'Informative genes' diaporamas de présentation

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Mining Phenotype Structures

Mining Phenotype Structures

Mining Phenotype Structures. Chun Tang and Aidong Zhang Bioinformatics Journal, 20(6):829-838, 2004. Microarray Data Analysis. Analysis from two angles sample as object, gene as attribute gene as object, sample/condition as attribute. Supervised Analysis.

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621 views • 55 slides
Computational Biology Group

Computational Biology Group

Computational Biology Group. Class prediction of tumor samples Supervised Clustering Detection of Subgroups in a Class. Training Set. Test Sample. Class prediction : Assign unknown samples to already known classes.

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445 views • 34 slides
Classifying Lymphoma Dataset Using Multi-class Support Vector Machines

Classifying Lymphoma Dataset Using Multi-class Support Vector Machines

Classifying Lymphoma Dataset Using Multi-class Support Vector Machines. INFS-795 Advanced Data Mining Prof. Domeniconi Presented by Hong Chai. Agenda. (1) Lymphoma Dataset Description (2) Data Preprocessing - Formatting - Dealing with Missing Values

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468 views • 30 slides
Combining heterogeneous data to reverse engineer regulatory networks

Combining heterogeneous data to reverse engineer regulatory networks

Combining heterogeneous data to reverse engineer regulatory networks. Allan Tucker School of Information Systems Computing and Mathematics, Brunel University, London. UB8 3PH. Intelligent Data Analysis. IDA attempts to deal with data explosion to discover patterns and knowledge from data

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397 views • 30 slides
Journal Club Meeting Sept 13, 2010 Tejaswini Narayanan

Journal Club Meeting Sept 13, 2010 Tejaswini Narayanan

Journal Club Meeting Sept 13, 2010 Tejaswini Narayanan. Question addressed. Gene expression profiling provides tremendous info to help unravel complexity cancer. Selection of the most informative genes from huge noise for cancer classification has taken importance.

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227 views • 11 slides

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