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Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms
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We describe a comparative mathematical framework for two genome-scale expression data sets. This framework formulates expression as superposition of the effects of regulatory programs, biological processes, and experimental artifacts common to both data sets, as well as those that are exclusive to one data set or the other, by using generalized singular value decomposition. This framework enables comparative reconstruction and classification of the genes and arrays of both data sets. We illustrate this framework with a comparison of yeast and human cell-cycle expression data sets.
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“Generalized Single Value Decomposition (GSVD) is a unique type of differential co-expression analysis that relies on spectral decomposition to identify modules of co-regulated genes.”
From Gene co-expression analysis for functional classification and gene–disease predictions (2017) · cites this paper as [104]
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Metadata
- Authors
- Alter, O., Brown, P. O., & Botstein, D.
- Affiliations
- Stanford University (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2003-03-11
- Volume
- 100
- Issue
- 6
- Pages
- 3351-3356
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC152296
- OpenAlex
- W2129256542
- Cited by
- 304
- References
- 14
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 2 · 2023: 6 · 2022: 5 · 2021: 8 · 2020: 15 · 2019: 13 · 2018: 9 · 2017: 9 · 2016: 16 · 2015: 10 · 2014: 29 · 2013: 13 · 2012: 8
- FWCI
- 7.58
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Human Genome Research Institute (5 K01 HG00038-01, K01HG000038)
- National Cancer Institute (CA85129, CA 77097, R01CA077097, U01CA085129)
- National Institute of General Medical Sciences (GM46406, R37GM046406, R01GM046406)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- generalized singular value decomposition, regulatory programs, biological processes, experimental artifacts, gene classification, yeast cell cycle, cross-species comparison
- MeSH terms
- Cell Cycle, Data Interpretation, Statistical, Genes, Fungal, Humans, Pheromones, RNA, Fungal, RNA, Messenger, Saccharomyces cerevisiae, Stress, Physiological, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Genomics, Databases, Genetic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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