The information presented in each ActionBioscience.org article has been correlated to the U.S. National Science Education Standards (NSES). Articles may be listed below in more than one category of the standards and educators may determine other curricular applications for the articles.

This fun Web site is part of OLogy, where kids can collect virtual trading cards and create projects with them. Here, they see how DNA is used to solve crimes against animals. The activity starts with an introduction to George Amato, an AMNH scientist who sometimes helps the U.S. government solve mysteries. In a three-part online slide show, students see how Amato earned the title "DNA Detective" in 1993 when he helped the U.S. Fish and Wildlife Service catch someone trying to sneak protected reptile skin into the United States. Then students are challenged to Crack the Code, an online game in which they play DNA detective and determine which of a collection of handbags, clothing, figurines, and other items are made from protected species.

This session introduces bioinformatics using a case study of pathogenic bacterial identification via a Howard Hughes Medical Institute's virtual lab and NCBI web database searches. Another goal is to get the students thinking, writing and talking about the impact of the human genome project. Our students do the exercise independently coming together in the laboratory to present and discuss their findings--this feature makes the exercise feasible for large or small classes with limited laboratory computer resources. The sub-theme of this session is the use of virtual laboratories (vlabs) re-enforcing scientific concepts and methods to supplement lectures, tutorials or "wet" labs.

Covers the basics of R software and the key capabilities of the Bioconductor project (a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology and rooted in the open source statistical computing environment R), including importation and preprocessing of high-throughput data from microarrays and other platforms. Also introduces statistical concepts and tools necessary to interpret and critically evaluate the bioinformatics and computational biology literature. Includes an overview of of preprocessing and normalization, statistical inference, multiple comparison corrections, Bayesian Inference in the context of multiple comparisons, clustering, and classification/machine learning.

The objective of this subject is to teach the design of contemporary information systems for biological and medical data. These data are growing at a prodigious rate, and new information systems are required. This subject will cover examples from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures will be covered. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (C, C++, Java, Lisp, Perl, Python, etc.). A major term project is required of all students. Reading is assigned from the contemporary literature, and there is occasional homework.

" This course teaches the design of contemporary information systems for biological and medical data. Examples are chosen from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (e.g. C, C++, Java, Lisp, Perl, Python). A major term project is required of all students. This subject is open to motivated seniors having a strong interest in biomedical engineering and information system design with the ability to carry out a significant independent project. This course was offered as part of the Singapore-MIT Alliance (SMA) program as course number SMA 5304."

The objective of this subject is to teach the design of contemporary information systems for biological and medical data. These data are growing at a prodigious rate, and new information systems are required. This subject will cover examples from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures will be covered. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (C, C++, Java, Lisp, Perl, Python, etc.). A major term project is required of all students. Reading is assigned from the contemporary literature, and there is occasional homework.

This course will introduce the student to the major concepts of biotechnology. The student will discuss genetic engineering of plants and animals and the current major medical, environmental, and agricultural applications of each. There are also a variety of topics that this course will cover after ranging from nanobiotechnology to environmental biotechnology. Upon successful completion of this course, the student will be able to: identify and describe the fields of biotechnology; compare and contrast forward and reverse genetics and the way they influence biodiversity; compare and contrast systemic studies of the genome, transcriptome, and proteome; explain how genome projects are performed, and discuss the completion and the information processing in these projects; describe and explain the principles of existing gene therapies; design strategies that support genetic counseling; explain and analyze DNA fingerprints, and compare DNA fingerprints to non-DNA biometrics; describe and compare bioremediation technologies in air, water, and soil; design strategies for generating genetically modified organisms, and discuss ethical concerns; discuss emerging fields in biotechnology. (Biology 403)

This course will consider the claim that there is no such thing as race, with a particular emphasis on the question whether races should be thought of as natural kinds: is our concept of race a natural kind concept? Is the term 'race' a natural kind term? If so, is Appiah right to conclude that there are no races? How should one go about "analyzing" the concept of race?

" This course focuses on the algorithmic and machine learning foundations of computational biology, combining theory with practice. We study the principles of algorithm design for biological datasets, and analyze influential problems and techniques. We use these to analyze real datasets from large-scale studies in genomics and proteomics. The topics covered include: Genomes: biological sequence analysis, hidden Markov models, gene finding, RNA folding, sequence alignment, genome assembly Networks: gene expression analysis, regulatory motifs, graph algorithms, scale-free networks, network motifs, network evolution Evolution: comparative genomics, phylogenetics, genome duplication, genome rearrangements, evolutionary theory, rapid evolution "

This course covers the analytical, graphical, and numerical methods supporting the analysis and design of integrated biological systems. Topics include modularity and abstraction in biological systems, mathematical encoding of detailed physical problems, numerical methods for solving the dynamics of continuous and discrete chemical systems, statistics and probability in dynamic systems, applied local and global optimization, simple feedback and control analysis, statistics and probability in pattern recognition.

DNA microarrays are influencing many areas of biology. DNA microarrays allow investigators to measure simultaneously the activity of every gene in a genome. This paper provides the reader with background information, a set of interactive questions, and most importantly, free software (MAGIC Tool) for use in the undergraduate curriculum. MAGIC Tool (www.bio.davidson.edu/MAGIC) resources allow the user to understand how DNA microarray data are analyzed by providing raw data, instructions, mathematical supplements, and free software that works on all computer platforms. MAGIC Tool facilitates the incorporation of microarrays into any upper level biology course.

This workshop, which is half wet lab and half Internet lab, uses DNA sequences to examine the relatedness of different species. DNA from several insect and/or fish species are compared. This chapter includes instructions for extracting DNA from gels and making PCR products. We prepare PCR products to send to a computerized automated sequencing facility. (No radioisotopes are used in this sequencing!) We recover sequence from the facility over the Web as four-color graphics on a computer screen and as text. We make pair-wise DNA sequence comparisons between species with BLAST2 and multi-species comparisons with MultAlin. We see substitutions, insertions, and deletions. Then we make a distance-based evolutionary tree with GeneBee.

This simple OLogy experiment provides insight into genetics by allowing kids to see and hold real DNA. The activity begins with an explanation about how the Moon, itself, doesn't really change, just our view of it. Then kids go to "See the Moon in Action," an interactive illustration of the Moon's orbit around the Earth, where they can see what the Moon looks like from Earth at eight different positions in its orbit. The activity ends with a Moon Watch Log, a printable PDF file, that kids use to observe the Moon for 28 nights and then compile their illustrations into a flip book.

This exercise will give students an interactive opportunity to develop their understanding of DNA structure, how it is packaged into chromosomes, and the mechanisms of transcription and translation.

Virtual world devoted to science, technology and free educational games...

This online article, from the museum's Musings newsletter for educators, provides insight into teaching genetics and building genetic literacy. It looks at ways that teachers can: build their own knowledge base stay abreast of the wave of new information about genetics give their students the tools and techniques to make their way in the genomic age.

Genetics is the branch of biology that studies the means by which traits are passed on from one generation to the next and the causes of similarities and differences between related individuals. In this course, the student will take a close look at chromosomes, DNA, and genes. The student will learn how hereditary information is transferred, how it can change, how it can lead to human disease and be tested to indicate disease, and much more. Upon successful completion of this course, students will be able to: give a brief synopsis of the history of genetics by explaining the fundamental genetic concepts covered in this course as they were discovered through time; identify the links between Mendel's discoveries (often represented by Punnett squares) with mitosis and meiosis, dominance, penetrance, and linkage; recognize the role of simple probability in genetic inheritance; apply advanced genetic concepts, including genetic mapping and transposons, to practical applications, including pedigree analysis and corn kernel color; identify the cause behind several genetic diseases currently prevalent in society (such as color blindness and hemophilia) and recognize the importance of genetic illness throughout history; compare and contrast advanced concepts of chromosomal, bacterial, human, and population genetics; recognize the similarities and differences between nuclear, chloroplast, and mitochondrial DNA; describe the fundamentals of population genetics, calculate gene frequencies in a give scenario, predict future gene frequencies over future generations, and define the role of evolution in gene frequency shift over time; recall, analyze, synthesize, and build on the foundational material to then learn the cutting-edge technological advances in genetics, including genomics, population and evolutionary genetics, and QTL mapping. (Biology 305)

This online article, from the museum's Musings newsletter for educators, looks at the fully functional Genetics Laboratory that was part of the exhibition The Genomic Revolution. It discusses: the significance of the recent sequencing of the human genome in a historical perspective the process visitors underwent during their hour-and-a-half visit to the lab, where they extracted, isolated, visualized, and sequenced their DNA the follow-up activities for visitors on the AMNH Web site.