Systems Biology—Biomedical Modeling
Members of the Systems Biology Center New York developed a course at Icahn School of Medicine that introduces first-year graduate students to computational principles and approaches. There are a total of 13 Teaching Resources published in sequential issues of Science Signaling. Each of the Teaching Resources provides lecture notes, slides, problem sets, and answer keys.
- Overview: Systems Biology--Biomedical Modeling
- Introduction to Statistical Methods to Analyze Large Data Sets: Principal Components Analysis
- Introduction to Statistical Methods for Analyzing Large Data Sets: Gene-Set Enrichment Analysis
- Introduction to Network Analysis in Systems Biology
- An Introduction to Dynamical Systems
- An Introduction to MATLAB
- Obtaining and Estimating Kinetic Parameters from the Literature
- Biomedical Model Fitting and Error Analysis
- Computational Modeling of the Cell Cycle
- Developing Models in Virtual Cell
- Simulations of Stochastic Biological Phenomena
- Probabilistic Reasoning in Data Analysis
Training in Systems Pharmacology: Predoctoral Program in Pharmacology and Systems Biology at Icahn School of Medicine
Abstract: Our recently developed predoctoral training program in pharmacology and systems biology prepares students to become experts in systems-level models of disease that identify therapeutic targets and predict adverse effects or new uses of existing therapeutics. Multiple computational modeling modes are introduced throughout a curriculum that integrates basic cell and molecular sciences with the physiology and pathophysiology of disease states. Problem-based learning exercises enable students from different experimental and computational backgrounds to design experiments and interpret data quantitatively.
Citation: Sobie EA, Jenkins SL, Iyengar R, Krulwich TA. Training in systems pharmacology: predoctoral program in pharmacology and systems biology at Icahn School of Medicine. Clin Pharmacol Ther. 2010 Jul;88(1):19-22.
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Using Web-Based Discussion Forums as a Model of the Peer-Review Process and a Tool for Assessment
Abstract: This Teaching Resource describes how to use an online asynchronous discussion as a mechanism to introduce students to the peer-review process, as well as to assess student performance and understanding. This method was applied to a graduate course on signal transduction and the Teaching Resource includes a syllabus, detailed plan for incorporating the online discussion, sample journal club questions, and sample student responses to the discussion forum, faculty responses, and student revisions.
Citation: Jenkins SL, Iyengar R, Diverse-Pierluissi MA, Chan AM, Devi LA, Sobie EA, Ting AT, Weinstein DC. Teaching resources. Using web-based discussion forums as a model of the peer-review process and a tool for assessment. Sci Signal. 2008;1(9):tr2.
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Inquiry Learning. Integrating Content Detail and Critical Reasoning by Peer Review
Abstract: Classroom lectures by experts in combination with journal clubs and Web-based discussion forums help graduate students develop critical reasoning skills.
Citation: Iyengar R, Diverse-Pierluissi MA, Jenkins SL, Chan AM, Devi LA, Sobie EA, Ting AT, Weinstein DC. Inquiry learning. Integrating content detail and critical reasoning by peer review. Science. 2008 Feb 29;319(5867):1189-90.
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Cell Signaling Systems: A Course for Graduate Students
Abstract: This course uses the primary literature to develop a systems-level understanding of the information flow through the various cell signaling pathways and networks. Current areas of research activities in the experimental and theoretical understanding of cell signaling research are highlighted. This Teaching Resource describes a sample syllabus and organization for this course. Each lecture is 2 hours. After each set of lectures, there is a 2-hour discussion period during which students present an in-depth analysis of a primary literature article, selected in consultation with the lecturer.
Citation: Iyengar R, Diverse-Pierluissi M, Weinstein D, Devi LA. Teaching resources. Cell signaling systems: a course for graduate students. Sci STKE. 2005 Feb 1;2005(269):tr3.
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