Courses tagged with "Nutrition" (6413)

6.811: Principles and Practice of Assistive Technology (PPAT) is an interdisciplinary, project-based course, centered around a design project in which small teams of students work closely with a person with a disability in the Cambridge area to design a device, piece of equipment, app, or other solution that helps them live more independently.

This course serves as a description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Topics covered include drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules, and economic and financial considerations of the drug development process. A multidisciplinary perspective is provided by the faculty, who represent clinical, life, and management sciences. Various industry guests also participate.

This course serves as a description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Topics covered include drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules, and economic and financial considerations of the drug development process. A multidisciplinary perspective is provided by the faculty, who represent clinical, life, and management sciences. Various industry guests also participate.

This course serves as a description and critical assessment of the major issues and stages of developing a pharmaceutical or biopharmaceutical. Topics covered include drug discovery, preclinical development, clinical investigation, manufacturing and regulatory issues considered for small and large molecules, and economic and financial considerations of the drug development process. A multidisciplinary perspective is provided by the faculty, who represent clinical, life, and management sciences. Various industry guests also participate.

This course helps in developing skills as science communicators through projects and analysis of theoretical principles. Case studies explore the emergence of popular science communication over the past two centuries and consider the relationships among authors, audiences and media. Project topics are identified early in the term and students work with MIT Museum staff. Projects may include physical exhibits, practical demonstrations, or scripts for public programs.

The principles and practice of tissue engineering (and regenerative medicine) are taught by faculty of the Harvard-MIT Division of Health Sciences and Technology (HST) and Tsinghua University, Beijing, China. The principles underlying strategies for employing selected cells, biomaterial scaffolds, soluble regulators or their genes, and mechanical loading and culture conditions, for the regeneration of tissues and organs in vitro and in vivo are addressed. Differentiated cell types and stem cells are compared and contrasted for this application, as are natural and synthetic scaffolds. Methodology for the preparation of cells and scaffolds in practice is described. The rationale for employing selected growth factors is covered and the techniques for incorporating their genes into the scaffolds are examined. Discussion also addresses the influence of environmental factors including mechanical loading and culture conditions (e.g., static versus dynamic). Methods for fabricating tissue-engineered products and devices for implantation are taught. Examples of tissue engineering-based procedures currently employed clinically are analyzed as case studies.

Archived webcast lecture videos for the Fall 2008 version of this class can be found at the HST.535 Fall 2008 website.

Principles of Applied Mathematics is a study of illustrative topics in discrete applied mathematics including sorting algorithms, information theory, coding theory, secret codes, generating functions, linear programming, game theory. There is an emphasis on topics that have direct application in the real world.

This course was recently revised to meet the MIT Undergraduate Communication Requirement (CR). It covers the same content as 18.310, but assignments are structured with an additional focus on writing.

18.311 Principles of Continuum Applied Mathematics covers fundamental concepts in continuous applied mathematics, including applications from traffic flow, fluids, elasticity, granular flows, etc. The class also covers continuum limit; conservation laws, quasi-equilibrium; kinematic waves; characteristics, simple waves, shocks; diffusion (linear and nonlinear); numerical solution of wave equations; finite differences, consistency, stability; discrete and fast Fourier transforms; spectral methods; transforms and series (Fourier, Laplace). Additional topics may include sonic booms, Mach cone, caustics, lattices, dispersion, and group velocity.

This course introduces the design of feedback control systems as applied to a variety of air and spacecraft systems. Topics include the properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability, the Root locus method, Nyquist criterion, frequency-domain design, and state space methods.

This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their application, taken from the disciplines of artificial intelligence and operations research.

Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, and machine learning. Optimization paradigms include linear programming, integer programming, and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes.

This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their application, taken from the disciplines of artificial intelligence and operations research.

Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, and machine learning. Optimization paradigms include linear programming, integer programming, and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes.

Principles of Biochemistry integrates an introduction to the structure of macromolecules and a biochemical approach to cellular function. Topics addressing protein function will include enzyme kinetics, the characterization of major metabolic pathways and their interconnection into tightly regulated networks, and the manipulation of enzymes and pathways with mutations or drugs. An exploration of simple cells (red blood cells) to more complex tissues (muscle and liver) will be used as a framework to discuss the progression in metabolic complexity. Learners will also develop problem solving and analytical skills that are more generally applicable to the life sciences.

New in version 2, learners will explore how alteration of these metabolic pathways relates to the development and progression of some human diseases.

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Image credit: PDB ID 2DN1, 2DN2

Park S-Y, Yokoyama T, Shibayama N, Shiro Y, Tame JRH (2006) 1.25 A resolution crystal structures of human haemoglobin in the oxy, deoxy and carbonmonoxy forms. J Mol Biol 360: 690–701.

5.112 is an introductory chemistry course for students with an unusually strong background in chemistry. Knowledge of calculus equivalent to MIT course 18.01 is recommended. Emphasis is on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis. The course also covers applications of basic principles to problems in metal coordination chemistry, organic chemistry, and biological chemistry.

This course provides an introduction to the chemistry of biological, inorganic, and organic molecules. The emphasis is on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis.

In an effort to illuminate connections between chemistry and biology, a list of the biology-, medicine-, and MIT research-related examples used in 5.111 is provided in Biology-Related Examples.

Acknowledgements

Development and implementation of the biology-related materials in this course were funded through an HHMI Professors grant to Prof. Catherine L. Drennan.

This course provides an introduction to the chemistry of biological, inorganic, and organic molecules. The emphasis is on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria, chemical kinetics, and catalysis. One year of high school chemistry is the expected background for this freshman-level course.

The aims include developing a unified and intuitive view of how electronic structure controls the three-dimensional shape of molecules, the physical and chemical properties of molecules in gases, liquids and solids, and ultimately the assembly of macromolecules as in polymers and DNA. Relationships between chemistry and other fundamental sciences such as biology and physics are emphasized, as are the relationships between the science of chemistry to its applications in environmental science, atmospheric chemistry and electronic devices. 

Acknowledgements

Professor Drennan would like to acknowledge the contributions of MIT Lecturer Dr. Elizabeth Vogel Taylor, Professor Sylvia Ceyer, and Professor Robert Silbey to the development of this course and its materials.

6.826 provides an introduction to the basic principles of computer systems, with emphasis on the use of rigorous techniques as an aid to understanding and building modern computing systems. Particular attention is paid to concurrent and distributed systems. Topics covered include: specification and verification, concurrent algorithms, synchronization, naming, networking, replication techniques (including distributed cache management), and principles and algorithms for achieving reliability.

This course introduces the basic mathematical and programming principles that underlie much of Computer Science. Students will refine their programming skills as well as learn the basics of creating efficient solutions to common computational problems.