|
Wednesday, August 23
Conference Short Course Tutorials
Morning
8:30 am Registration for Morning Short Courses
9:00-12:00
|
Array Technologies for Pathogen Detection |
OR |
Using Classical Statistics & Experiment Design, Reduce Noise in Your Next Microarray Experiment |
9:00 Advanced Applications of xMAP Technology for Pathogen Detection
Dr. John C. Carrano, Executive
Director, R& D, Luminex Corporation
In this paper we present a discussion of the chip-scale implementation of a bio-detection technology suitable for a variety of applications including medical diagnostics, drug discovery, and environmental pathogen sensors. One very successful instrument approach in this class of detection technology is the optically read, bead-based bio-assay flow cytometer. Dyed microspheres capable of generating 100 distinct bead sets are coated with bio-assays, then prepared with a given sample and interrogated by two lasers: one to identify the distinct bead set; and the other to determine assay binding events. Our new concept involves an optimized implementation of micro-fluidics, electronics, and photonic components designed to provide very high performance, compact form-factor, and greatly reduced cost compared to current generation systems. This chip-scale implementation takes advantage of not only the economy of scale traditionally associated with semiconductor technologies, but also the robustness offered by the heterogeneous integration of multiple components on a single substrate.
10:00 Development of Simple, Sensitive and Sturdy devices for Threat Detection and Identification
Dr. Andy McShea, Vice President, Biology & Chemistry,
CombiMatrix Corporation
CombiMatrix technology readily supports multiplexed genomic and serological assays against all categories of biothreat agents. CombiMatrix instruments are based on a novel semiconductor technology platform combined with electro-chemical detection. CombiMatrix electrochemical detection system is a fixed or mobile stand-alone detection system that identifies threat agents in less than one minute.
11:00 TBA |
Mr. Thomas J.
Downey, President, Partek, Inc.
Microarray data contains treatment and/or phenotype effects embedded in a
sea of technical and biological noise. This workshop will demonstrate how
to use proven statistical methods of experiment design and data analysis to
reliably identify biological effects of interest while controlling and
removing noise due to biological and technical nuisance effects.
Attendees will learn how to employ completely randomized block designs to
isolate and remove batch effects due to processing batches, etc. clearly
revealing the signals from the biological factors of interest. In addition
to p-values, estimates of ratios and fold-changes will be examined from a
statistical perspective. The techniques will be demonstrated using
published Affymetrix gene expression and exon experiments. Attendees will
learn how to apply and interpret statistical techniques such as analysis
of variance (ANOVA) -including mixed linear models and linear contrasts,
multiple test corrections, and principal components analysis.
Who should attend?
This workshop is designed for scientists who design and analyze microarray
experiments, and would like to learn the statistical techniques that will
lead to reliable, reproducible biological results. |
Afternoon
1:30 Registration for Afternoon Short Courses
2:00-5:00
|
Taking Multivariate Statistical
Methods of the Black Box |
OR |
Advanced Methods for Microarray Analysis |
|
Ms. Janis Dugle, Senior Research Scientist (Statistics), Ross Products Division, Abbott Laboratories
The multivariate statistical methods of Principal Components Analysis (PCA), Partial Least Squares
(PLS) and Discriminant Analysis (DA) have become popular tools of the burgeoning biosytems and “omics” sciences (genomics, proteomics,
metabonomics, etc.). However, they often appear as “black box” techniques that leave the scientist in the dark about what has been done to his/her data. This mini-course provides a non-technical introduction to these methods. Many examples of PC, PLS and DA are given (sometimes on the same data), which allows comparisons of their capabilities, limitations, and commonalities. Many sources of data are used to illustrate the wide range of application of these techniques, and the resulting graphical output gives a hands-on feel to large data sets. The course ends with a grand finale of a marker search through data with thousands of measurements on 116 samples. This class is enjoyable and easily understood, regardless of your statistical background.
Who should attend?
This course is designed for anyone who wants a non-technical, understandable, highly visual overview of PC, PLS, and DA. It is appropriate for the researcher who is interested in seeing what statistics can and can't do, but who is not concerned with technical statistical derivations.
Why attend?
Do you want to be able to “talk the talk” in multivariate methods? This is the place. Find out what they are doing with your data, and what other options may be available. |
Mr. Paul Fogel, Consultant, France
The purpose of this course is to present advanced methods for microarray analysis, but to do it in a way that emphasizes concepts and visualization. The steps in the analysis process will be covered, but the main focus will be on the gene to experimental outcome step, target identification. There is a move to ever larger numbers of genes, while the number of samples is increasing only modestly. The key concept is to take advantage of the correlation among the genes so that meaningful sets of genes are identified. Theory will be presented. Available software to support the theory and analysis will be integrated into the course. Real examples will be used. The attendee will come away with an overall view of the process and the methods needed to make a sound analysis of microarray experiments.
Who should attend?
Biologists wishing to understand the statistical methods used for microarray data. Statisticians wanting to see cutting edge methods for microarray analysis.
Managers who want to understand analysis results to help them guide key next steps. |
5:00-6:00 Early Registration For Microarray Data Analysis Meeting
Separate Registration Required
“Torture the data long enough and they will confess to anything”
David G., Merck Co.
For more information, please contact:
Mary Ann Brown, Senior Conference Director, Cambridge Healthtech Institute
Phone: 781-972-5497 E-mail: mabrown@healthtech.com
For sponsorship information, please contact:
Suzanne Carroll, Manager, Business Development, Cambridge Healthech
Institute
Phone: 781-972-5452 Email: scarroll@healthtech.com
|
