LabAutomation 2006 - SLAS
LabAutomation 2006 - SLAS
LabAutomation 2006 - SLAS
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Where Laboratory Technologies Emerge and Merge<br />
11:00 am Tuesday, January 24, <strong>2006</strong> Track 4: Informatics Room: Madera<br />
Wyndham Palm Springs Hotel<br />
Silpa Wairatpanij<br />
Co-Author<br />
Indiana University School of Informatics<br />
Douglas Perry<br />
Indianapolis, Indiana<br />
siwairat@iupui.edu<br />
Indiana University School of Informatics<br />
Robot Re-engineering for LabVIEW Functionality<br />
Introduction<br />
The Zymate laboratory robot (Caliper Life Sciences) is excellent for demonstrating the principles of laboratory robotics, but it is controlled by a<br />
proprietary, motion-level programming language, limiting its usefulness. To use the robot for job-level programming using LabVIEW, re-engineering<br />
is necessary. The goal of this project was to unleash the full potential of LabVIEW by using state-of-the-art hardware for robotic control.<br />
Methods<br />
To do this, we completely rebuilt the robot using the latest sensors, actuators, and controller hardware. The original robot was stripped down<br />
to its frames and joints. To transition from analog to digital control, we designed a new control system in which potentiometers were replaced<br />
with digital encoders, and analog actuator drivers with pulse width modulation drivers. To increase stability, we added digital signal feedback and<br />
increased actuator torque.<br />
For time-critical tasks, real-time control is essential. This requires rapid control loop turnaround. To accomplish this, we bypassed the computer<br />
bus by implementing an external controller.<br />
Challenges in achieving this goal included designing and implementing entirely new circuitry throughout the robot, overcoming physical design<br />
constraints by using multiplexer technology, and reducing circuit noise with efficient isolation techniques.<br />
Results<br />
Re-engineering the robot resulted in markedly improved performance characteristics, which included excellent system stability and<br />
accuracy and increased motion resolution to the submillimeter range. Most important, we gained the ability to program the robot with the<br />
full capabilities of LabVIEW.<br />
11:30 am Tuesday, January 24, <strong>2006</strong> Track 4: Informatics Room: Madera<br />
Wyndham Palm Springs Hotel<br />
Tom Downey<br />
Co-Author(s)<br />
Partek Incorporated<br />
Scott Lyon<br />
St Charles, Missouri<br />
Dave Bennett. Partek Inc.<br />
tjd@partek.com<br />
Edward Spitznagel<br />
Washington University<br />
Jing Lin<br />
Partek Inc.<br />
Reducing Noise Due to Technical Batch Effects in Biological Data<br />
Biological data contains signals hidden in a sea of noise.<br />
The noise is a combination of biological variability, inherent imprecision of the measurement technology, and technical and biological<br />
“batch” effects. These batch effects come from a variety of sources, such as different operators, biological samples (e.g. cell lines),<br />
reagent batches and lots, processing dates, etc. We demonstrate how to incorporate technical batches into the experiment design so<br />
that they can be removed from the data using statistical estimates such as analysis of variance (ANOVA). We use example data from highthroughput<br />
screening and gene expression microarrays to show how this technique greatly reduces noise due to technical batch effects,<br />
revealing the biological signals much more clearly than in the original data.<br />
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