Thermo Fisher Scientific Publishes new Poster from Lab Automation 2009
News Apr 16, 2009
Thermo Fisher Scientific Inc. has published a new technical poster demonstrating how Thermo Scientific Nautilus LIMS™ has helped accelerate discovery for the Miami Project to Cure Paralysis in their high content screening laboratories.
The new technical poster is available free-of-charge via http://www.thermo.com/eThermo/CMA/PDFs/Product/productPDF_50097.pdf.
The poster was presented at the Lab Automation 2009 conference in Palm Springs, CA and is entitled Integrating Informatics and High Content Screening to Find a Cure for Spinal Cord Injury. Co-authored by research scientists from the University of Miami Miller School of Medicine and senior technical managers from Thermo Fisher Scientific, the poster highlights the growing need to manage the large amounts of data generated in the screening of neurons undertaken during the Project’s quest to promote nerve growth.
The Miami Project to Cure Paralysis sought a Laboratory Information Management System (LIMS) for its LemBix laboratory that would facilitate their laboratory workflows and automate their previously manual data management processes. With the increasing workload in their high-throughput laboratories, a single experiment can generate data from 300,000 neurons with 140 parameters per cell, and managers required an informatics solution that could manage the flow of data and enhance productivity.
Furthermore, lab managers needed to be able to readily access and analyze the data to provide them with knowledge that was previously difficult to acquire. The new poster demonstrates how the lab implemented an informatics solution to manage the enormous volumes of data generated by The Miami Project to Cure Paralysis in order to ease the administrative tasks of the scientist so they could focus on the laboratory’s goal of finding a cure.
Thermo Fisher introduced a workshop approach with the LemBix Laboratory to minimize costs and engage staff while developing the best solution to integrate informatics in their high content screening environment. The LemBix laboratory implemented Thermo Scientific Nautilus LIMS to improve productivity, organize and improve the accuracy of their collected data.
An artificial intelligence (AI) approach based on deep learning convolutional neural network (CNN) could identify nuanced mammographic imaging features specific for recalled but benign (false-positive) mammograms and distinguish such mammograms from those identified as malignant or negative.
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