract = "Copy number profiling methods aim at assigning DNA copy numbers to chromosomal regions using measurements from microarray-based comparative genomic hybridizations. Among the proposed methods to this end, Hidden Markov Model (HMM)-based approaches seem promising since DNA copy number transitions are naturally captured in the model. Current discrete-index HMM-based approaches do not, however, take into account heterogeneous information regarding the genomic overlap between clones. Moreover, the majority of existing methods are restricted to chromosome-wise analysis.",
keywords = "Algorithms, Artificial Intelligence, Base Sequence, Chromosome Mapping, Gene Dosage, Gene Expression Profiling, Markov Chains, Molecular Sequence Data, Oligonucleotide Array Sequence Analysis, Pattern Recognition, Automated",
author = "Robin Andersson and Bruder, {Carl E G} and Arkadiusz Piotrowski and Uwe Menzel and Helena Nord and Johanna Sandgren and Hvidsten, {Torgeir R} and {Diaz de St{\aa}hl}, Teresita and Dumanski, {Jan P} and Jan Komorowski",
year = "2008",
month = mar,
day = "15",
doi = "10.1093/bioinformatics/btn003",
language = "English",
volume = "24",
pages = "751--8",
journal = "Bioinformatics (Online)",
issn = "1367-4811",
publisher = "Oxford University Press",
number = "6",

}

RIS

TY - JOUR

T1 - A segmental maximum a posteriori approach to genome-wide copy number profiling

AU - Andersson, Robin

AU - Bruder, Carl E G

AU - Piotrowski, Arkadiusz

AU - Menzel, Uwe

AU - Nord, Helena

AU - Sandgren, Johanna

AU - Hvidsten, Torgeir R

AU - Diaz de Ståhl, Teresita

AU - Dumanski, Jan P

AU - Komorowski, Jan

PY - 2008/3/15

Y1 - 2008/3/15

N2 - Copy number profiling methods aim at assigning DNA copy numbers to chromosomal regions using measurements from microarray-based comparative genomic hybridizations. Among the proposed methods to this end, Hidden Markov Model (HMM)-based approaches seem promising since DNA copy number transitions are naturally captured in the model. Current discrete-index HMM-based approaches do not, however, take into account heterogeneous information regarding the genomic overlap between clones. Moreover, the majority of existing methods are restricted to chromosome-wise analysis.

AB - Copy number profiling methods aim at assigning DNA copy numbers to chromosomal regions using measurements from microarray-based comparative genomic hybridizations. Among the proposed methods to this end, Hidden Markov Model (HMM)-based approaches seem promising since DNA copy number transitions are naturally captured in the model. Current discrete-index HMM-based approaches do not, however, take into account heterogeneous information regarding the genomic overlap between clones. Moreover, the majority of existing methods are restricted to chromosome-wise analysis.

KW - Algorithms

KW - Artificial Intelligence

KW - Base Sequence

KW - Chromosome Mapping

KW - Gene Dosage

KW - Gene Expression Profiling

KW - Markov Chains

KW - Molecular Sequence Data

KW - Oligonucleotide Array Sequence Analysis

KW - Pattern Recognition, Automated

U2 - 10.1093/bioinformatics/btn003

DO - 10.1093/bioinformatics/btn003

M3 - Journal article

C2 - 18204059

VL - 24

SP - 751

EP - 758

JO - Bioinformatics (Online)

JF - Bioinformatics (Online)

SN - 1367-4811

IS - 6

ER -

ID: 106776275