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.

Dr. Laura Elnitski, Head of the Genomic Functional Analysis Section, Genome Technology Branch NHGRI/NIHDr. Elnitski uses experimental and Bioinformatic methods to discover non-coding functional elements in the human genome. On 7 March 2008, Dr. Elnitski came to MSU-Bozeman to participate in the Women In Bioinformatics Seminar Series.

The Biology course is a first-year course in biology at the high school level and involves the scientific study of living organisms. The course considers the interactions among the vast number of organisms that inhabit planet Earth. It presents the basic form and function of these organisms, from cells to organ systems, from simple viruses to complex humans. It delves into interactions between organisms, and between an organism and its environment. It also looks into how biotechnology is used to improve our health and daily lives.

- Understand the form and function of microorganisms
- Understand the form and function of plants
- Understand the form and function of animals
- Understand the workings of human biological systems
- Understand biology as it relates to the Earth's environment

" 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 "

The goal of this exercise is to show how we can relate the results of two independent gene expression datasets to each other. In the case where one dataset provides "transcriptional signatures" of known oncogenic pathways, we can get clues as to which oncogenic pathways may be represented within the results obtained from another dataset. Lab for the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

The eukaryotic genome is packaged as chromatin with nucleosomes comprising its basic structural unit, but the detailed structure of chromatin and its dynamic remodeling in terms of individual nucleosome positions has not been completely defined experimentally for any genome. We used ultra-high–throughput sequencing to map the remodeling of individual nucleosomes throughout the yeast genome before and after a physiological perturbation that causes genome-wide transcriptional changes. Nearly 80% of the genome is covered by positioned nucleosomes occurring in a limited number of stereotypical patterns in relation to transcribed regions and transcription factor binding sites. Chromatin remodeling in response to physiological perturbation was typically associated with the eviction, appearance, or repositioning of one or two nucleosomes in the promoter, rather than broader region-wide changes. Dynamic nucleosome remodeling tends to increase the accessibility of binding sites for transcription factors that mediate transcriptional changes. However, specific nucleosomal rearrangements were also evident at promoters even when there was no apparent transcriptional change, indicating that there is no simple, globally applicable relationship between chromatin remodeling and transcriptional activity. Our study provides a detailed, high-resolution, dynamic map of single-nucleosome remodeling across the yeast genome and its relation to global transcriptional changes.

Computational laboratory: Starting from a set of breast cancer BACs (bacterial artificial chromosomes) End Sequence Profiling (ESP) is performed. ESP analysis sequences the ends of insert DNA in order to characterize genomic rearrangements that may be involved in breast cancer progression. In this study, genomic rearrangements are characterized from 100 breast cancer BACs and 10,000 Fosmids (derived from a pool of the 100 originating BAC) using ESP. Analysis and comparison of both BAC and Fosmid based data sets will be performed. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

Lecture on gene expression studies of cancer and gene transcription signatures. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

Lecture on gene expression studies of cancer and gene transcription signatures. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

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 is an introduction to the Genome Variation Server at the University of Washington sponsored by GVS. You can get more freely available training materials on GVS including a longer introductory tutorial (40 minutes), slides, handouts and exercises at OpenHelix GVS Tutorial or visit the resource at GVS

Insights into cancer biology from the study of base pair-level changes in coding sequences. Genotyping vs. resequencing. Identifying cancer-related genes using association studies. Use of next-generation sequencing technologies to map chromosomal aberrations in cancer genomes. PCR-based resequencing vs. array-based enrichment. Using recurrence, pathway enrichment, and other signatures of positive selection to identify "driver" somatic mutations involved in cancer progression. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine

Overview of some of the whole-genome sequences available: Arabidopsis, C. elegans, Drosophila, H. sapiens, and M. musculus.

This course reviews the key genomic technologies and computational approaches that are driving advances in prognostics, diagnostics, and treatment. Throughout the semester, emphasis will return to issues surrounding the context of genomics in medicine including: what does a physician need to know? what sorts of questions will s/he likely encounter from patients? how should s/he respond? Lecturers will guide the student through real world patient-doctor interactions. Outcome considerations and socioeconomic implications of personalized medicine are also discussed. The first part of the course introduces key basic concepts of molecular biology, computational biology, and genomics. Continuing in the informatics applications portion of the course, lecturers begin each lecture block with a scenario, in order to set the stage and engage the student by showing: why is this important to know? how will the information presented be brought to bear on medical practice? The final section presents the ethical, legal, and social issues surrounding genomic medicine. A vision of how genomic medicine relates to preventative care and public health is presented in a discussion forum with the students where the following questions are explored: what is your level of preparedness now? what challenges must be met by the healthcare industry to get to where it needs to be?

This Web site, created to complement the museum's The Genomic Revolution exhibition, examines the mapping of the genome and its implications.

A research team led by scientists at MD Anderson Cancer Center report that 2 specific common inherited genetic variations are associated with increased risk of lung cancer for smokers and former smokers. Dr. Amos talks about how the findings are a major step forward in identifying those at high risk for non-small cell lung cancer and for understanding how smoking and genetic factors interact to cause the disease.

Play a game and find out about a Nobel Prize awarded discovery or work! You are practicing as an ECG technician in a health clinic Your job is to perform ECGs on patients referred to you by medical doctors. This game lets you explore the key elements of the electrocardiogram, and in the end there will be a task for you to complete.

Play a game and find out about a Nobel Prize awarded discovery or work! We need several thousands of different proteins in our body. It is the genetic material, the DNA, in our cells that provides the information needed to produce all these proteins. The genetic information is stored in molecules represented by three-letter words called codons. These words need to be translated to the "protein language" of 20 words, each representing an amino acid. Translate the code and challenge a friend to a five in a row game online!

MicrobeWorld visits The Maloy Lab at San Diego State University to talk with Professor Stanley Maloy and three grad students, Dave Matthews, Gerardo Perez and Veronica Casas, about their research. The Maloy Lab focuses on the genetics and physiology of Salmonella and bacteriophage that infect Salmonella. Maloy and his students use a combination of genetic, molecular, biochemical, and genomic approaches to answer questions about the uptake of DNA from bacteriophage, transfer of genes between bacteria and phage, and the evolution of pathogenesis.