Go Go Go Joseph You Know What They Say
Computer Scientist — Division of Bioinformatics and Biostatistics
Joseph Meehan
(870) 543-7121
NCTRResearch@fda.hhs.gov
Dorsum to NCTR Principal Investigators folio
About | Publications
Background
Joseph Meehan studied philosophy at Rhodes College and graduated with a bachelor's degree cum laude in 1981. He studied computer science at the University of Arkansas at Petty Rock, and management through the University of London (London Schoolhouse of Economic science) before earning a graduate certificate in bioinformatics from Stanford in 2003. Mr. Meehan began his career every bit a figurer programmer at Baptist Memorial Hospital in Memphis before coming to NCTR in 1983. He was the systems and networks manager from 2001 to 2008 and software development manager from 2008 to 2012 for NCTR. He currently is a senior counselor in the Sectionalisation of Bioinformatics and Biostatistics.
Research Interests
Mr. Meehan serves as a team leader for bioinformatics software development, where he is responsible for the evolution of new software for various inquiry applications, including regulatory information science, toxicogenomics, and machine learning.
He is the NCTR principal investigator on a collaborative projection to develop and enhance regulatory review and enquiry tools at FDA's Heart for Drug Evaluation and Inquiry, including efforts to port a critical regulatory database to Oracle, capture pharmacology and toxicology review data from review documents, and retrospectively extract review information from FDA approval letters using blueprint matching and natural language processing.
Professional person Societies/National and International Groups
The American Clan for the Advancement of Scientific discipline (AAAS)
Member
2017 – Present
Select Publications
Publication titles are linked to text abstracts on PubMed.
Applying Network Assay and Nebula (Neighbor-Edges Based and Unbiased Leverage Algorithm) to Toxcast Data.
Ye H., Luo H., Ng H., Meehan J., Ge W., Tong W., and Hong H.
Environ Int. 2016, 89-90:81-92.
Alignment of Curt Reads: A Crucial Step for Awarding of Next-Generation Sequencing Data in Precision Medicine.
Ye H., Meehan J., Tong W., and Hong H.
Pharmaceutics. 2015, seven(four):523-41.
An Investigation of Biomarkers Derived From Legacy Microarray Data for Their Utility in the RNA-Seq Era.
Su Z., Fang H., Hong H., Shi L., Zhang W., Zhang W., Zhang Y., Dong Z., Lancashire L., Bessarabova M., Yang 10., Ning B., Gong B., Meehan J., Xu J., Ge Due west., Perkins R., Fischer M., and Tong W.
Genome Biol. 2014, xv(12):523.
Assessing Technical Performance in Differential Factor Expression Experiments with External Spike-in RNA Command Ratio Mixtures.
Munro S., Lund S., Pine P., Binder H., Clevert D., Conesa A., Dopazo J., Fasold Thou., Hochreiter S., Hong H., Jafari North., Kreil D., Łabaj P., Li South., Liao Y., Lin S., Meehan J., Mason C., Santoyo-Lopez J., Setterquist R., Shi L., Shi W., Smyth G., Stralis-Pavese Due north., Su Z., Tong W., Wang C., Wang J., Xu J., Ye Z., Yang Y., Yu Y., and Salit One thousand.
Nat Commun. 2014, five:5125.
The Concordance Betwixt RNA-Seq and Microarray Data Depends on Chemic Treatment and Transcript Abundance.
Wang C., Gong B., Bushel P., Thierry-Mieg J., Thierry-Mieg D., Xu J., Fang H., Hong H., Shen J., Su Z., Meehan J., Li Ten., Yang 50., Li H., Łabaj P., Kreil D., Megherbi D., Gaj Southward., Caiment F., van Delft J., Kleinjans J., Scherer A., Devanarayan V., Wang J., Yang Y., Qian H., Lancashire L., Bessarabova M., Nikolsky Y., Furlanello C., Chierici M., Albanese D., Jurman G., Riccadonna Due south., Filosi M., Visintainer R., Zhang K., Li J., Hsieh J., Svoboda D., Fuscoe J., Deng Y., Shi Fifty., Paules R., Auerbach Southward., and Tong W.
Nat Biotechnol. 2014, 32(9):926-32.
Whole Genome Sequencing of 35 Individuals Provides Insights into the Genetic Compages of Korean Population.
Zhang W., Meehan J., Su Z., Ng H., Shu M., Luo H., Ge W., Perkins R., Tong W., and Hong H.
BMC Bioinformatics. 2014, fifteen Suppl 11:S6.
Meta-Analysis of Pulsed-Field Gel Electrophoresis Fingerprints Based on a Constructed Salmonella Database.
Zou W., Chen H., Hise K., Tang H., Foley S., Meehan J., Lin Due west., Nayak R., Xu J., Fang H., and Chen J.
PLoS One. 2013, eight(3):e59224.
Data Mining Tools for Salmonella Characterization: Application to Gel-Based Fingerprinting Analysis.
Zou Due west., Tang H., Zhao West., Meehan J., Foley Due south., Lin W., Chen H., Fang H., Nayak R., and Chen J.
BMC Bioinformatics. 2013, 14 Suppl 14:S15.
The Microarray Quality Control (MAQC)-Two study of Common Practices for the Development and Validation of Microarray-Based Predictive Models.
MAQC Consortium.
Nat Biotechnol. 2010, 28(eight):827-38.
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Source: https://www.fda.gov/about-fda/science-research-nctr/joseph-meehan
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