Creating and Implementing Quantitative Biology Lessons with QB@CC, Beneficial for Both Faculty and Students

In this activity, students will analyze raw data obtained from an experiment that explores the effect of overexpressing the Ssk protein in order to strengthen the intestinal barrier and prevent bacteria from leaking out of the gut and into the hemolymph, which is the fruit fly equivalent to blood in the circulatory system. Using Excel, students will fit an exponential function to the few known data points and will then interpolate the missing data points and extrapolate a few future data points. They will also learn how they can fit a linear model by transforming the data (applying the logarithmic function) and use that model to estimate the missing data points. This activity involves both statistical analysis and mathematical modeling as well as displaying the usefulness of mathematical models for biological data analysis.

This is a poster presented at the SABER West 2020 conference. We introduced the grant's goals and objectives, described the leadership team and disseminated the information about the first network launch meeting.

This module explores how cell size and shape varies across cell types in the human body by having students calculate relative proportions of numbers in scientific notation. The adaptation has added a review of scientific notation.

In this powerpoint, several of the resources from the published module 'Sizes, Scales and Specialization' are used to create a mini-module that has students examine the size and abundance of different human cell types using scientific notation.

NABT and QB@CC hosted a special webinar to explore the QB@CC OER entitled Sizes, Scales, and Specialization.

Students are introduced to concepts of sampling distributions, p-values, and hypothesis testing. Using both simulated and real data for methylmercury level in fish populations, students will determine whether observations fall within government safety guidelines for safe consumption.

In this adaptation students in online classrooms will use linear regression at home and in synchronous online time to analyze real data on vector-borne diseases and explore how environmental factors affect disease transmission.

In this activity students will use linear regression to analyze real data on vector-borne diseases and explore how environmental factors such as climate change or population density influence the transmission of these diseases.

In this activity students will use statistics and regression models to explore the effects of carbon dioxide on blood pH by measuring pH changes that occur over time as carbon dioxide reacts with water to form carbonic acid. Physiological pH changes caused by exercise are also examined.

In this activity, students will perform an experiment utilizing dialysis tubing to create cellular models to demonstrate the linear relationship between cell weight and time in varying tonicities. Videos and data sets (of faculty results) are provided for

This collection of activities explores the relationship between blood flow, pressure, and the factors of resistance through graphs and modeling direct and inverse variation.