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 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:

"Walking through the produce section at the grocery store, you are likely to find tomatoes of all shapes, sizes, and colors. One variety may be large and oblong with a hint of bitter flavor while another will have small, sweet fruits. This variance is primarily the result of genetic and chemical properties of the different varieties. But it turns out, environment also plays a role. A team of Italian scientists has shown that the molecular properties of tomatoes are strongly influenced by environmental factors such as temperature and moisture. And changing these factors can, in turn, have pronounced effects on the physical and culinary qualities of the fruits – an important finding considering the pace of current climate change. To tease apart the interaction between genetics, environment, and organoleptic traits, the research team grew three tomato varieties in two different locations. This exposed the plants to varying levels of moisture, soil acidity, and temperature, among other conditions..."

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

Students learn about complex networks and how to represent them using graphs. They also learn that graph theory is a useful mathematical tool for studying complex networks in diverse applications of science and engineering, such as neural networks in the brain, biochemical reaction networks in cells, communication networks, such as the internet, and social networks. Topics covered include set theory, defining a graph, as well as defining the degree of a node and the degree distribution of a graph.

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.

Using a website simulation tool, students build on their understanding of random processes on networks to interact with the graph of a social network of individuals and simulate the spread of a disease. They decide which two individuals on the network are the best to vaccinate in an attempt to minimize the number of people infected and "curb the epidemic." Since the results are random, they run multiple simulations and compute the average number of infected individuals before analyzing the results and assessing the effectiveness of their vaccination strategies.

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.

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:

"A new study from the Max Planck Institute for Human Development unveils the deep bodily connections that can form among choir singers Researchers tracked different physiological variables as a choir sung and used algorithms to uncover connections between them Aside from a blending of voices, they found that choir singers’ heart rates and breathing patterns sync up when performing as a group This merging was coupled to the vocalization patterns of the singers The conductor’s hand movements also caused a shared physiological response among the singers In essence, the work suggests that a choir can be considered a type of coherent physiological entity… or, as the researchers suggest, a superorganism Viktor Müller, Julia A.M. Delius, Ulman Lindenberger. Complex networks emerging during choir singing..."

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

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.

Students use graph theory to create social graphs for their own social networks and apply what learn to create a graph representing the social dynamics found in a dramatic text. Students then derive meaning based on what they know about the text from the graphs they created. Students learn graph theory vocabulary, as well as engineering applications of graph theory.

Students analyze their social networks using graph theory. They gather data on their own social relationships, either from Facebook interactions or the interactions they have throughout the course of a day, recording it in Microsoft Excel and using Cytoscape (a free, downloadable application) to generate social network graphs that visually illustrate the key persons (nodes) and connections between them (edges). The nodes in the Cytoscape graphs are color-coded and sized according to the importance of the node (in this activity, nodes are people in students' social networks). After the analysis, the graphs are further examined to see what can be learned from the visual representation. Students gain practice with graph theory vocabulary, including node, edge, betweeness centrality and degree on interaction, and learn about a range of engineering applications of graph theory.