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  8. Joseph Meehan
  1. Science & Research (NCTR)

Computer Scientist  — Division of Bioinformatics and Biostatistics

Joseph Meehan
Joseph Meehan

(870) 543-7121

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About  |  Publications 


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 Little Rock, and management through the University of London (London School of Economics) before earning a graduate certificate in bioinformatics from Stanford in 2003. Mr. Meehan began his career as a computer 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 advisor in the Division of Bioinformatics and Biostatistics.

Research Interests

Mr. Meehan serves as a team leader for bioinformatics software development, where he is responsible for the development of new software for diverse research applications, including regulatory informatics, toxicogenomics, and machine learning.

He is the NCTR principal investigator on a collaborative project to develop and enhance regulatory review and research tools at FDA’s Center for Drug Evaluation and Research, 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 pattern matching and natural language processing.

Professional Societies/National and International Groups

The American Association for the Advancement of Science (AAAS)          
2017 – Present

Select Publications

Publication titles are linked to text abstracts on PubMed.

Applying Network Analysis 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 Short Reads: A Crucial Step for Application of Next-Generation Sequencing Data in Precision Medicine.
Ye H., Meehan J., Tong W., and Hong H.
Pharmaceutics. 2015, 7(4):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 X., Ning B., Gong B., Meehan J., Xu J., Ge W., Perkins R., Fischer M., and Tong W.
Genome Biol. 2014, 15(12):523.

Assessing Technical Performance in Differential Gene Expression Experiments with External Spike-in RNA Control Ratio Mixtures.
Munro S., Lund S., Pine P., Binder H., Clevert D., Conesa A., Dopazo J., Fasold M., Hochreiter S., Hong H., Jafari N., Kreil D., Łabaj P., Li S., Liao Y., Lin S., Meehan J., Mason C., Santoyo-Lopez J., Setterquist R., Shi L., Shi W., Smyth G., Stralis-Pavese N., Su Z., Tong W., Wang C., Wang J., Xu J., Ye Z., Yang Y., Yu Y., and Salit M.
Nat Commun. 2014, 5:5125.

The Concordance Between RNA-Seq and Microarray Data Depends on Chemical 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 X., Yang L., Li H., Łabaj P., Kreil D., Megherbi D., Gaj S., 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 S., Filosi M., Visintainer R., Zhang K., Li J., Hsieh J., Svoboda D., Fuscoe J., Deng Y., Shi L., Paules R., Auerbach S., and Tong W.
Nat Biotechnol. 2014, 32(9):926-32.

Whole Genome Sequencing of 35 Individuals Provides Insights into the Genetic Architecture 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, 15 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 W., Nayak R., Xu J., Fang H., and Chen J.
PLoS One. 2013, 8(3):e59224.

Data Mining Tools for Salmonella Characterization: Application to Gel-Based Fingerprinting Analysis.
Zou W., Tang H., Zhao W., Meehan J., Foley S., Lin W., Chen H., Fang H., Nayak R., and Chen J.
BMC Bioinformatics. 2013, 14 Suppl 14:S15.

The Microarray Quality Control (MAQC)-II study of Common Practices for the Development and Validation of Microarray-Based Predictive Models.
MAQC Consortium.
Nat Biotechnol. 2010, 28(8):827-38.

Contact Information
Joseph Meehan
(870) 543-7121
Technology & Discipline
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