" This course does not seek to provide answers to ethical questions. Instead, the course hopes to teach students two things. First, how do you recognize ethical or moral problems in science and medicine? When something does not feel right (whether cloning, or failing to clone) ‰ŰÓ what exactly is the nature of the discomfort? What kind of tensions and conflicts exist within biomedicine? Second, how can you think productively about ethical and moral problems? What processes create them? Why do people disagree about them? How can an understanding of philosophy or history help resolve them? By the end of the course students will hopefully have sophisticated and nuanced ideas about problems in bioethics, even if they do not have comfortable answers."

Our goal is to present the key observations and unifying concepts upon which modern biology is based; it is not a survey of all biology! Once understood, these foundational observations and concepts should enable you to approach any biological process, from disease to kindness, from a scientific perspective. To understand biological systems we need to consider them from two complementary perspectives; how they came to be (the historic, that is, evolutionary) and how their structures, traits, and behaviors are produced (the mechanistic, that is, the physicochemical)

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 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.

Imagine you are a salesman needing to visit 100 cities connected by a set of roads. Can you do it while stopping in each city only once? Even a supercomputer working at 1 trillion operations per second would take longer than the age of the universe to find a solution when considering each possibility in turn. In 1994, Leonard Adleman published a paper in which he described a solution, using the tools of molecular biology, for a smaller 7-city example of this problem. His paper generated enormous scientific and public interest, and kick-started the field of Biological Computing, the main subject of this discussion based seminar course. Students will analyze the Adleman paper, and the papers that preceded and followed it, with an eye for identifying the engineering and scientific aspects of each paper, emphasizing the interplay of these two approaches in the field of Biological Computing. This course is appropriate for both biology and non-biology majors. Care will be taken to fill in any knowledge gaps for both scientists and engineers.

This course illustrates how knowledge and principles of biology, biochemistry, and engineering are integrated to create new products for societal benefit. It uses a case study format to examine recently developed products of pharmaceutical and biotechnology industries: how a product evolves from initial idea, through patents, testing, evaluation, production, and marketing. Emphasizes scientific and engineering principles; the responsibility scientists, engineers, and business executives have for the consequences of their technology; and instruction and practice in written and oral communication. The topic focus of this class will vary from year to year. This version looks at inflammation underlying many diseases, specifically its role in cancer, diabetes, and cardiovascular disease.

This course covers sensing and measurement for quantitative molecular/cell/tissue analysis, in terms of genetic, biochemical, and biophysical properties. Methods include light and fluorescence microscopies; electro-mechanical probes such as atomic force microscopy, laser and magnetic traps, and MEMS devices; and the application of statistics, probability and noise analysis to experimental data.

In this course problems from biological engineering are used to develop structured computer programming skills and explore the theory and practice of complex systems design and construction.

This is a syllabus for a first-semester introductory biology class, including reading links for current news articles related to the course topics as well as an OpenStax textbook.

A biology site to house Biology 211: General Biology I, Biology 231: Microbiology, and Biology 251: Genetics at Guttman College.

Biology is designed to cover the scope and sequence requirements of a typical two-semester biology course for science majors. The text provides comprehensive coverage of foundational research and core biology concepts through an evolutionary lens. Biology includes rich features that engage students in scientific inquiry, highlight careers in the biological sciences, and offer everyday applications. The book also includes clicker questions to help students understand—and apply—key concepts.

Lab Manual for BIO101 at Mt Hood Community College. The associated textbook is available at https://openoregon.pressbooks.pub/mhccbiology101/

An introduction to biology intended for non-science majors.  Focus areas include chemical foundations, cell structure and division, genetics, and evolution.

This site is an OER for BIology II and contains all the materials needed for the course including lecture slides and labs.

This template course was developed from generally available open educational resources (OER) in use at multiple institutions, drawing mostly from a primary work published by OpenStax College Concepts of Biology, but also including additional open works from various sources as noted in attributions on each page of materials.

This course outline for Biology II includes resources for both students and instructors including the OpenStax Biology textbook, lecture schedule, lecture slides, labs, list of related resources and Interdisciplinary (ID) Biology II topics and assignments.

Students perform a literature review on a biology topic, choose 2-3 papers published in scientific journals to discuss in their assignment, provide a final opinion on the topic, and some voluntarily present on their selected topic.

"This course covers the principles of materials science and cell biology underlying the design of medical implants, artificial organs, and matrices for tissue engineering. Methods for biomaterials surface characterization and analysis of protein adsorption on biomaterials. Molecular and cellular interactions with biomaterials are analyzed in terms of unit cell processes, such as matrix synthesis, degradation, and contraction. Mechanisms underlying wound healing and tissue remodeling following implantation in various organs. Tissue and organ regeneration. Design of implants and prostheses based on control of biomaterials-tissue interactions. Comparative analysis of intact, biodegradable, and bioreplaceable implants by reference to case studies. Criteria for restoration of physiological function for tissues and organs."