Ongoing statistical genetics research involves data analysis, methodology and design [A 38, 40, 43-44, 48-49, 53-60; B 1-2, 6-7; E 8-9 *]. Work by Satagopan (PhD 1996 **) on Bayesian inference for QTLs using Markov chain Monte Carlo methods to estimate the joint distribution of QTL number, locations and effects [A 38; E 8; F 8; S 2-3] has been continued by Gaffney [F 9] (PhD 2001). Recent QTL research with Zou [A 54, 60; B 1] (PhD 2001) and Fine (Biostatistics) includes combining genetic data across multiple experiments [B 11] and semi-parametric and non-parametric inference for QTLs [B 10; N 4]. Other theoretical and applied genetics research concern mixed models [A 45; N 4] and polyploid genetics [A 40, 44]. Recent collaborations with Gianola (Animal Science) examines genetic map construction [A 53; F 10; N 3]. Considerable recent research has been focused on microarray gene expression data analysis, particularly with Lin (Statistics) and Attie (Biochemistry) on microarray data analysis [A 48, 49, 56, 58, 59; B 2, 6-8; E 9; S 6, 8-9]. Invited to workshops in Finland, NCSU, and Jackson Labs; joint plans for a QTL book [J 3].
Research in ecological modeling builds on novel ideas about individual-based models in population ethology [A 52; H 11; J 1-2] with a software release [S 7].
* Citations in brackets refer to Curriculum Vitae.
** See Student Advising.