GENE 104Q: Law and the Biosciences
Preference to sophomores. Focus is on human genetics; also assisted reproduction and neuroscience. Topics include forensic use of DNA, genetic testing, genetic discrimination, eugenics, cloning, pre-implantation genetic diagnosis, neuroscientific methods of lie detection, and genetic or neuroscience enhancement. Student presentations on research paper conclusions.
Terms: Spr
| Units: 3
| UG Reqs: WAY-ER, Writing 2
Instructors:
Greely, H. (PI)
GENE 199: Undergraduate Research
Students undertake investigations sponsored by individual faculty members. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum
| Units: 1-18
| Repeatable
for credit
Instructors:
Altman, R. (PI)
;
Baker, J. (PI)
;
Barna, M. (PI)
;
Bassik, M. (PI)
;
Brown, P. (PI)
;
Brunet, A. (PI)
;
Bustamante, C. (PI)
;
Calos, M. (PI)
;
Cherry, J. (PI)
;
Cohen, S. (PI)
;
Fire, A. (PI)
;
Francke, U. (PI)
;
Fuller, M. (PI)
;
Gitler, A. (PI)
;
Greenleaf, W. (PI)
;
Herzenberg, L. (PI)
;
Herzenberg, L. (PI)
;
Kay, M. (PI)
;
Kim, S. (PI)
;
Li, J. (PI)
;
Lipsick, J. (PI)
;
Ormond, K. (PI)
;
Pringle, J. (PI)
;
Pritchard, J. (PI)
;
Quake, S. (PI)
;
Sage, J. (PI)
;
Sherlock, G. (PI)
;
Sidow, A. (PI)
;
Snyder, M. (PI)
;
Tang, H. (PI)
;
Villeneuve, A. (PI)
;
Vollrath, D. (PI)
;
Winslow, M. (PI)
GENE 200: Genetics and Developmental Biology Training Camp (DBIO 200)
Open to first year Department of Genetics and Developmental Biology students, to others with consent of instructors. Introduction to basic manipulations, both experimental and conceptual, in genetics and developmental biology.
Terms: Aut
| Units: 1
Instructors:
Fire, A. (PI)
;
Greenleaf, W. (PI)
;
Kingsley, D. (PI)
...
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Instructors:
Fire, A. (PI)
;
Greenleaf, W. (PI)
;
Kingsley, D. (PI)
;
Li, J. (PI)
;
Montgomery, S. (PI)
;
Vollrath, D. (PI)
;
Winslow, M. (PI)
GENE 202: Human Genetics
Utilizes lectures and small group activities to develop a working knowlege of human genetics as applicable to clinical medicine. Basic principles of inheritance, risk assessment, and population genetics are illustrated using examples drawn from diverse areas of medical genetics practice including prenatal, pediatric, adult and cancer genetics. Practical aspects of molecular and cytogenetic diagnostic methods emphasized. Existing and emerging treatment strategies for single gene disorders are also covered. Prerequisites: biochemistry, basic genetics.
Terms: Aut
| Units: 4
Instructors:
Bernstein, J. (PI)
GENE 205: Advanced Genetics
For PhD students in any of the Biosciences Departments and Programs at Stanford University. Emphasis on developing the ability to solve problems using genetic ideas and methods, to understand the nature and reliability of genetic inference, and to apply genetic reasoning to biological research. Weekly paper discussions based on original research papers that define or illustrate the ideas and techniques covered in the lecture.
Terms: Win
| Units: 3
Instructors:
Fire, A. (PI)
;
Pringle, J. (PI)
;
Pritchard, J. (PI)
...
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Instructors:
Fire, A. (PI)
;
Pringle, J. (PI)
;
Pritchard, J. (PI)
;
Villeneuve, A. (PI)
;
Winslow, M. (PI)
GENE 209: Current Topics in Human, Population, and Statistical Genomics
Intensive seminar/workshop. Topics, drawn from current and past literature, may include: assessing and population genetic analysis of genomic variation; genome-to-phenome mapping; reconstructing demographic history from genome sequence data; domestication genomics; host-pathogen genome evolution; detecting signatures of selection; experimental design in human genetics; linkage and association mapping; ethical and social issues in human, plant, and animal genetics research. Emphasis on analysis and logic or experimental and observational genomics research. Faculty-led discussion with evaluation of response papers, problem sets, and intensive course project. May be repeated for credit.
Terms: Spr
| Units: 2
| Repeatable
for credit
Instructors:
Bustamante, C. (PI)
GENE 210: Genomics and Personalized Medicine (DBIO 220)
Principles of genetics underlying associations between genetic variants and disease susceptibility and drug response. Topics include: genetic and environmental risk factors for complex genetic disorders; design and interpretation of genome-wide association studies; pharmacogenetics; full genome sequencing for disease gene discovery; population structure and genetic ancestry; use of personal genetic information in clinical medicine; ethical, legal, and social issues with personal genetic testing. Hands-on workshop making use of personal or publicly available genetic data. Prerequisite:
GENE 202,
Gene 205 or
BIOS 200.
Terms: Spr
| Units: 3
Instructors:
Gitler, A. (PI)
;
Kim, S. (PI)
GENE 211: Genomics
Genome evolution, organization, and function; technical, computational, and experimental approaches; hands-on experience with representative computational tools used in genome science; and a beginning working knowledge of PERL.
Terms: Win
| Units: 3
Instructors:
Cherry, J. (PI)
;
Sherlock, G. (PI)
GENE 212: Introduction to Biomedical Informatics Research Methodology (BIOE 212, BIOMEDIN 212, CS 272)
Hands-on software building. Student teams conceive, design, specify, implement, evaluate, and report on a software project in the domain of biomedicine. Creating written proposals, peer review, providing status reports, and preparing final reports. Guest lectures from professional biomedical informatics systems builders on issues related to the process of project management. Software engineering basics. Prerequisites:
BIOMEDIN 210, 211, 214, 217 or consent of instructor.
Terms: Spr
| Units: 3
Instructors:
Altman, R. (PI)
GENE 214: Representations and Algorithms for Computational Molecular Biology (BIOE 214, BIOMEDIN 214, CS 274)
Topics: introduction to bioinformatics and computational biology, algorithms for alignment of biological sequences and structures, computing with strings, phylogenetic tree construction, hidden Markov models, Gibbs Sampling, basic structural computations on proteins, protein structure prediction, protein threading techniques, homology modeling, molecular dynamics and energy minimization, statistical analysis of 3D biological data, integration of data sources, knowledge representation and controlled terminologies for molecular biology, microarray analysis, machine learning (clustering and classification), and natural language text processing. Prerequisites: programming skills; consent of instructor for 3 units.
Terms: Aut
| Units: 3-4
Instructors:
Altman, R. (PI)
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