This resource consists of a Java applet and expository text. The applet simulates Bernoulli trials in terms of random points on a timeline. The random variables of interest are the number of successes and the proportion of successes. The number of trials and the probability of success can be varied. This applet illustrates the law of large numbers, the central limit theorem, and the binomial distribution.

Students learn how to manipulate the behavior of water by using biochar—a soil amendment used to improve soil functions. As a fluid, water interacts with soil in a variety of ways. It may drain though a soil’s non-solid states, or its “pores”; lay above the soil; or move across cell membranes via osmosis. In this experiment, students solve the specific problem of standing water by researching, designing, and engineering solutions that enable water to drain faster. This activity is designed for students to explore how biochar helps soils to act as “sponges” in order to retain more water.

This course focuses on the interaction of chemical engineering, biochemistry, and microbiology. Mathematical representations of microbial systems are featured among lecture topics. Kinetics of growth, death, and metabolism are also covered. Continuous fermentation, agitation, mass transfer, and scale-up in fermentation systems, and enzyme technology round out the subject material.

This course is a continuation of Bioinformatics I. Topics include gene expression, microarrays, next- generation sequencing methods, RNA-seq, large genomic projects, protein structure and stability, protein folding, and computational structure prediction of proteins; proteomics; and protein-nucleic acid interactions. The lab component includes R-based statistical data analysis on large datasets, introduction to big data analysis tools, protein visualization software, internet-based tools and high-level programming languages.

This graduate course will introduce students to the processes controlling phytoplankton, zooplankton, heterotrophic bacterial and benthic infaunal growth and abundance. We'll do a broad-scale survey of patterns of productivity and abundance in the coastal zones, upwelling centers, gyres, and the deep sea. We'll briefly survey ecosystem simulation models, especially those applicable to the Gulf of Maine. Readings will be from the primary literature and a few book chapters. The effects of anthropogenic effects on marine communities will be stressed throughout. Calculus will be used throughout the course, but there is no formal calculus requirement.

Biology is designed for multi-semester biology courses for science majors. It is grounded on an evolutionary basis and includes exciting features that highlight careers in the biological sciences and everyday applications of the concepts at hand. To meet the needs of today’s instructors and students, some content has been strategically condensed while maintaining the overall scope and coverage of traditional texts for this course. Instructors can customize the book, adapting it to the approach that works best in their classroom. Biology also includes an innovative art program that incorporates critical thinking and clicker questions to help students understand—and apply—key concepts.

By the end of this section, you will be able to:Identify significant threats to biodiversityExplain the effects of habitat loss, exotic species, and hunting on biodiversityIdentify the early and predicted effects of climate change on biodiversity

By the end of this section, you will be able to:Describe the basic types of ecosystems on EarthExplain the methods that ecologists use to study ecosystem structure and dynamicsIdentify the different methods of ecosystem modelingDifferentiate between food chains and food webs and recognize the importance of each

By the end of this section, you will be able to:Describe the basic types of ecosystems on EarthDifferentiate between food chains and food webs and recognize the importance of each

By the end of this section, you will be able to:Explain pharmacogenomicsDefine polygenic

Analyzes computational needs of clinical medicine reviews systems and approaches that have been used to support those needs, and the relationship between clinical data and gene and protein measurements. Topics: the nature of clinical data; architecture and design of healthcare information systems; privacy and security issues; medical expertsystems; introduction to bioinformatics. Case studies and guest lectures describe contemporary systems and research projects. Term project using large clinical and genomic data sets integrates classroom topics.

This course consists of a series of seminars focused on the development of professional skills. Each semester focuses on a different topic, resulting in a repeating cycle that covers medical ethics, responsible conduct of research, written and oral technical communication, and translational issues. Material and activities include guest lectures, case studies, interactive small group discussions, and role-playing simulations.

This seminar based course explores techniques for recognizing, analyzing, and resolving ethical dilemmas facing healthcare professionals and biomedical researchers in today's highly regulated environment. Guest lectures by practicing clinicians, technologists, researchers, and regulators will include case studies, interactive small group discussions, and role-playing simulations. Professional conduct topics will include authorship, conflict of interest, data acquisition and management, and the protection of human subjects and animals involved in research programs.

This course focuses on feedback control mechanisms that living organisms implement at the molecular level to execute their functions, with emphasis on techniques to design novel systems with prescribed behaviors. Students will learn how biological functions can be understood and designed using notions from feedback control.

The aim of this course is to provide fundamental statistical concepts and tools relevant to the practice of summarizing, analyzing, and visualizing data. This course will build your knowledge of the fundamental principles of biostatistical inference. The course will focus on linear regression and generalized linear regression models. We will use a variety of examples and exercises from scientific, medical, and public health research.

This task asks students to glean contextual information about bird eggs from a collection of measurements of said eggs organized in a scatter plot. In particular, students are asked to identify a correlation and use it to make interpolative predictions, and reason about the properties of specific eggs via the graphical presentation of the data.

In this activity, students distinguish between directly and indirectly transmitted diseases and participate in a group game to simulate the spread of vector-borne diseases. They then research a particular pathogenic disease to learn how global warming and biodiversity loss can affect disease transmission.