DNA Microarray Image Analysis - University of Illinois at Urbana ...
DNA Microarray Image Analysis - University of Illinois at Urbana ... DNA Microarray Image Analysis - University of Illinois at Urbana ...
Open Problems • Problem statements: • Problem #1: Given gene annotations and tabular information about expression level, fuse and visualize the information • Problem #2: Given a data base of microarray experiments (only numerical expression level information), find the best match of a new microarray experiment in the data base. • Problem #3: Incorporate multiple knowledge discovery techniques into analyses 84
Visualization • Data: 3D cubes,distribution charts, curves, surfaces, link graphs, image frames and movies, parallel coordinates • Results: pie charts, scatter plots, box plots, association rules, parallel coordinates, dendograms, temporal evolution Pie chart Parallel coordinates Temporal evolution 85
- Page 33 and 34: Microarray Grid Alignment: Previous
- Page 35 and 36: 35 Grid Alignment Algorithm Overvie
- Page 37 and 38: Image Down-Sampling • Design of r
- Page 39 and 40: Vertical and Horizontal Line Score
- Page 41 and 42: Optional Regularity Enforcement •
- Page 43 and 44: Processing Multiple Grids Line Disc
- Page 45 and 46: Spot Size & Spot Density 45 •Radi
- Page 47 and 48: Missing Spots The fewer the spots i
- Page 49 and 50: Down-sampling •Experimental resul
- Page 51 and 52: Grid Alignment Properties Color Inv
- Page 53 and 54: Multiple Grids: Semi-Automated vs.
- Page 55 and 56: 55 MICROARRAY FOREGROUND SEPARATION
- Page 57 and 58: Foreground Separation Using Spatial
- Page 59 and 60: Foreground Separation Using Intensi
- Page 61 and 62: Foreground Separation From Multi-Ch
- Page 63 and 64: Step 1: Separating Spots from Backg
- Page 65 and 66: Goals and Objectives of Quality Ass
- Page 67 and 68: Quality Assessment: Spot Examples
- Page 69 and 70: Criteria for Assessing Morphologica
- Page 71 and 72: I2K Selecting Valid Pixels - SNR Me
- Page 73 and 74: I2K Selecting Valid Pixels - Topolo
- Page 75 and 76: 75 MICROARRAY DATA QUANTIFICATION A
- Page 77 and 78: Spot Descriptors • Volume of fore
- Page 79 and 80: Visualization of Spot Descriptors S
- Page 81 and 82: Normalization • Normalization usi
- Page 83: 83 MICROARRAY DATA FUSION, ANALYSIS
- Page 87 and 88: Web-Based Documentation 87 http://a
Open Problems<br />
• Problem st<strong>at</strong>ements:<br />
• Problem #1: Given gene annot<strong>at</strong>ions and tabular inform<strong>at</strong>ion<br />
about expression level, fuse and visualize the inform<strong>at</strong>ion<br />
• Problem #2: Given a d<strong>at</strong>a base <strong>of</strong> microarray experiments<br />
(only numerical expression level inform<strong>at</strong>ion), find the best<br />
m<strong>at</strong>ch <strong>of</strong> a new microarray experiment in the d<strong>at</strong>a base.<br />
• Problem #3: Incorpor<strong>at</strong>e multiple knowledge discovery<br />
techniques into analyses<br />
84
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