Robust enumeration of cell subsets from tissue expression profiles
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Ash A. Alizadeh | Aaron M. Newman | Michael R. Green | Chuong D. Hoang | A. Newman | A. Gentles | C. Liu | C. Hoang | M. Diehn | M. Green | Weiguo Feng | Yue Xu | Yue Xu
[1] Bernhard Schölkopf,et al. New Support Vector Algorithms , 2000, Neural Computation.
[2] A. E. Hoerl,et al. Ridge regression: biased estimation for nonorthogonal problems , 2000 .
[3] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[4] Aleksey A. Nakorchevskiy,et al. Expression deconvolution: A reinterpretation of DNA microarray data reveals dynamic changes in cell populations , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[5] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[6] John D. Storey,et al. Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[7] Yunqian Ma,et al. Practical selection of SVM parameters and noise estimation for SVM regression , 2004, Neural Networks.
[8] Alexander R. Abbas,et al. Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data , 2005, Genes and Immunity.
[9] G. Collins. The next generation. , 2006, Scientific American.
[10] H. Zou,et al. The doubly regularized support vector machine , 2006 .
[11] Chi-Ying F. Huang,et al. Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme , 2007, BMC Genomics.
[12] S. Wacholder,et al. Gene Expression Signature of Cigarette Smoking and Its Role in Lung Adenocarcinoma Development and Survival , 2008, PloS one.
[13] Z. Modrušan,et al. Deconvolution of Blood Microarray Data Identifies Cellular Activation Patterns in Systemic Lupus Erythematosus , 2009, PloS one.
[14] S. Teichmann,et al. A HaemAtlas: characterizing gene expression in differentiated human blood cells , 2008, Blood.
[15] Mark M. Davis,et al. Cell type–specific gene expression differences in complex tissues , 2010, Nature Methods.
[16] H. Parkinson,et al. A global map of human gene expression , 2010, Nature Biotechnology.
[17] Ramnik J. Xavier,et al. Gene enrichment profiles reveal T-cell development, differentiation, and lineage-specific transcription factors including ZBTB25 as a novel NF-AT repressor. , 2010, Blood.
[18] Jeffrey T. Lau,et al. CD40 Pathway Activation Status Predicts Response to CD40 Therapy in Diffuse Large B Cell Lymphoma , 2011, Science Translational Medicine.
[19] D. Hanahan,et al. Hallmarks of Cancer: The Next Generation , 2011, Cell.
[20] Donald Eugene. Farrar,et al. Multicollinearity in Regression Analysis; the Problem Revisited , 2011 .
[21] R. Faull,et al. Population-specific expression analysis (PSEA) reveals molecular changes in diseased brain , 2011, Nature Methods.
[22] J. Szustakowski,et al. Optimal Deconvolution of Transcriptional Profiling Data Using Quadratic Programming with Application to Complex Clinical Blood Samples , 2011, PloS one.
[23] Zhandong Liu,et al. Gene expression deconvolution in linear space , 2011, Nature Methods.
[24] Yi Zhong,et al. Digital sorting of complex tissues for cell type-specific gene expression profiles , 2013, BMC Bioinformatics.
[25] Mei Yu,et al. PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions , 2012, PLoS Comput. Biol..
[26] Ting Gong,et al. DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data , 2013, Bioinform..
[27] G. Getz,et al. Inferring tumour purity and stromal and immune cell admixture from expression data , 2013, Nature Communications.
[28] A. Palucka,et al. Neutralizing Tumor-Promoting Chronic Inflammation: A Magic Bullet? , 2013, Science.
[29] S. Shen-Orr,et al. Computational deconvolution: extracting cell type-specific information from heterogeneous samples. , 2013, Current opinion in immunology.
[30] Andrea J. Goldsmith,et al. A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays , 2013, PLoS Comput. Biol..
[31] Ash A. Alizadeh,et al. Active idiotypic vaccination versus control immunotherapy for follicular lymphoma. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[32] Kun Huang,et al. MMAD: microarray microdissection with analysis of differences is a computational tool for deconvoluting cell type-specific contributions from tissue samples , 2014, Bioinform..