On the trail of Genomic Pioneers-James Lupski
The inaugural edition of our ‘On the Trail of Genomic Pioneers’ interview series features Prof. James R. Lupski, Department of Molecular and Human Genetics, Baylor College of Medicine. His research focuses on using human genetics, genomics, and molecular biological techniques to elucidate biological mechanisms for diseases. This interview gives fascinating insights into genomic disorders and discusses his research in this area.
Snippet from Prof. Lupski’s interview
“We do believe that CNV may be responsible for a lot more disease than currently believed or anticipated. The focus to date in approaches to human genetic traits has been, whether by virtue of the Mendelian model or a hypothesis generating search through genome-wide association studies (GWAS), the focus has been on base pair changes as being responsible for the variation leading to the genetic cause or susceptibility to disease traits. However, if we look just in the past year or two alone we have witnessed that when researchers open their minds to CNV as a mutational mechanism, and analyze their data with that thought in mind, one can find CNV being responsible for conditions such as autism and schizophrenia for which we previously have had a difficult time identifying specific genetic etiologies”
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Gaithersburg, Maryland, US, July 21, 2009: Genomic Pioneers Gateway has announced a call for partnership with societies, industry associations, regional biotech clusters and other likeminded forums for their upcoming programs. Genomic Pioneers Gateway is the thought leadership forum and ideation platform comprising thought leaders, key think tanks, companies, research centers and societies for envisioning and giving direction to the field of Genomics. This class is a ‘group of excellence’ which works together for creating affordable, novel and quality genomics driven solutions in key areas including improved healthcare & therapeutics, agriculture, food & nutraceuticals amongst other niche priority areas.
In order to maximize confidence in gene fragment estimates using oligonucleotide microarrays such as the Affymetrix GeneChip , it’s necessary to identify arrays contaminated with artifacts not related to fragments of interest. While it is recognized that quality control measures should be implemented in generating gene expression data, existing quality control techniques employ limited functionality. One of the more critical metrics in assessing a genome chip is the overall chip brightness involving an estimate of the background noise on the chip. The overall chip brightness provides a basis for an automatic pass or fail. The quality metrics comprise a plurality of algorithms for detection of outliers resulting from commonly encountered defects.
The system for analyzing gene expression data obtained from a plurality of microarrays having mismatch (MM) probe pairs and perfect match (PM) probe pairs is automated. Image data for a plurality of scanned microarrays is stored in a database along with a set of microarray parameters which includes one or more image processing metrics for quality control of the microarray and a pass/fail status of the microarray as determined by these metrics. The user can search the database records according to one or more microarray parameters. The image processing metrics include algorithms for removing local background effects from the probe measurements by determining a model for estimated background using PM probe values.
A centralized application is provided for viewing, masking and pass/failing chips, and making use of the Image Processing (IP) metrics and limits. The application tracks the processes as a chip moves from registration and scan to publish and beyond. It permits users to view experiments, mask experiments if necessary, set pass/fail status and fail reason if fail, correct problems and view any of a number of chip parameters including IP (image processing) metrics and limits.
The Method and System for managing and querying gene expression data according to quality is covered by a patent in the name of Gene Logic. To know more about this patent, follow this link: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PTXT&s1=%22ocimum+biosolutions%22&OS=”ocimum+biosolutions”&RS=”ocimum+biosolutions“
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