1 / 10

A Report on CAMDA’01

A Report on CAMDA’01. Biointelligence Lab School of Computer Science and Engineering Seoul National University Kyu-Baek Hwang and Jeong-Ho Chang. Outline. Critical Assessment of Microarray Data Analysis Techniques 2001 Oct. 15 ~ 16 at Duke University in Durham, NC.

arissa
Download Presentation

A Report on CAMDA’01

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A Report on CAMDA’01 Biointelligence Lab School of Computer Science and Engineering Seoul National University Kyu-Baek Hwang and Jeong-Ho Chang

  2. Outline • Critical Assessment of Microarray Data Analysis Techniques 2001 • Oct. 15 ~ 16 at Duke University in Durham, NC. • Organized by Duke Bioinformatics Shared Resource. • 16 papers were presented at the conference including 12 oral presentations. • Vendor fair (Silicon Genetics, Packard BioScience, SPSS Science, and Stratagene BioCrest) • Data Set • Rosetta compendium on the yeast (4) • NCI60 cell lines data set on the human cancer (11) • 1 (?)

  3. Oct. 15 (1/4) • Keynote (R. Stoughton, Rosetta InPharmatics) • “Lessons learned” from researches on microarray data analysis • Error model hierarchy • Single spot (pixel intensities, unbiased control) • Single transcript (reproducibility) • Array repeats (incorporation) • Large data sets (pattern matching  no free lunch) • Distance metric  the goal • Biclustering of genes and experiments • Find some small block in a dendro matrix • Null hypothesis problem • Automated annotation (PubMed + Unigene, Swiss Prot, etc.) • Inkjet oligo (25,000 oligos / 1  3 inches, sensitive 60 mers)

  4. Oct. 15 (2/4) • Keynote (cont’d) • Standard Dataset Project (SDS) by Dec., 2001. • 200 arrays • ~ 2,000 genes  5 exons  2 probes (experimentally confirmed for differential expression) • Data, clusters, literature DB  (annotating engine) annotated clusters • Application of Bayesian Decomposition to Gene Expression Analysis of Deletion Mutation Data • Matrix decomposition by MCMC simulation (Rosetta data) • Clustering based on the multiple cluster membership

  5. Oct. 15 (3/4) • Using Functional Genomic Units to Corroborate User Experiments with the Rosetta Compendium • Functional genomic units  ICA or latent variables • Published data + own experimental data • Biologically-Driven Clustering of Microarray Data: Applications to the NCI60 Data Set • Important genes for cancer and chromosomal abnormalities • UniGene  locus link  gene ontology • Why (biological process), what (function), where (cellular component) • Clustering based on genes in one chromosome (functional category)

  6. Oct. 15 (4/4) • Extracting Global Structure from Gene Expression Profiles • GeneCut Program (clustering) • Fishing Expedition – A Supervised Approach to Extract Patterns from a Compendium of Expression Profiles • Unified maximum separability Analysis

  7. Oct. 16 (1/3) • Keynote (D.J. Lockhart, Affymetrix) • Experiments without hybridization • Signal intensities and reproducibility (experimental findings, upper 10% ~ lower 60%) • Analysis of Gene Expression and Drug Activity Data by Knowledge-based Association Mining • Association rules finding • DFNA  Taxol in colon cancer cell line • Extracting Knowledge from Genomic Experiments by Incorporating the Biomedical Literature • Poster  (issue of this year in the microarray analysis)

  8. Oct. 16 (2/3) • Closing Remarks (J. Weinstein, NCI) • The variability between cell lines ~ How many replicates should we use? • Omic and hypothesis - driven research (a necessary synergy) • Genomics, proteomics, transcriptomics, toxicomics, clinomics, economics, just comics, etc. • ~ 35,000 human genes • ~ 100,000 splice variation • > 500,000 protein states (post-protein modifications) •  A very wiring diagram of the cell • Methods for gene expression analysis • SAGE • Differential display, restriction display • Flat surface hybridization, etc.

  9. Oct. 16 (3/3) • Closing Remarks (Cont’d) • Protein  2D gels and Mass spectrometry ID. • mRNA  cDNA and oligos • DNA  SNPs, etc. • Integrate expression DB with other DBs • Design study (replicates, controls, internal stds, etc.) • Types of Bioinformatics • Applied Bioinformatics • Exploration of public DBs • Data analysis • Developmental Bioinformatics • Statistical procedure development • Algorithms, software development

  10. Conclusions • CAMDA of this year • America under attacks (?) • Less participants than the last year • The primary issue • Incorporating the knowledge base extracted from the literature databases with the analysis method

More Related