Courses tagged with "Nutrition" (6413)
Do you have an interest in biology and quantitative tools? Do you know computational methods but do not realize how they apply to biological problems? Do you know biology but do not understand how scientists really analyze complicated data? 7.QBWx: Quantitative Biology Workshop is designed to give learners exposure to the application of quantitative tools to analyze biological data at an introductory level. For the last few years, the Biology Department of MIT has run this workshop-style course as part of a one-week outreach program for students from other universities. With 7.QBWx, we can give more learners from around the world the chance to discover quantitative biology. We hope that this series of workshops encourages learners to explore new interests and take more biology and computational courses.
We expect that learners from 7.00x Introduction to Biology – The Secret of Life or an equivalent course can complete this workshop-based course without a background in programming. The course content will introduce programming languages but will not teach any one language in a comprehensive manner. The content of each week varies. We want learners to have an introduction to multiple languages and tools to find a topic that they would want to explore more. Participants with programming experience will find some weeks easier than students with only biology experience, while those with a biology background should find the week on genetics easier. We recommend that learners try to complete each week to find what interests them the most.
Workshop Content Creators and Residential Leaders
Gregory Hale, Michael Goard, Ph.D., Ben Stinson, Kunle Demuren, Sara Gosline, Ph.D., Glenna Foight, Leyla Isik, Samir El-Boustani, Ph.D., Gerald Pho, and Rajeev Rikhye
Residential Outreach Workshop Organizer and Creator
Mandana Sassanfar, Ph.D.
This workshop includes activities on the following biological topics: population biology, biochemical equilibrium and kinetics, molecular modeling of enzymes, visual neuroscience, genetics, gene expression and development, and genomics. The tools and programming languages include MATLAB, PyMOL, StarGenetics, Python, and R. This course does not require learners to download MATLAB. All MATLAB activities run and are graded within the edX platform. We do recommend that participants download a few other free tools for the activities so that they learn how to use the same tools and programs that scientists use.
This course provides a foundation in the following four areas: evolutionary and population genetics; comparative genomics; structural genomics and proteomics; and functional genomics and regulation.
In this subject, we consider two basic topics in cellular biophysics, posed here as questions:
- Which molecules are transported across cellular membranes, and what are the mechanisms of transport? How do cells maintain their compositions, volume, and membrane potential?
- How are potentials generated across the membranes of cells? What do these potentials do?
Although the questions posed are fundamentally biological questions, the methods for answering these questions are inherently multidisciplinary. As we will see throughout the course, the role of mathematical models is to express concepts precisely enough that precise conclusions can be drawn. In connection with all the topics covered, we will consider both theory and experiment. For the student, the educational value of examining the interplay between theory and experiment transcends the value of the specific knowledge gained in the subject matter.
This course is jointly offered through four departments, available to both undergraduates and graduates.
In this subject, we consider two basic topics in cellular biophysics, posed here as questions:
- Which molecules are transported across cellular membranes, and what are the mechanisms of transport? How do cells maintain their compositions, volume, and membrane potential?
- How are potentials generated across the membranes of cells? What do these potentials do?
Although the questions posed are fundamentally biological questions, the methods for answering these questions are inherently multidisciplinary. As we will see throughout the course, the role of mathematical models is to express concepts precisely enough that precise conclusions can be drawn. In connection with all the topics covered, we will consider both theory and experiment. For the student, the educational value of examining the interplay between theory and experiment transcends the value of the specific knowledge gained in the subject matter.
This course is jointly offered through four departments, available to both undergraduates and graduates.
In this subject, we consider two basic topics in cellular biophysics, posed here as questions:
- Which molecules are transported across cellular membranes, and what are the mechanisms of transport? How do cells maintain their compositions, volume, and membrane potential?
- How are potentials generated across the membranes of cells? What do these potentials do?
Although the questions posed are fundamentally biological questions, the methods for answering these questions are inherently multidisciplinary. As we will see throughout the course, the role of mathematical models is to express concepts precisely enough that precise conclusions can be drawn. In connection with all the topics covered, we will consider both theory and experiment. For the student, the educational value of examining the interplay between theory and experiment transcends the value of the specific knowledge gained in the subject matter.
This course is jointly offered through four departments, available to both undergraduates and graduates.
In this subject, we consider two basic topics in cellular biophysics, posed here as questions:
- Which molecules are transported across cellular membranes, and what are the mechanisms of transport? How do cells maintain their compositions, volume, and membrane potential?
- How are potentials generated across the membranes of cells? What do these potentials do?
Although the questions posed are fundamentally biological questions, the methods for answering these questions are inherently multidisciplinary. As we will see throughout the course, the role of mathematical models is to express concepts precisely enough that precise conclusions can be drawn. In connection with all the topics covered, we will consider both theory and experiment. For the student, the educational value of examining the interplay between theory and experiment transcends the value of the specific knowledge gained in the subject matter.
This course is jointly offered through four departments, available to both undergraduates and graduates.
This course elaborates on the application of the principles of energy and mass flow to major human organ systems. It discusses mechanisms of regulation and homeostasis. It also discusses anatomical, physiological, and pathophysiological features of the cardiovascular, respiratory, and renal systems. There is emphasis on those systems, features, and devices that are most illuminated by the methods of physical sciences.
This course develops logical, empirically based arguments using statistical techniques and analytic methods. Elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation are covered. Emphasis is on the use and limitations of analytical techniques in planning practice.
This course provides students with a rigorous introduction to Statistics for Political Science. Topics include basic mathematical tools used in social science modeling and statistics, probability theory, theory of estimation and inference, and statistical methods, especially differences of means and regression. The course is often taken by students outside of political science, especially those in business, urban studies, and various fields of public policy, such as public health. Examples draw heavily from political science, but some problems come from other areas, such as labor economics.
This course is the second semester in the statistics sequence for political science and public policy offered in the Political Science Department at MIT. The intellectual thrust of the course is a presentation of statistical models for estimating causal effects of variables. The model of an effect is a conditional mean (though we might imagine other effect). The notion of causality is the effect of one variable on another holding all else constant.
This course is an introduction to quantum computational complexity theory, the study of the fundamental capabilities and limitations of quantum computers. Topics include complexity classes, lower bounds, communication complexity, proofs, advice, and interactive proof systems in the quantum world. The objective is to bring students to the research frontier.
This course provides an introduction to the theory and practice of quantum computation. Topics covered include: physics of information processing, quantum logic, quantum algorithms including Shor's factoring algorithm and Grover's search algorithm, quantum error correction, quantum communication, and cryptography.
How can you tell a secret when everyone is able to listen in? In this course, you will learn how to use quantum effects, such as quantum entanglement and uncertainty, to implement cryptographic tasks with levels of security that are impossible to achieve classically.
This interdisciplinary course is an introduction to the exciting field of quantum cryptography, developed in collaboration between QuTech at Delft University of Technology and the California Institute of Technology.
By the end of the course you will
- Be armed with a fundamental toolbox for understanding, designing and analyzing quantum protocols.
- Understand quantum key distribution protocols.
- Understand how untrusted quantum devices can be tested.
- Be familiar with modern quantum cryptography – beyond quantum key distribution.
This course assumes a solid knowledge of linear algebra and probability at the level of an advanced undergraduate. Basic knowledge of elementary quantum information (qubits and simple measurements) is also assumed, but if you are completely new to quantum information additional videos are provided for you to fill in any gaps.
This is an advanced graduate course on quantum computation and quantum information, for which prior knowledge of quantum mechanics is required. Topics include quantum computation, advanced quantum error correction codes, fault tolerance, quantum algorithms beyond factoring, properties of quantum entanglement, and quantum protocols and communication complexity.
Already know something about quantum mechanics, quantum bits and quantum logic gates, but want to design new quantum algorithms, and explore multi-party quantum protocols? This is the course for you!
In this advanced graduate physics course on quantum computation and quantum information, we will cover:
- The formalism of quantum errors (density matrices, operator sum representations)
- Quantum error correction codes (stabilizers, graph states)
- Fault-tolerant quantum computation (normalizers, Clifford group operations, the Gottesman-Knill Theorem)
- Models of quantum computation (teleportation, cluster, measurement-based)
- Quantum Fourier transform-based algorithms (factoring, simulation)
- Quantum communication (noiseless and noisy coding)
- Quantum protocols (games, communication complexity)
Research problem ideas are presented along the journey.
Learner Testimonial
“This course is hard!”
-- Anonymous MIT graduate student
Quantum computation is a remarkable subject building on the great computational discovery that computers based on quantum mechanics are exponentially powerful. This course aims to make this cutting-edge material broadly accessible to undergraduate students, including computer science majors who do not have any prior exposure to quantum mechanics. The course starts with a simple introduction to the fundamental principles of quantum mechanics using the concepts of qubits (or quantum bits) and quantum gates. This treatment emphasizes the paradoxical nature of the subject, including entanglement, non-local correlations, the no-cloning theorem and quantum teleportation. The course covers the fundamentals of quantum algorithms, including the quantum fourier transform, period finding, Shor's quantum algorithm for factoring integers, as well as the prospects for quantum algorithms for NP-complete problems. It also discusses the basic ideas behind the experimental realization of quantum computers, including the prospects for adiabatic quantum optimization and the D-Wave controversy.
Before your course starts, try the new edX Demo where you can explore the fun, interactive learning environment and virtual labs. Learn more.
Do I need a textbook for this class?
No. Notes will be posted each week. If you wish to consult other references, a list of related textbooks and online resources will be provided.
What is the estimated effort for course?
About 5-12 hrs/week.
Why is the work load range so wide?
How long you spend on the course depends upon your background and on the depth to which you wish to understand the material. The topics in this course are quite open ended, and will be presented so you can understand them at a high level or can try to follow it at a sophisticated level with the help of the posted notes.
How much does it cost to take the course?
Nothing! The course is free.
Will the text of the lectures be available?
Yes. All of our lectures will have transcripts synced to the videos.
Do I need to watch the lectures live?
No. You can watch the lectures at your leisure.
Quantum Mechanics for Everyone is a four-week long MOOC that teaches the basic ideas of quantum mechanics with a method that requires no complicated math beyond taking square roots (and you can use a calculator for that). Quantum theory is taught without “dumbing down” any of the material, giving you the same version experts use in current research. We will cover the quantum mystery of the two-slit experiment and advanced topics that include how to see something without shining light on it (quantum seeing in the dark) and bunching effects of photons (Hong-Ou-Mandel effect).
To get a flavor for the course and see if it is right for you, watch "Let's get small", which shows you how poorly you were taught what an atom looks like, and "The fallacy of physics phobia."
Please note: the four sections of this course will be released on a weekly basis from April 18, 2017 to May 9, 2017, when all the course material will be available and the course will become fully self-paced.
Knowing the geometrical structure of the molecules around us is one of the most important and fundamental issues in the field of chemistry. This course introduces the two primary methods used to determine the geometrical structure of molecules: molecular spectroscopy and gas electron diffraction.
In molecular spectroscopy, molecules are irradiated with light or electric waves to reveal rich information, including:
- Motions of electrons within a molecule (Week 1),
- Vibrational motions of the nuclei within a molecule (Week 2), and
- Rotational motions of a molecule (Week 3).
In the gas electron diffraction method, molecules are irradiated with an accelerated electron beam. As the beam is scattered by the nuclei within the molecule, the scattered waves interfere with each other to generate a diffraction pattern. In week 4, we study the fundamental mechanism of electron scattering and how the resulting diffraction images reveal the geometrical structure of molecules.
By the end of the course, you will be able to understand molecular vibration plays an important role in determining the geometrical structure of molecules and gain a fuller understanding of molecular structure from the information obtained by the two methodologies.
FAQ
Do I need to buy a textbook?
No, you can learn the contents without any textbooks. However, if you hope to learn more on the subjects treated in this course, you are recommended to read the textbook introduced below:
Kaoru Yamanouchi, “Quantum Mechanics of Molecular Structures,” Springer-Verlag, 2012.
In this quantum physics course you will learn the basic concepts of scattering – phase-shifts, time delays, Levinson’s theorem, and resonances – in the simple context of one-dimensional problems. We then turn to the study of angular momentum and the motion of particles in three-dimensional central potentials. We learn about the radial equation and study the case of the hydrogen atom in detail.
This is the final course in a series which includes:
- Quantum Mechanics: Wavefunctions, Operators, and Expectation Values
- Quantum Mechanics: Quantum Physics in 1D Potentials
- Quantum Mechanics: 1D Scattering and Central Potentials
The series is based on the MIT 8.04: Quantum Mechanics I. At MIT, 8.04 is the first of a three-course sequence in Quantum Mechanics, a cornerstone in the education of physics majors that prepares them for advanced and specialized studies in any field related to quantum physics.
After completing the 8.04x series, you will be ready to tackle the Mastering Quantum Mechanics course series on edX, which will be available in Spring 2018.
In this quantum physics course you will acquire concrete knowledge of quantum mechanics by learning to solve the Schrodinger equation for important classes of one-dimensional potentials. We study the associated energy eigenstates and bound states. The harmonic oscillator is solved using the differential equation as well as algebraically, using creation and annihilation operators. We discuss barrier penetration and the Ramsauer-Townsend effect.
This is the second course in a series which includes:
- Quantum Mechanics: Wavefunctions, Operators, and Expectation Values
- Quantum Mechanics: Quantum Physics in 1D Potentials
- Quantum Mechanics: 1D Scattering and Central Potentials
The series is based on the MIT 8.04: Quantum Mechanics I. At MIT, 8.04 is the first of a three-course sequence in Quantum Mechanics, a cornerstone in the education of physics majors that prepares them for advanced and specialized studies in any field related to quantum physics.
After completing the 8.04x series, you will be ready to tackle the Mastering Quantum Mechanics course series on edX, which will be available in Spring 2018.
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