printer friendly pageBIOE 361: Biomaterials in Regenerative Medicine (MATSCI 381)
Materials design and engineering for regenerative medicine. How materials interact with cells through their micro- and nanostructure, mechanical properties, degradation characteristics, surface chemistry, and biochemistry. Examples include novel materials for drug and gene delivery, materials for stem cell proliferation and differentiation, and tissue engineering scaffolds. Prerequisites: undergraduate chemistry, and cell/molecular biology or biochemistry.
Terms: Spr
| Units: 3
Instructors:
Heilshorn, S. (PI)
;
Suhar, R. (TA)
BIOE 390: Introduction to Bioengineering Research (MED 289)
Preference to medical and bioengineering graduate students with first preference given to Bioengineering Scholarly Concentration medical students. Bioengineering is an interdisciplinary field that leverages the disciplines of biology, medicine, and engineering to understand living systems, and engineer biological systems and improve engineering designs and human and environmental health. Students and faculty make presentations during the course. Students expected to make presentations, complete a short paper, read selected articles, and take quizzes on the material.
Terms: Aut
| Units: 1-2
| Repeatable
5 times
(up to 10 units total)
BIOE 393: Bioengineering Departmental Research Colloquium
Bioengineering department labs at Stanford present recent research projects and results. Guest lecturers. Topics include applications of engineering to biology, medicine, biotechnology, and medical technology, including biodesign and devices, molecular and cellular engineering, regenerative medicine and tissue engineering, biomedical imaging, and biomedical computation. Aut, Win, Spr (Lin, Riedel-Kruse, Barron)
Terms: Aut, Win, Spr
| Units: 1
| Repeatable
for credit
Instructors:
Marsden, A. (PI)
;
Quake, S. (PI)
BIOE 459: Frontiers in Interdisciplinary Biosciences (BIO 459, BIOC 459, CHEM 459, CHEMENG 459, PSYCH 459)
Students register through their affiliated department; otherwise register for
CHEMENG 459. For specialists and non-specialists. Sponsored by the Stanford BioX Program. Three seminars per quarter address scientific and technical themes related to interdisciplinary approaches in bioengineering, medicine, and the chemical, physical, and biological sciences. Leading investigators from Stanford and the world present breakthroughs and endeavors that cut across core disciplines. Pre-seminars introduce basic concepts and background for non-experts. Registered students attend all pre-seminars; others welcome. See
http://biox.stanford.edu/courses/459.html. Recommended: basic mathematics, biology, chemistry, and physics.
Terms: Aut, Win, Spr
| Units: 1
| Repeatable
for credit
Instructors:
Robertson, C. (PI)
BIOMEDIN 205: Precision Practice with Big Data
Primarily for M.D. students; open to other graduate students. Provides an overview of how to leverage large amounts of clinical, molecular, and imaging data within hospitals and in cyberspace--big data--to practice medicine more effectively. Lectures by physicians, researchers, and industry leaders survey how the major methods of informatics can help physicians leverage big data to profile disease, to personalize treatment to patients, to predict treatment response, to discover new knowledge, and to challenge established medical dogma and the current paradigm of clinical decision-making based solely on published knowledge and individual physician experience. May be repeated for credit. Prerequisite: background in biomedicine. Background in computer science can be helpful but not required.
Terms: Aut
| Units: 1
| Repeatable
for credit
Instructors:
Rubin, D. (PI)
;
Yu, A. (TA)
BIOMEDIN 207: Digital Medicine: How health IT is changing the practice of medicine
The widespread use of health IT, such as electronic health records, and of health applications by patients, will radically alter the practice of medicine in the coming decades. This seminar, comprised of guest lectures from industry and academia, will highlight the practical challenges and successes of how health IT has transformed care delivery programs. The seminar will cover current efforts in clinical decision support, patient-centered design, integration with community care, Big Data, and the innovation pipeline for healthcare delivery organizations.
Last offered: Summer 2016
BIOMEDIN 215: Data Driven Medicine
With the spread of electronic health records and increasingly low cost assays for patient molecular data, powerful data repositories with tremendous potential for biomedical research, clinical care and personalized medicine are being built. But these databases are large and difficult for any one specialist to analyze. To find the hidden associations within the full set of data, we introduce methods for data-mining at the internet scale, the handling of large-scale electronic medical records data for machine learning, methods in natural language processing and text-mining applied to medical records, methods for using ontologies for the annotation and indexing of unstructured content as well as semantic web technologies. Prerequisites:
CS 106A;
STATS 216. Recommended: one of
CS 246,
STATS 305, or
CS 22
Terms: Aut
| Units: 3
BIOMEDIN 217: Translational Bioinformatics (BIOE 217, CS 275)
Computational methods for the translation of biomedical data into diagnostic, prognostic, and therapeutic applications in medicine. Topics: multi-scale omics data generation and analysis, utility and limitations of public biomedical resources, machine learning and data mining, issues and opportunities in drug discovery, and mobile/digital health solutions. Case studies and course project. Prerequisites: programming ability at the level of
CS 106A and familiarity with biology and statistics.
Terms: Win
| Units: 4
Instructors:
Gevaert, O. (PI)
;
Mallick, P. (PI)
;
Wall, D. (PI)
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more instructors for BIOMEDIN 217 »
Instructors:
Gevaert, O. (PI)
;
Mallick, P. (PI)
;
Wall, D. (PI)
;
Gloudemans, M. (TA)
;
McInnes, G. (TA)
;
Shenoy, A. (TA)
BIOMEDIN 218: Translational Bioinformatics Lectures
Same content as
BIOMEDIN 217; for medical and graduate students who attend lectures and participate in limited assignments and final project. Computational methods for the translation of biomedical data into diagnostic, prognostic, and therapeutic applications in medicine. Topics: multi-scale omics data generation and analysis, utility and limitations of public biomedical resources, machine learning and data mining, issues and opportunities in drug discovery, and mobile/digital health solutions. Case studies.nPrerequisites: programming ability at the level of
CS 106A and familiarity with biology and statistics.
Terms: Win
| Units: 2
Instructors:
Gevaert, O. (PI)
;
Wall, D. (PI)
BIOMEDIN 225: Data Driven Medicine: Lectures
Lectures for
BIOMEDIN 215.With the spread of electronic health records and increasingly low cost assays for patient molecular data, powerful data repositories with tremendous potential for biomedical research, clinical care and personalized medicine are being built. But these databases are large and difficult for any one specialist to analyze. To find the hidden associations within the full set of data, we introduce methods for data-mining at the internet scale, the handling of large-scale electronic medical records data for machine learning, methods in natural language processing and text-mining applied to medical records, methods for using ontologies for the annotation and indexing of unstructured content as well as semantic web technologies. Prerequisites: familiarity with statistics (
STATS 216) and biology.
Terms: Aut
| Units: 2
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