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» Gene set analysis using principal components
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TSMC
2008
126views more  TSMC 2008»
15 years 3 months ago
Information Visualization for DNA Microarray Data Analysis: A Critical Review
Graphical representation may provide effective means of making sense of the complexity and sheer volume of data produced by DNA microarray experiments that monitor the expression p...
Leishi Zhang, J. Kuljis, Xiaohui Liu
KES
2010
Springer
15 years 2 months ago
Visualization and Language Processing for Supporting Analysis across the Biomedical Literature
Finding relevant publications in the large and rapidly growing body of biomedical literature is challenging. Search queries on PubMed often return thousands of publications and it ...
Carsten Görg, Hannah J. Tipney, Karin Verspoo...
ICCV
2007
IEEE
15 years 10 months ago
Laplacian PCA and Its Applications
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
138
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NIPS
2007
15 years 5 months ago
Sparse Overcomplete Latent Variable Decomposition of Counts Data
An important problem in many fields is the analysis of counts data to extract meaningful latent components. Methods like Probabilistic Latent Semantic Analysis (PLSA) and Latent ...
Madhusudana V. S. Shashanka, Bhiksha Raj, Paris Sm...
97
Voted
RECOMB
2010
Springer
15 years 10 months ago
Hierarchical Generative Biclustering for MicroRNA Expression Analysis
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret. We bring in explicitly an indicator of which genes tie ...
José Caldas, Samuel Kaski