This class analyzes complex biological processes from the molecular, cellular, extracellular, and organ levels of hierarchy. Emphasis is placed on the basic biochemical and biophysical principles that govern these processes. Examples of processes to be studied include chemotaxis, the fixation of nitrogen into organic biological molecules, growth factor and hormone mediated signaling cascades, and signaling cascades leading to cell death in response to DNA damage. In each case, the availability of a resource, or the presence of a stimulus, results in some biochemical pathways being turned on while others are turned off. The course examines the dynamic aspects of these processes and details how biochemical mechanistic themes impinge on molecular/cellular/tissue/organ-level functions. Chemical and quantitative views of the interplay of multiple pathways as biological networks are emphasized. Student work culminates in the preparation of a unique grant application in an area of biological networks.

This course is for students wishing to explore blockchain technology's potential use—by entrepreneurs and incumbents—to change the world of money and finance. The course begins with a review of Bitcoin and an understanding of the commercial, technical, and public policy fundamentals of blockchain technology, distributed ledgers, and smart contracts. The class then continues on to current and potential blockchain applications in the financial sector.

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:

"The clinical practice of anesthesia is nearly two centuries old. But today, how anesthetics suppress consciousness remains a mystery. Specifically, how do molecular-level drug effects translate into macro-level phenomena? A recent review in the journal Anesthesiology looks at how brain slice studies are helping bridge that gap in neuroscience—with recent findings increasingly pointing to the cortex as a critical center of anesthetic action. Anesthesiologists have embraced the acute brain slice method for investigating anesthetic drug effects. Brain slices enable researchers to examine drug actions in isolated, locally connected networks under highly controlled but flexible conditions. Collectively, such studies suggest that both cortical and subcortical regions of the brain, such as the midbrain and thalamus, play important roles in anesthesia, each contributing to both the level of arousal and the content of consciousness..."

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

This course covers the algorithmic and machine learning foundations of computational biology combining theory with practice. We cover both foundational topics in computational biology, and current research frontiers. We study fundamental techniques, recent advances in the field, and work directly with current large-scale biological datasets.

With the growing availability and lowering costs of genotyping and personal genome sequencing, the focus has shifted from the ability to obtain the sequence to the ability to make sense of the resulting information. This course is aimed at exploring the computational challenges associated with interpreting how sequence differences between individuals lead to phenotypic differences in gene expression, disease predisposition, or response to treatment.

This course provides the fundamental computational toolbox for solving science and engineering problems. Topics include review of linear algebra, applications to networks, structures, estimation, finite difference and finite element solutions of differential equations, Laplace's equation and potential flow, boundary-value problems, Fourier series, the discrete Fourier transform, and convolution. We will also explore many topics in AI and machine learning throughout the course.

This course provides a review of linear algebra, including applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow; boundary-value problems; minimum principles and calculus of variations; Fourier series; discrete Fourier transform; convolution; and applications.
Note: This course was previously called "Mathematical Methods for Engineers I."

This course will emphasize basic security concepts (authentication, confidentiality, accounting and integrity), apply these concepts to computer networks, and amplify the theory with hands-on aspects of configuring and using secure networks. Topics include: review of networking concepts, general security concepts, user authentication and authorization, encryption, network attacks (including hacking, viruses, worms and denial of service) and network protection. Defense tools including firewalls, Virtual Private Networks (VPNs), and filters will be discussed in depth, as they relate to effective and safe e-commerce and other applications in the real world. Case studies along with projects will be assigned and performed.

This open textbook aims to fill the gap between the open-source implementations and the open-source network specifications by providing a detailed but pedagogical description of the key principles that guide the operation of the Internet.

Suppose you want to build a computer network, one that has the potential to grow to global proportions and to support applications as diverse as teleconferencing, video on demand, electronic commerce, distributed computing, and digital libraries. What available technologies would serve as the underlying building blocks, and what kind of software architecture would you design to integrate these building blocks into an effective communication service? Answering this question is the overriding goal of this book—to describe the available building materials and then to show how they can be used to construct a network from the ground up.

This class covers topics on the engineering of computer software and hardware systems. Topics include techniques for controlling complexity; strong modularity using client-server design, operating systems; performance, networks; naming; security and privacy; fault-tolerant systems, atomicity and coordination of concurrent activities, and recovery; impact of computer systems on society.

Academic artist Enrique Legaspi grew up singing, skateboarding, and creating. As a teacher, one day he realized, "I'm doing everything I can, I'm staying up late, but I'm producing the same results. What's going on?" Now that he's begun to modify and adapt his teaching to his students' interests, Enrique's students are creating, curating and sharing their work using video and social media -- and it's made all the difference.

Network analysis is one of the four pillars of computational humanities, along with geographic, text, and image analysis. Participants in this course will receive a broad overview of networks as they’re applied to humanities problems.

Dive into Systems is a free, online textbook that serves as a gentle introduction to computer systems, computer organization, and parallel computing. The book is intended for an audience that has only a CS1 background. It guides readers through a vertical slice of a computer to develop an understanding of a variety of systems topics, including:

- how a computer runs a program, from a program expressed in a high-level language to low-level binary representation and circuits

- programming in C and Assembly, assuming a CS1 background

- introduction to operating systems and the systems costs that affect program performance (the memory hierarchy, caching, and code optimization)

- introduction to parallel computing with shared memory and pthreads

Dive into Systems is designed to be present topics in as independent manner as possible so that it can be used as a primary textbook for a wide range of introductory-level computer systems courses, or as a supplemental background textbook for upper-level courses that cover Operating Systems, Computer Architecture, Compilers, Networks, Databases, and Parallel Computing.

This course surveys the core perceptual and cognitive abilities of the human mind and asks how they are implemented in the brain. Key themes include the representations, development, and degree of functional specificity of these components of mind and brain. The course will take students straight to the cutting edge of the field, empowering them to understand and critically evaluate empirical articles in the current literature.

This is a unit of study whose competency is to locate necessary resources that help to acquire additional subject matter and pedagogical knowledge for professional development. The objectives are: identify relevant resources for professional development and collaborative teacher networks. Discuss the advantages of collaborative networks and participate in collaborative teacher networks.

This material enable the user to understand clearly the computer networks in detail.

Texts:

Bonaventure, O., Computer Networking: Principles, Protocols and Practice, Release 0.25, Saylor Foundation, 2011. http://www.saylor.org/site/wp-content/uploads/2012/02/Computer-Networking-Principles-Bonaventure-1-30-31-OTC1.pdf

Dordal, P., An Introduction to Computer Networks, Release 1.9.16, 2019. http://intronetworks.cs.luc.edu/current/ComputerNetworks.pdf

Course description: A comprehensive examination of how computers can be linked together to share resources and information. Emphasis will be given to understanding packet switched networks and how they enable contemporary enterprises. Topics include network hardware, software and protocols. Prerequisites: CS13X or CS161 (or concurrent).

Learning Outcomes:
After completing this course:
Students will have practical experience using protocols to enable communication between computing devices connected to each other,
Students will have configured an IT infrastructure solution for a small organization, including a network based on standard technology components, servers, security devices, and several different types of computing clients,
Students will apply core concepts underlying IP networks to solve simple network design problems, including IP subnetting.

The course provides a graduate level introduction to Industrial Organization. It is designed to provide a broad introduction to topics and industries that current researchers are studying as well as to expose students to a wide variety of techniques. It will start the process of preparing economics PhD students to conduct thesis research in the area, and may also be of interest to doctoral students working in other areas of economics and related fields. The course integrates theoretical models and empirical studies.

This class offers a broad coverage of technology concepts and trends underlying current and future developments in information technology, and fundamental principles for the effective use of computer-based information systems. There will be a special emphasis on networks and distributed computing, including the World Wide Web. Other topics include: hardware and operating systems, software development tools and processes, relational databases, security and cryptography, enterprise applications, and electronic commerce. Hands-on exposure to Web, database, and graphical user interface (GUI) tools.
This course is intended for students with little or no background in computer technology. Students with extensive education or work experience in computer technology should consider taking a more advanced course.