Changing the Nature of Quantitative Biology Education: Data Science as a Driver.

We live in a data-rich world with rapidly growing databases with zettabytes of data. Innovation, computation, and technological advances have now tremendously accelerated the pace of discovery, providing driverless cars, robotic devices, expert healthcare systems, precision medicine, and automated discovery to mention a few. Even though the definition of the term data science continues to evolve, the sweeping impact it has already produced on society is undeniable.

Mathematical biology modules based on modern molecular biology and modern discrete mathematics.

We describe an ongoing collaborative curriculum materials development project between Sweet Briar College and Western Michigan University, with support from the National Science Foundation. We present a collection of modules under development that can be used in existing mathematics and biology courses, and we address a critical national need to introduce students to mathematical methods beyond the interface of biology with calculus. Based on ongoing research, and designed to use the project-based-learning approach, the modules highlight applications of modern discrete mathematics and algebraic statistics to pressing problems in molecular biology.

Bayesian probability approach to ADHD appraisal.

Accurate diagnosis of attentional disorders such as attention-deficit hyperactivity disorder (ADHD) is imperative because there are multiple negative psychosocial sequelae related to undiagnosed and untreated ADHD. Early and accurate detection can lead to effective intervention and prevention of negative sequelae. Unfortunately, diagnosing ADHD presents a challenge to traditional assessment paradigms because there is no single test that definitively establishes its presence.

Desegregating undergraduate mathematics and biology--interdisciplinary instruction with emphasis on ongoing biomedical research.

The remarkable advances in the field of biology in the last decade, specifically in the areas of biochemistry, genetics, genomics, proteomics, and systems biology, have demonstrated how critically important mathematical models and methods are in addressing questions of vital importance for these disciplines. There is little doubt that the need for utilizing and developing mathematical methods for biology research will only grow in the future. The rapidly increasing demand for scientists with appropriate interdisciplinary skills and knowledge, however, is not being reflected in the way undergraduate mathematics and biology courses are structured and taught in most colleges and universities nationwide.

Diffuse mesangial IgA glomerulonephritis in a patient with rheumatoid arthritis: a possible extra-articular manifestation in rheumatoid arthritis.

Rheumatoid arthritis (RA) is an inflammatory joint disease, in which, unlike systemic lupus erythematosus (SLE), renal involvement is uncommon. The major causes of renal disease in RA are usually linked to amyloid or secondary effects of drugs. Nevertheless the relation between IgA, IgA-rheumatoid factor (RF) and renal disease in patients with RA is not clear, but the affinity of IgA for mesangium, skin and synovium might explain clinical presentation of RA with mesangial IgA glomerulonephritis.

Calibration of ADHD assessments across studies: a meta-analysis tool.

When analyzed separately, data from small studies provide only limited information with limited clinical generalizability, due to small sample size, differing assessments, and limited scope. In this methodological paper we outline a theoretical framework for performing meta-analysis of data obtained from disparate studies using disparate tests, based on calibration of the data from such studies and tests into a unified probability scale. We apply this method to combine the data from five studies examining the diagnostic abilities of different assessments of Attention Deficit/Hyperactivity Disorder (ADHD), including behavioral rating scales and EEG assessments.