Antibiotic resistance is a global public health concern. Bacteria have evolved resistance to most antibiotics, which means that for any given bacterial infection, the bacteria may be resistant to one or several antibiotics. For effective treatment and to control the spread of resistant strains of bacteria, accurate and efficient detection of resistance is important. It has been suggested that genomic sequencing and machine learning (ML) could make resistance testing more accurate and cost-effective. Given that ML is likely to become an ever more important tool in medicine, we believe that it is important for pre-health students and others in the life sciences to learn to use machine learning tools. This paper provides a step-by-step tutorial to learn four different ML models to predict drug resistance for E. coli isolates based on genomic data. The tutorial is accessible to beginners, doesn’t require any software to be installed as it is based on Google Colab notebooks, and can be used in undergraduate and graduate classes.

Signaling and gene expression are fundamental to cell biology and developmental biology. Although these topics are highly interrelated, they typically appear in separate units in a course. We use a series of short problem-based learning exercises for two complementary purposes: 1) to promote a better understanding of the mechanisms of signal transduction; and 2) to reinforce students' understanding of cell- and tissue-specific gene expression. Moreover, the exercises promote synthesis of these two topics in the context of real biological problems. The first small-group exercise that we present poses questions about the implications of cell- or tissue-specific expression of signaling molecules, encouraging students to synthesize information when thinking about biological systems. The second exercise asks students to apply the principles of signal transduction to interpret data presented in a case study based on mutations in a MAP kinase pathway that cause Noonan syndrome. Both in-class exercises present opportunities for the students and the instructor to assess the students' understanding of signaling mechanisms. Finally, we include a set of guiding questions on the Wnt signaling pathway as an out-of-class assignment, to be followed by a quiz on Wnt signaling as a summative assessment.

I implemented Unit 5 of the "Climate of Change" module into two weeks of my nonmajors Environmental Science course to cover the concepts of atmospheric science, climate change, and data evaluation.

The BioSkills Guide comprises program- and course-level learning outcomes for the Vision and Change core competencies that elaborate what general biology majors should be able to do by the time they graduate.

Students typically find linear regression analysis of data sets in a biology classroom challenging. These activities could be used in a Biology, Chemistry, Mathematics, or Statistics course. The collection provides student activity files with Excel instructions and Instructor Activity files with Excel instructions and solutions to problems. Students will be able to perform linear regression analysis, find correlation coefficient, create a scatter plot and find the r-square using MS Excel 365. Students will be able to interpret data sets, describe the relationship between biological variables, and predict the value of an output variable based on the input of an predictor variable.

Using oVERT project models students examine examples of extant traditional lizards, snakes and limbless lizards and create phylogenies based on trait and genetic data.

place based cure

This Practical Guide in the Bringing Bioinformatics into the Classroom series introduces the idea of computers as tools to help understand aspects of biology.

This Practical Guide in the Bringing Bioinformatics into the Classroom series introduces the idea of computers as tools to help understand aspects of biology.

This module discusses mental and physical aspects of field safety. The module contains resources for supporting students and technicians in the field and guides supervisors as they write their own Right to Know document.

Genome Solver began as a way to teach undergraduate faculty some basic skills in bioinformatics; no coding or scripting is required. This pre-lesson introduces the BLAST tool.

In this lesson, learners will hear about research that focuses on bacterial antibiotic resistance and biofilm production. Students will see how antibiotic resistance is measured and interpret a graph measuring biofilm production of these bacterial soil isolates. Then, learners view and reflect on an interview with microbiology researcher Dr. Danielle Graham, who collected the data that they interpreted.

Decades of evidence support the premise that undergraduate research experiences are valuable endeavors for science students; however, a lack of knowledge about research and how to get involved can preclude equitable participation. We developed two in-class workshops to teach introductory biology students about undergraduate research experiences. In the first workshop, students are introduced to various types of undergraduate research, including faculty-mentored research, Course Based Undergraduate Research Experiences (CUREs), summer research experiences and research-related jobs and internships. Students hear first-hand accounts about research from undergraduates actively performing research and learn about the benefits and challenges associated with participating. In the second workshop, students learn how to effectively identify and secure research opportunities and engage in an exercise that teaches them how to write a professional email to potential research advisors. Students also work together to develop strategies for building resilience if faced with rejection from a faculty member or internship/job opportunity. The workshops utilize student speakers, think-pair-share activities, and class discussions to engage and inform students. By the end of the workshops, all students are familiar with undergraduate research and have the knowledge and skills needed to identify and secure a research opportunity. The workshops were designed for introductory biology students but can be adapted for students in related majors or at different stages of the academic journey.

Primary Image: Undergraduate research poster session at Sacramento State. Students present the discoveries they made through their course-based research experiences. Photograph was taken in-house. 

Bioassessment is an evaluation of the biological condition of a waterbody using biological surveys and other direct measurements of resident living organisms. Aquatic macroinvertebrates are important indicators of stream health: they are relatively long-lived, differentially sensitive to environmental stressors, and relatively easy to sample. This lesson is a hands-on introduction to the use of stream macroinvertebrates in assessing a stream’s biological condition. Students will learn how to (1) sample and identify stream macroinvertebrates and (2) conduct a rapid bioassessment to quantify ecosystem integrity based on the macroinvertebrate taxa that they collect. The lesson can be conducted with any number of students (although a second instructor would likely be needed for class sizes >20) and is appropriate for undergraduates of all levels.

Ideas for revamping my physiology lab

In this module, students use data from natural history collections to look at range shifts related to climate variables over different time periods.

Data driven curriculum module from Dryad Digital Repository

Use digitized natural history collection occurrence data from the Global Biodiversity Information Facility (GBIF) to map the distribution of the beaver in the state of Oregon from 1800-2020 using QGIS

In this lesson students will learn about the impacts of urbanization, and the conservation challenges it poses to wildlife, in particular avifauna. Introductory ecology topics such as the theory of island biogeography and habitat fragmentation will be discussed, and the student will learn about the beneficial role of native plants in urban residential landscaping. A focal paper will be used to better explore these topics, and data from this observational study will be utilized to introduce generalized linear models in the R programming environment. The student should have some prior basic knowledge of introductory ecology concepts, introductory statistics and have R studio installed on their computer with a basic understanding of this programming language. Upon completion of this lesson, students will learn how urban residential yards contribute to the overall green space in urbanized areas and be used as a conservation strategy to mitigate habitat loss. In R, the student will learn how to conduct statistical analyses and determine if the species area relationship and distance effects of the theory of island biogeography predict bird richness in this study system.

The video and exercise provides insight into how researchers are using digital data resources to investigate biodiversity in prairie fen wetlands.