Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms

Matrix Computations

Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505

Comprehensive Identification of Cell Cycle–regulated Genes of the YeastSaccharomyces cerevisiaeby Microarray Hybridization

Spellman, P. T., Sherlock, G. J., Zhang, M. Q., Iyer, V. R., Anders, K. R., Eisen, M. B., Brown, P. O., Botstein, D., & Futcher, B. (1998) · Molecular Biology of the Cell · doi:10.1091/mbc.9.12.3273 · Cited by 4,724

Systematic determination of genetic network architecture

Tavazoie, S., Hughes, J. D., Campbell, M. J., Cho, R. J., & Church, G. M. (1999) · Nature Genetics · doi:10.1038/10343 · Cited by 2,509

Singular value decomposition for genome-wide expression data processing and modeling

Alter, O., Brown, P. O., & Botstein, D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.18.10101 · Cited by 1,989

Identification of Genes Periodically Expressed in the Human Cell Cycle and Their Expression in Tumors

Whitfield, M. L., Sherlock, G., Saldanha, A. J., Murray, J. I., Ball, C. A., Alexander, K. E., Matese, J. C., Perou, C. M., Hurt, M. M., Brown, P. O., et al. (2002) · Molecular Biology of the Cell · doi:10.1091/mbc.02-02-0030 · Cited by 1,527

Large-scale temporal gene expression mapping of central nervous system development

Wen, X., Fuhrman, S., Michaels, G. S., Carr, D. B., Smith, S. V., Barker, J. L., & Somogyi, R. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.1.334 · Cited by 645

Molecular characterisation of soft tissue tumours: a gene expression study

Nielsen, T. O., West, R. B., Linn, S. C., Alter, O., Knowling, M. A., OʼConnell, J. X., Zhu, S., Fero, M., Sherlock, G. J., Pollack, J. R., et al. (2002) · The Lancet · doi:10.1016/s0140-6736(02)08270-3 · Cited by 574

Towards a Generalized Singular Value Decomposition

Paige, C. C., & Saunders, M. A. (1981) · SIAM Journal on Numerical Analysis · doi:10.1137/0718026 · Cited by 555

The Stanford Microarray Database

Sherlock, G. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.152 · Cited by 528

Fundamental patterns underlying gene expression profiles: Simplicity from complexity

Holter, N. S., Mitra, M., Maritan, A., Cieplak, M., Banavar, J. R., & Fedoroff, N. V. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.150242097 · Cited by 475

Gene Selection Strategies in Microarray Expression Data: Applications to Case-Control Studies

Stolovitzky, G. A. (2007) · Springer eBooks · doi:10.1007/978-0-387-33532-2_30 · Cited by 5

Hierarchical Dirichlet Process-Based Models For Discovery of Cross-species Mammalian Gene Expression

Gerber, G. K., Dowell, R. D., Jaakkola, T., & Gifford, D. K. (2007) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 5

Time Series Analysis Using the Concept of Adaptable Threshold Similarity

Aßfalg, J., Kriegel, H.-P., Kröger, P., Kunath, P., Pryakhin, A., & Renz, M. (2006) · International Conference on Scientific and Statistical Database Management · doi:10.1109/ssdbm.2006.53 · Cited by 5

Efficient filtration of sequence similarity search through singular value decomposition

Aghili, S., Sahin, O. D., Agrawal, D., & Abbadi, A. E. (2004) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2004.1317371 · Cited by 5

Probabilistic analysis of the human transcriptome with side informationPreprint

Lahti, L. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1102.5509 · Cited by 5

Erratum to: A Nonlinear Generalization of Singular Value Decomposition and Its Applications to Mathematical Modeling and Chaotic Cryptanalysis

Vaidya, P. G., S, S. A. P., & Nagaraj, N. (2010) · Acta Applicandae Mathematicae · doi:10.1007/s10440-010-9565-7 · Cited by 5

Application of Singular Value Decomposition

Niknejad, A. (2005) · Cited by 5

An overview of recent developments in genomics and associated statistical methods

Eter, B. Y. P., Ickel, J. B., Ames, J., Rown, B. B., & Uang, H. A. H. (2015) · Cited by 4

Approximation Algorithms for Biclustering Problems

Wang, L., Lin, Y., & Liu, X. (2008) · SIAM Journal on Computing · doi:10.1137/060664112 · Cited by 4

Multilinear Models, Iterative Methods

Tomasi, G., Acar, E., & Bro, R. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-409547-2.14609-8 · Cited by 4

DataRemix: a universal data transformation for optimal inference from gene expression datasets

Mao, W., Rahimikollu, J., Hausler, R. M., & Chikina, M. D. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa745 · Cited by 4

Functional, structural, and phenotypic data fusion to predict developmental scores of pre-school children based on Canonical Polyadic Decomposition

Dron, N., Navarro-Cáceres, M., Chin, R., & Escudero, J. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102889 · Cited by 4

Interval-Focused Similarity Search in Time Series Databases

Aßfalg, J., Kriegel, H., Kröger, P., Kunath, P., Pryakhin, A., & Renz, M. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-71703-4_50 · Cited by 4

Component- and Factor-Based Models for Data Fusion in the Behavioral Sciences

Mechelen, I. V., & Ceulemans, E. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2442652 · Cited by 4

Improving Missing Value Imputation in Microarray Data by Using Gene Regulatory Information

Xiang, Q., & Dai, X. (2008) · International Conference on Bioinformatics and Biomedical Engineering · doi:10.1109/icbbe.2008.83 · Cited by 4

Matrix factorization reveals aging-specific co-expression gene modules in the fat and muscle tissues in nonhuman primates

Wang, Y., Zhao, W., & Zhou, X. (2016) · Scientific Reports · doi:10.1038/srep34335 · Cited by 4

Using Wavelets and Spectral Methods to Study Patterns in Image-Classification DatasetsPreprint

Yousefzadeh, R., & Huang, F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.09879 · Cited by 6

Randomized Algorithms for Computing the Generalized Tensor SVD Based on the Tensor Product

Ahmadi‐Asl, S., Rezaeian, N., & Ugwu, U. O. (2025) · Communications on Applied Mathematics and Computation · doi:10.1007/s42967-024-00461-3 · Cited by 3

Characterizing GSVD by Singular Value Expansion of Linear Operators and Its Computation

Li, H. (2025) · SIAM Journal on Matrix Analysis and Applications · doi:10.1137/24m1651150 · Cited by 3

A Grassmannian Minimum Enclosing Ball Approach for Common Subspace Extraction

Renard, E., Gallivan, K. A., & Absil, P.-A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-93764-9_7 · Cited by 3

Livebearing or egg-laying mammals: 27 decisive nucleotides of FAM168

Pramanik, S., Kutzner, A., & Heese, K. (2017) · BioScience Trends · doi:10.5582/bst.2016.01252 · Cited by 3

A Clinical Metabolomics Strategy to Discover New Biomarkers in Complex Disease: An Overview

Baumgärtner, C. (2013) · Biomedizinische Technik/Biomedical Engineering · doi:10.1515/bmt-2013-4305 · Cited by 3

Molecular Diagnosis of Lymphoma: Outcome Prediction by Gene Expression Profiling in Diffuse Large B-Cell Lymphoma

Last, K., Debarnardi, S., & Lister, T. A. (2005) · Humana Press eBooks · doi:10.1385/1-59259-936-2:015 · Cited by 3

Handling Big Data in Precision Medicine

Lemus, E. H., Enríquez, J. E., & García-Herrera, R. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809411-2.00014-3 · Cited by 3

Decomposition of Variation of Mixed Variables by a Latent Mixed Gaussian Copula Model

Liu, Y., Darville, T. L., Zheng, X., & Li, Q. (2022) · Biometrics · doi:10.1111/biom.13660 · Cited by 4

Identifying Conserved and Divergent Transcriptional

Li, H., & Zhan, M. (2009) · Journal of Proteomics & Bioinformatics · doi:10.4172/jpb.1000068 · Cited by 3

An extension of analytic solutions of a class of constrained matrix minimization problems

Xu, W., Lü, Y., & Zhu, L. (2020) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2019.112671 · Cited by 3

Principal Component Analysis for ExperimentsPreprint

Konishi, T. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1212.6006 · Cited by 3

Enhanced visualization of time series through higher Fourier harmonics

Li, Z., Zhang, A., & Ramanathan, M. K. (2003) · Cited by 3

Robust methods for locating multiple dense regions in complex datasets

Gupta, G. (2006) · Texas ScholarWorks (Texas Digital Library) · Cited by 3

A novel stepwise analysis procedure of genome‐wide expression profiles identifies transcript signatures of thiamine genes as classifiers of mitochondrial mutants

Eijssen, L., Lindsey, P. J., Peeters, R., Westra, R. L., van Eijsden, R. G. E., Bolotin‐Fukuhara, M., Smeets, H. J. M., & VLIETINCK, R. F. (2007) · Yeast · doi:10.1002/yea.1573 · Cited by 3

Genomics and Proteomics: A Signal Processor's Tour

Vaidyanathan, P. P. (2004) · doi:10.21236/ada427792 · Cited by 3

A New Matrix Maximization Model for Computing Ratios of Generalized Singular Values from High-Order GSVD

Xu, W., & Ng, M. K. (2023) · Journal of Scientific Computing · doi:10.1007/s10915-022-02071-8 · Cited by 2

A Review on Solving Sylvester-Type Equations

Wang, Q.-W., & Gao, J. (2026) · Symmetry · doi:10.3390/sym18060984 · Cited by 2

Comparative Analysis of NOMA and OMA Schemes: GSVD-based NOMA Systems and the Role of Mobile Edge Computing

Dursun, Y. (2023) · Journal of Telecommunications and Information Technology · doi:10.26636/jtit.2023.3.1354 · Cited by 2

AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer

Ponnapalli, S. P., Miron, P. L., Miskimen, K. L. S., Waite, K. A., Sosonkina, N., Coppens, S. E., Bryan, A. C., Kiernan, E. P., Yang, H., Bowen, J., et al. (2023) · International Conference for High Performance Computing, Networking, Storage and Analysis (SC) · doi:10.1145/3624062.3624078 · Cited by 2

Approximation Algorithms for Bi-clustering Problems

Wang, L., Lin, Y., & Liu, X. (2006) · Lecture notes in computer science · doi:10.1007/11851561_29 · Cited by 2

Vector Space Information Retrieval Techniques for Bioinformatics Data Mining

Sakk, E., & Iyanuoluwa, E. (2011) · InTech eBooks · doi:10.5772/18905 · Cited by 2

Cross-Species Comparison Using Expression Data

Lelandais, G., & Crom, S. L. (2007) · Humana Press eBooks · doi:10.1007/978-1-59745-531-2_8 · Cited by 2

Unsupervised analysis of leukemia and normal hematopoiesis by joint clustering of gene expression data

Badea, L. (2012) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2012.6399647 · Cited by 2

Applied problems of the identification and regression analysis in stochastic structures with multimodal properties

Kulikov, V. B., & Kulikov, A. (2016) · ITM Web of Conferences · doi:10.1051/itmconf/20160603008 · Cited by 2

Biomarker discovery in multi-omics datasets using tensor decompositions; A comprehensive review

Koleini, F., Gemperline, P. J., & Tabrizi, N. (2023) · EPiC series in computing · doi:10.29007/8xdb · Cited by 2

Gene hunting with forests for multigroup time course data

Papana, A., & Ishwaran, H. (2009) · Statistics & Probability Letters · doi:10.1016/j.spl.2009.01.003 · Cited by 2

Analytic solutions of a class of extended constrained matrix maximization problems

Xu, W., Ge, Z.-H., & Zhu, L. (2020) · Applied Mathematics and Computation · doi:10.1016/j.amc.2019.124989 · Cited by 2

X-Module: A novel fusion measure to associate co-expressed gene modules from condition-specific expression profiles

Kakati, T., Bhattacharyya, D. K., & Kalita, J. K. (2020) · Journal of Biosciences · doi:10.1007/s12038-020-0007-z · Cited by 2

Bioinformatic analysis of epithelial:mesenchymal crosstalk during mouse gut development and patterning

Li, X. (2009) · Deep Blue (University of Michigan) · Cited by 2

DNA meets the SVDPreprint

Grindrod, P., Higham, D. J., Kalna, G., Spence, A. M., Stoyanov, Z., & Vass, J. K. (2008) · Cited by 2

SEMI-SUPERVISED THRESHOLD QUERIES ON PHARMACOGENOMICS TIME SEQUENCES

Aßfalg, J., Kriegel, H.-P., Kröger, P., Kunath, P., Pryakhin, A., & Renz, M. (2005) · Asia-Pacific Bioinformatics Conference · doi:10.1142/9781860947292_0034 · Cited by 2

Comparative analysis of gene expression and DNA copy number data for pancreatic and breast cancers using an orthogonal decomposition

Berger, J. A., Hautaniemi, S., & Mitra, S. K. (2004) · doi:10.1109/csb.2004.54 · Cited by 2

A contour integral-based algorithm for computing generalized singular values

Liu, Y., Shan, X., & Shao, M. (2026) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2026.117583 · Cited by 1

A differential biclustering algorithm for comparative analysis of gene expression

Tchagang, A., Tewfik, A. H., Skubitz, A. P. N., & Skubitz, K. M. (2006) · Cited by 1

Predictive model building for microarray data using generalized partial least squares model

Wu, B., & August, R. (2006) · Cited by 1

Maximum Likelihood Estimation of GEVD: Applications in Bioinformatics

Thomas, M., Daemen, A., & Moor, B. D. (2014) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2014.2304292 · Cited by 1

Mining Multimodal Big Data

Roy, S., & Berry, M. W. (2018) · Advances in data mining and database management book series · doi:10.4018/978-1-5225-3142-5.ch023 · Cited by 1

Parallel reduction of four matrices to condensed form for a generalized matrix eigenvalue algorithm

Bosner, N. (2020) · Numerical Algorithms · doi:10.1007/s11075-020-00883-z · Cited by 1

JEBIN: analyzing gene co-expressions across multiple datasets by joint network embedding

Wu, G., Li, X., Guo, W., Zheng, W., Hu, T., Shan, Y., & Gu, J. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab603 · Cited by 1

Generalized singular value decomposition in multidimensional condition monitoring of systems

Cempel, C. (2008) · Diagnostyka · Cited by 1

Article Commentary: Microarray Data Analysis of Gene Expression Evolution

Lin, H. (2009) · Gene Regulation and Systems Biology · doi:10.4137/grsb.s2997 · Cited by 1

Genomics and Microarrays

Sarwal, M., & Alemi, F. (2005) · Elsevier eBooks · doi:10.1016/b978-012455900-4/50322-6 · Cited by 1

Tensor generalizations of the singular value decomposition for integrative analysis of large-scale molecular biological data

Omberg, L. G. (2007) · Texas ScholarWorks (Texas Digital Library) · Cited by 1

Tensors in Power System Computation I: Distributed Computation for Optimal Power Flow, DC OPFPreprint

Oh, H. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.06735 · Cited by 1

Higher order analysis of gene correlations by tensor decompositionPreprint

Yahyanejad, F. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/579276 · Cited by 1

Orthogonal Shared Basis Factorization: Cross-species gene expression analysis using a common expression subspacePreprint

Thomas, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.26.505467 · Cited by 1

Redução dimensional de dados de alta dimensão e poucas amostras usando Projection Pursuit

Llerena, S. E. (2013) · doi:10.11606/t.18.2013.tde-10102013-150240

Inferring Transcriptional Regulatory Network

Zhan, M. (2010) · Systems biology · doi:10.1007/978-1-4419-5797-9_9

A mean pattern model for integrative study — Integrative self-organizing map

Yang, Z., Al-Watban, A., & Yang, Z. R. (2014) · International Conference on Biomedical Engineering and Informatics (BMEI) · doi:10.1109/bmei.2014.7002853

An Effective Conversion Algorithm of Arithmetic Expression from Infix Form to Prefix Form

Wang, T., Tan, H. X., & Liu, R. R. (2011) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.58-60.1350

Statistical methods for biomarker discovery in proteomics

Tan, C. S. (2008) · Figshare

Analysis of High Throughput Genomic Datasets Across Species

Zinman, G. (2012)

Lossless Microarray Image Compression by Hardware Array CompactorPreprint

Banaei, A., Samavi, S., & Esfahani, E. N. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2303.10489

Structure and responsiveness

Grindrod, P. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.003.0004

Similarity, graphs and networks, random matrices, and SVD

Grindrod, P. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.003.0002 · Cited by 1

Dynamically evolving networks

Grindrod, P. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.003.0003

Multiple hypothesis testing over live data

Peter Grindrod, C. B. E. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.003.0006

IFGFA: Identification of featured genes from genomic data using factor analysis

Fu, C. H., Deng, S., Wu, J., Wu, X. Q., Fu, Z. H., & Yu, Z. (2016) · Genetics and Molecular Research · doi:10.4238/gmr.15038803

Customer journeys and Markov chains

Grindrod, P. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.003.0008

Clustering and unsupervised classification

Peter Grindrod, C. B. E. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.003.0005

A simultaneous decomposition of four real quaternion matrices encompassing $η$-Hermicity and its applicationsPreprint

He, Z., & Wang, Q. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1702.00551

Application of singular value decomposition to DNA microarray.

Niknejad, A. (2025) · Figshare

New Formulation and Computation for Generalized Singular Values of Grassman Matrix PairPreprint

Xu, W., Ng, M. K., & Bai, Z. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.02180

SOLAR: Fusing Node Embeddings and Attributes into an Arbitrary Space

Wang, Z., Cui, J., Chen, Y., & Hu, C. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59419-0_27

Fusing Node Embeddings and Incomplete Attributes by Complement‐Based Concatenation

Wang, Z., Wu, Y., Bao, Y., Yu, J. S., & Wang, X. (2021) · Wireless Communications and Mobile Computing · doi:10.1155/2021/6654349

行列・テンソル分解によるヘテロバイオデータ統合解析の数理 ―第1回 行列分解―

露崎弘毅 (2021) · doi:10.11234/jsbibr.2021.1

Analytical solutions of a class of matrix function optimization problems with unitary constraints

Shen, W., Ping, S., Ge, Z., & Xu, W. (2021) · Applied Mathematics Letters · doi:10.1016/j.aml.2021.107601

Current awareness on comparative and functional genomics

(2003) · Comparative and Functional Genomics · doi:10.1002/cfg.230

References

Chen, L., Wang, R.-S., & Zhang, X.-S. (2009) · Wiley eBooks · doi:10.1002/9780470488065.refs

Adaptive forecasting

Grindrod, P. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.003.0007

Comparative analysis of gene expression and DNA copy number data for pancreatic and breast cancers using an orthogonal decomposition

Berger, J. A., Hautaniemi, S., & Mitra, S. K. (2004) · IEEE Computational Systems Bioinformatics Conference (CSB) · doi:10.1109/csb.2004.1332506

Introduction

Grindrod, P. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.003.0001

Faculty Opinions recommendation of Data integration in the era of omics: current and future challenges.

Auffray, C., & Meulder, B. D. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.725955089.793561298

Faculty Opinions recommendation of Gene co-regulation is highly conserved in the evolution of eukaryotes and prokaryotes.

Mushegian, A. R. (2004) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.1021486.245630

13 Functional Genomics to Characterize Opportunistic Pathogens

Heinekamp, T., Valiante, V., Koester-Eiserfunke, N., & Brakhage, A. A. (2014) · Springer eBooks · doi:10.1007/978-3-642-45218-5_13

Copyright Page

(2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.002.0003

Preface

(2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.002.0005

Dedication

(2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.002.0004

Uncertainty, Probability and Reasoning

(2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.005.0001

Solutions to Exercises

(2014) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780198725091.002.0007

Coupled Matrix Tensor Factorization via a Semi-Algebraic Solution Based on Simultaneous Matrix Diagonalization (SECSI -CMTF)

Manina, A., Grasis, M. J., de Almeida, A. L. F., & Haardt, M. (2023) · IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing · doi:10.1109/camsap58249.2023.10403496

Double-variable trace maximization for extreme generalized singular quartets of a matrix pair: A geometric method

Xu, W., & Bai, Z. (2024) · Mathematics of Computation · doi:10.1090/mcom/3936

Fast Randomized Algorithms for Low-Rank Matrix Approximations for Generalized Singular Value Decomposition with Applications

Xu, W., Shen, W., Li, W., Gao, W., & Li, Y. (2026) · Journal of Scientific Computing · doi:10.1007/s10915-026-03231-w

Processing and Modeling Genome-Wide Expression Data Using Singular Value Decomposition

Alter, O., Brown, P. O., & Botstein, D. (2001)

Singular value decomposition for genome-wide expression data processing and modeling

Alter, O., Brown, P. O., & Botstein, D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.18.10101 · Cited by 1,989

A Higher-Order Generalized Singular Value Decomposition for Comparison of Global mRNA Expression from Multiple Organisms

Ponnapalli, S. P., Saunders, M. A., Loan, C. F. V., & Alter, O. (2011) · PLoS ONE · doi:10.1371/journal.pone.0028072 · Cited by 102

SVD (singular value decomposition)

Yap, K. C., Acta Inc, Wathugala, G. W., Hasselman, T. K., Acta Inc, Keng, D., Yap, C., & Fidelity, H. H. (2008) · Springer eBooks · doi:10.1007/978-1-4020-6754-9_16446 · Cited by 2

Combining transcriptional datasets using the generalized singular value decomposition

SCHREIBER, A. W., Shirley, N. J., Burton, R. A., & Fincher, G. B. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-335 · Cited by 14