Journal ArticleDOI
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Todd R. Golub,Todd R. Golub,Donna K. Slonim,Pablo Tamayo,Christine Huard,Michelle Gaasenbeek,Jill P. Mesirov,Hilary A. Coller,Mignon L. Loh,James R. Downing,Michael A. Caligiuri,Clara D. Bloomfield,Eric S. Lander +12 more
TLDR
A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.Abstract:
Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumors to known classes (class prediction). Here, a generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case. A class discovery procedure automatically discovered the distinction between acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) without previous knowledge of these classes. An automatically derived class predictor was able to determine the class of new leukemia cases. The results demonstrate the feasibility of cancer classification based solely on gene expression monitoring and suggest a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.read more
Citations
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Journal ArticleDOI
Regularization and variable selection via the elastic net
Hui Zou,Trevor Hastie +1 more
TL;DR: It is shown that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation, and an algorithm called LARS‐EN is proposed for computing elastic net regularization paths efficiently, much like algorithm LARS does for the lamba.
Journal ArticleDOI
Molecular portraits of human breast tumours
Charles M. Perou,Therese Sørlie,Michael B. Eisen,Matt van de Rijn,Stefanie S. Jeffrey,Christian A. Rees,Jonathan R. Pollack,Douglas T. Ross,Hilde Johnsen,Lars A. Akslen,Øystein Fluge,Alexander Pergamenschikov,Cheryl A. Williams,Shirley Zhu,Per Eystein Lønning,Anne Lise Børresen-Dale,Patrick O. Brown,David Botstein +17 more
TL;DR: Variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals were characterized using complementary DNA microarrays representing 8,102 human genes, providing a distinctive molecular portrait of each tumour.
Journal ArticleDOI
An introduction to variable and feature selection
Isabelle Guyon,André Elisseeff +1 more
TL;DR: The contributions of this special issue cover a wide range of aspects of variable selection: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.
Journal ArticleDOI
Regularization Paths for Generalized Linear Models via Coordinate Descent
TL;DR: In comparative timings, the new algorithms are considerably faster than competing methods and can handle large problems and can also deal efficiently with sparse features.
Journal ArticleDOI
Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications
Therese Sørlie,Charles M. Perou,Robert Tibshirani,Turid Aas,Stephanie Geisler,Hilde Johnsen,Trevor Hastie,Michael B. Eisen,Matt van de Rijn,Stefanie S. Jeffrey,T. Thorsen,Hanne Quist,John C. Matese,Patrick O. Brown,David Botstein,Per Eystein Lønning,Anne Lise Børresen-Dale +16 more
TL;DR: Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
References
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Journal ArticleDOI
Comprehensive Identification of Cell Cycle–regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization
Paul T. Spellman,Gavin Sherlock,Gavin Sherlock,Michael Q. Zhang,Vishwanath R. Iyer,Kirk R. Anders,Michael B. Eisen,Patrick O. Brown,Patrick O. Brown,David Botstein,Bruce Futcher +10 more
TL;DR: A comprehensive catalog of yeast genes whose transcript levels vary periodically within the cell cycle is created, and it is found that the mRNA levels of more than half of these 800 genes respond to one or both of these cyclins.
PatentDOI
Expression monitoring by hybridization to high density oligonucleotide arrays
TL;DR: In this article, the authors proposed a method for monitoring the expression levels of a multiplicity of genes by hybridizing a nucleic acid sample to a high density array of oligonucleotide probes and quantifying the hybridized nucleic acids in the array.
Journal ArticleDOI
Tissue microarrays for high-throughput molecular profiling of tumor specimens
Juha Kononen,Lukas Bubendorf,Anne Kallioniemi,Maarit Bärlund,Peter Schraml,S Leighton,Joachim Torhorst,Michael J. Mihatsch,Guido Sauter,Olli Kallioniemi +9 more
TL;DR: In this paper, an array-based high-throughput technique that facilitates gene expression and copy number surveys of very large numbers of tumors is presented. But, it is limited to a single tumor tissue microarray.
Journal ArticleDOI
Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation
Pablo Tamayo,Donna K. Slonim,Jill P. Mesirov,Qing Zhu,Sutisak Kitareewan,Ethan Dmitrovsky,Eric S. Lander,Todd R. Golub,Todd R. Golub +8 more
TL;DR: In this article, the application of self-organizing maps, a type of mathematical cluster analysis that is particularly well suited for recognizing and classifying features in complex, multidi-mensional data, is described.
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