This interdisciplinary course provides a hands-on approach to students in the topics of bioinformatics and proteomics. Lectures and labs cover sequence analysis, microarray expression analysis, Bayesian methods, control theory, scale-free networks, and biotechnology applications. Designed for those with a computational and/or engineering background, it will include current real-world examples, actual implementations, and engineering design issues. Where applicable, engineering issues from signal processing, network theory, machine learning, robotics and other domains will be expounded upon.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Researchers from Japan and Massachusetts have devised a new way to estimate induction motor speed. Typically difficult to achieve for an object constantly in motion, that ability could lead to the construction of more efficient electric motors. Numerous industries literally run on induction motors. These electromagnetic engines are found in everything from small toys and appliances to giant construction equipment. One big improvement made to induction motor design in recent decades was the removal of the encoder—a fragile sensor that keeps tabs on the position and speed of the shaft during operation. Despite boosting engine efficiency and reducing size, this sensorless design can put performance at risk when trying to ensure smooth operation. And although indirect estimation methods have been developed, many are found to be lacking. Some, for example, assume rotor speed to be a constant parameter—which is hardly the case in practice..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This course covers the fundamental methods used for exploring the information content of observations related to kinematical and dynamical models.

Introduction to Sociology 2e adheres to the scope and sequence of a typical, one-semester introductory sociology course. It offers comprehensive coverage of core concepts, foundational scholars, and emerging theories, which are supported by a wealth of engaging learning materials. The textbook presents detailed section reviews with rich questions, discussions that help students apply their knowledge, and features that draw learners into the discipline in meaningful ways. The second edition retains the book’s conceptual organization, aligning to most courses, and has been significantly updated to reflect the latest research and provide examples most relevant to today’s students. In order to help instructors transition to the revised version, the 2e changes are described within the preface.

Describe the functionalist view of deviance in society through four sociologist’s theoriesExplain how conflict theory understands deviance and crime in societyDescribe the symbolic interactionist approach to deviance, including labeling and other theories

This one-day workshop provides a brief overview of system dynamics and a hands-on simulation experience. It also serves as a preview of the more in-depth coverage of the subject available in other courses offered at MIT Sloan.

This course provides an introduction to cellular and population-level systems biology with an emphasis on synthetic biology, modeling of genetic networks, cell-cell interactions, and evolutionary dynamics. Cellular systems include genetic switches and oscillators, network motifs, genetic network evolution, and cellular decision-making. Population-level systems include models of pattern formation, cell-cell communication, and evolutionary systems biology.