Bill Forrest

Molecular medicine is an evolving and expanding body of knowledge and methods wherein each advance enables experiments that reveal new insights into human disease. I work closely with discovery and translational scientists, applying both classic statistical techniques and recent methodological advances to frame questions, design experiments, and craft & conduct statistical analyses that will extend our understanding so that the next round of investigation can come into focus.

Working in statistics within biotechnology is an opportunity to learn continually about diverse and developing areas. Some recent collaborations have included applying mixed models to proteomic assays to detect rare types of enzymes and advising bioinformatic scientists on choice and application of techniques from penalized regression and machine learning for identifying features of high-dimensional data sets relevant in cancer immunology. My current work is developing new statistical summaries and software employing regression splines to estimate changes in longitudinal data, with applications in translational oncology.

• University of Pittsburgh, Department of Human Genetics, Postdoctoral Researcher – 1998-2000
• University of California, Berkeley, Ph.D. in statistics – 1998
• University of California, Berkeley, M.A. in statistics – 1994
• Santa Clara University, B.S. in mathematics – 1992