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.
Study and discussion of computational approaches and algorithms for contemporary problems in functional genomics. Topics include DNA chip design, experimental data normalization, expression data representation standards, proteomics, gene clustering, self-organizing maps, Boolean networks, statistical graph models, Bayesian network models, continuous dynamic models, statistical metrics for model validation, model elaboration, experiment planning, and the computational complexity of functional genomics problems.
DNA microarray analysis is one of the fastest-growing new technologies in the field of genetic research. Scientists are using DNA microarrays to investigate everything from cancer to pest control. Now you can do your own DNA microarray experiment! Here you will use a DNA microarray to investigate the differences between a healthy cell and a cancer cell.
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?
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