Analysis Methods Core Members

Jeffrey O’Connell, PhD

Co-leader of the Analysis Methods Core. Extensive experience developing and implementing custom analysis methods in MMAP (Mixed Models for Analysis in Pedigrees/Populations) software to address mdoeling gaps and compute challenges for big data. He has developed turn-key cluster-based scripts and cloud-based apps to facilitate deployment of complex analyses and pipelines in TOPMed.

Paola Sebastiani, PhD

Co-leader of the Analysis Methods Core. Dr. Sebastiani led the development of the FLoSS score that was used to select informative families for enrollment in LLFS and has been a statistician for LLFS since 2005. She hasdeveloped new methods to discover patterns of molecular data and to generate Byesian networks from family-based observational data.

Stefano Monti, PhD

Computational biology and network modeling


Dr. Benos

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Dr. Lodi

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Kathryn Lunetta, PhD

Biostatistician, Framingham Heart Study Liason


Robert Boudreau, PhD

Application and development of methods for modeling longitudinal data, employing hierarchical and mixed models, cluster analysis and longitudinal latent class and mixture models.


Anatoliy Yashin, PhD

Expertise in developing mathematical and statistical methods of analysis of genetic and non-genetic data on aging, health, and survival using data collected in various longitudinal human studies. His major research interest is in understanding mechanisms regulating rates of physiological aging changes.


Michael Province, PhD

Statistical genetics methods including haplotyping and correlated meta-analysis.


Michael Brent, PhD

Developing and applying mathematical and computational methods for mapping gene regulation networks, modeling them quantitatively, and synthesizing new network designs.


E. Warwick Daw, PhD

Statistical methods related to quality control of genomic data, family-based analysis methods, haplotyping.