The QBS program seeks to train highly qualified students for productive careers in biomedical research and teaching through the completion of an interdisciplinary PhD degree in bioinformatics, biostatistics and epidemiology. Our philosophy is that the modern biomedical researcher must be able to speak more than one language to successfully collaborate in a highly multidisciplinary environment.

Upcoming Events

Jan 9th / 4 - 4:45 pm / Aud H DHMC

QBS Student RIPS

"Characterization of the maternal influence on the infant gut microbiome"

Recent News

Brock Christensen's, PhD lab recently had their paper "5-Hydroxymethylcytosine localizes to enhancer elements and is associated with survival in glioblastoma patients" published in Nature Communications. Their work was also featured on The NIH Director's Blog and by The Geisel News Center.

Chris Amos, PhD has recently published about the development of an inexpensive genotyping microarray, the OncoArray. Check out these other recent publications in Bioinformatics and Arthritis & Rheumatology with his former QBS student David Qian, PhD.

QBS student Craig MacKenzie and mentor Gevorg Grigoryan,PhD recently published in The Proceedings of the National Academy of Sciences on the "Tertiary alphabet for the observable protein structural universe"

Check out James O'Malley's recent publications "Optimal small-area estimation and design when nonrespondents are subsampled for followup" and "Modeling zero-modified count and semicontinuous data in health services research Part 1: background and overview and Part 2: case studies."

"Effects of low arsenic levels during pregnancy and fetal growth" published by Diane Gilbert-Diamond, PhD along with QBS co-authors Jennifer Emond, PhD and Margaret Karagas, PhD was selected as one of NIEHS' top papers of the year. Check out Diane's other recent publication "Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues"

Eugene Demidenko, PhD presented his work at the Norris Cotton Cancer Center Grand Rounds based on his recent publication, "The P-value You Can't Buy". Eugene also published this month in "Toxicology and Applied Pharmacology".

QBS students, Ellen Nutter, Mavra Nasir, Lia Harrington, as well as MCB student, Youdinghuan Chen were recently accepted to the The Dartmouth Big Data in the Life Sciences Training Program supported by the Burrough's Wellcome Trust.

Third year QBS student, Jeffrey Thompson had his paper "A Methylation-to-Expression Feature Model for Generating Accurate Prognostic Risk Scores and Identifying Disease Targets in Clear Cell Kidney Cancer" accepted to proceedings of the Pacific Symposium on Biocomputing (PSB) Jan 3-7, 2017. He has also received a travel award to attend the conference and will give an invited talk on the paper.

Second year QBS student, Alexander Titus, and incoming QBS student, Daniel Mattox, were selected to be Big Data Trainees and will receive graduate training support from the Big Data to Knowledge (BD2K) Predoctoral Training in Biomedical Big Data Science (T32) grant. Read more about the BD2K initiative...

Third year QBS student, Sara Lundgren, was awarded the Rosaline Borison Memorial Predoctoral Fellowship. This competitive fellowship supports graduate students working on promising topics in medical science and distinguishes students who are doing exceptional work.

Recent QBS graduate, David Qian, was awarded the 2016 John W. Strohbehn Medal for Excellence in Biomedical Research at Dartmouth's Graduate Investiture Ceremony on June 11, 2016. This award recognizes a graduating PhD candidate who best exemplifies qualities of a scientific scholar. Read more...

Michael Whitfield, PhD, a translational genetics researcher at Dartmouth's Geisel School of Medicine, has earned a second highly competitive award from the Dr. Ralph and Marian Falk Medical Research Trust for his pioneering work on the rare autoimmune disease systemic scleroderma. Read more...

A research team, led by Chao Cheng, Ph.D., Assistant Professor in the Department of Genetics at The Geisel School of Medicine at Dartmouth, used gene expression data from breast cancer patients to computationally infer the presence of different types of immune cells. Read more... Publication