Hi, in this first lecture, we are going to talk about Complex Systems. It's now becoming clear that in many sciences, we face very similar issues. It's not only because we are dealing with large data sets, it's also because complex systems in general share common design principles. In systems of biology, we mostly care about the design principles of cells. In this course, we will deal mostly with mammalian cells. However, we'll try to identify analogies between human cells and technological complex systems. So what is Science? One definition is systematic knowledge of the physical and material world gained through observations and experimentations. So one thing to keep in mind about observations, is that they have to be reproducible. Once we have a reproducible observation, we can form generalizations. Generalizations can be formulated mathematically or programmatically into models. These models gives rise to theories, once we have an accurate model we can perform simulations or computations that can be used to predict unseen yet observations. The question about model is and theories is how accurate in general they are. Once we obtain systematic knowledge about the physical and material world, we can use this knowledge to create new tools. Here, innovation and creativity are critical, and these new tools, he can now compete in an economic or in a social market, and the most fit tools will survive and evolve. So, let's think of an example. One obvious example is the circular rhythms of days, months, years, these observations are well understood and can be predicted. Then using this knowledge, calendars, clocks, and tools were invented by humans based on this scientific understanding. So one thing I would like you to try is think about other examples. If you are coming from the fields of biology or systems biology. I would like you to think of examples where scientific discoveries led to the development of tools that helped us advance scientific discovery, further scientific discovery in biology. If you come in from other fields, I'm sure you can find examples where science was used to develop new tools that were based on that science. So there's a yin-yang relationship or a feedback loop between technology and science. So for technology that was assisted by science. We produce new tools that can be better used to observe things and that advances science. Technology is also producing new complex systems that can be studied by science. For example, the stock market or the social network on Facebook. So far almost all complex systems that are created by human, that have technological origins are created to extend human fitness. So those are tools that we invented to extend our fitness. So what is a Complex System? Complex systems are made of many heterogeneous (diverse) agents or agent parts that interact in various ways to form higher order entities. Complex systems are networks or agent. Agents are made of other agent or made from agent parts. However, Complex systems are relatively difficult to define, because they contain many properties, so there's no one characteristic that makes a complex system a complex systems, so, What is the Science of Complexity? So in the 80's, a set of prolific scientists, banded together to form this new science, or to define this new science, to try to identify concepts across sciences, so, the goal was to better understand, generalize, theorize and predict the behavior of complex systems in general, not just in a particular field. So I used the term agent when I define complex systems. So what is an agent exactly? An agent is a term that was invented by those complex system researchers and it's an entity in complex system. It can actually be a complex system on its own, and it contain properties such as actuators. Those could be, arms and legs, as the complex system is a human. Complex systems typically contain sensors. And these are our eyes, our nose, for example. If we are to consider ourselves as a complex system. Typically complex, complex systems have a defense system. This could be our immune system in our body or it could be some type of a mechanism within cells to actually have self-defense from external attacks. Agents typically consume energy. And so they seek energy sources, consume them, convert them to an energy that can be utilized to do the various tasks that a complex agent is doing. Agents typically have boundaries, some type of an separator, a wall that separates the agents from other agents as well as separate the agents from the environment. Natural agents can have this amazing ability to self-reproduce. Technological agents are typically reproduced In the factories. Agents typically have some type of an oscillator inside of them, such as a heart and/or a Circadian rhythm clock. In cells, many agents have a central processing unit. This could be our brain. Or in the case of self there are the networks that we're going to talk about. Cell signalling and [INAUDIBLE] networks that control the behavior of a cell. Agents also typically have an ability to self repair. And, if you think about cities for example, this could be the police, hospitals, agents also have advanced transportation systems. One thing to keep in mind about natural biological complex systems is that they appear at different scales. So at the sub-cellular scale, we have complex agents, such as the nucleus or the mitochondria and those are independent systems within the system of a cell. The next level is the human cell and that is going to the be the focus of our course. Then the next level would be tissues and cell populations. This could be a heart, a liver, or a bacterial colony. Multi-cellular organism such as us, is another level in the scale in organization of natural complex systems. And this final level, those are ecosystems, social structures, such a a pond, a rain forest, beehive, countries, companies, and families. So one thing that I would like you to try is to, identify at every one of those skills, what are the agent component, or the complex systems properties, such as the actuators, the sensors. Each of those systems that I mentioned here at the different layers of scale. So I mentioned that technology extends human fitness. So human have invented products that increase their fitness. For example, a motorcycle increased our ability to move. Sunglasses or a microscope help us to improve our senses. Clothes help our defense from the natural environment, a megaphone, cell phones help us to communicate. And computers, help us in genera,l to process information, and do a lot of more things. So when I mentioned complex systems, I said that there are very different types of complex systems. Sometimes they are shared properties, and sometimes they are not. You have to distinguish between the Natural Evolution and Technological Evolution. And there are differences between those types of systems that emerge in Natural Evolution and Man-made Evolution. And some of the differences are, that the natural evolution takes a long time, billions of years to evolve. While Man-made Evolution, seems to accelerate and it's only been accelerating at on the moon for maybe thousands of years. So one is very slow and the other one is fast. Natural Evolution is limited to mutations, it has to pass through generations. Rise in technological evolution. You can have an idea, and that can become a product overnight. However there's some similarity between natural and man-made evolution. For example, the rate of evolution is different across different parts of our planet. In some areas such as major cities. You see, rapid evolution, while in other areas, there is very slow adaptation of change. You also want to distinguish between Open and Closed Complex Systems. So, what I mean by closed systems, I'm talking about an individual agent that can be a complex system like I mentioned before. So, closed systems have defined boundaries, a central processing unit, a clock, sensors, actuators, motility apparatus, they are born, live and die. They only grow to a defined size, they self-repair, and reproduce. Open systems, on the other hand, have less defined boundaries, not clear governance. They have many agents of the same type like the beehive. Or an ant colony, all acting stochastically, meaning that they act in random fashion. However, together they lead to an emergent behavior. So they look like they're all working together, even though individually they are at the randomly or self serving. Open systems grow faster as they become more complex. And, at first this is a general assessment. On the other hand, closed systems become less flexible as they grow in complexity. So, it's harder for them to change as complexity increases and this is an example one and it's closed system but an ant colony can be considered an open system. So I would like you to identify, from your own personal experience, some open and closed systems that you can consider complex systems, man-made and natural. So these are some examples to get you started. So, the human cell, obviously, or human. A cow, the weather system, stock market, New York City, a tree, commercial air traffic systems. So not only try to identify additional complex systems, but also try to classify them whether they're closed or open. So now I would like to focus on, what this course is about. This is the human or mouse cell and here after listening to this ideas about complex systems and agents, let's try to identify the parts of a cell. So now let's think about the human or mouse cell as an agent. Let's try to identify in the cell those general properties of agents and complex systems. So, if we think about actuators, those could be decisions made by a cell such as to crawl towards a specific direction. To differentiate into specific lineage. To perform self-execution which is ectosis or to a proliferate. When we talk about sensors and we're gonna talk about those more later on, this could be receptors of the cell membrane, all receptor, receptors of the nucleus. Those proteins, listen to the environment and transmit information about the status of the environment into the inside of the cell. Cells also have defense systems such as the interferon system. Cells have several boundaries, for example, the plasma membrane or the nuclear membrane. Cells obviously consume energy, for example, through conversion of glucose into ATP. Cells can self-reproduce like I mentioned through the cell cycle. They have a clock, which is typically the circadian rhythm clock. They have various transportation systems, for example, the retrograde transport, vesicle transports mechanisms. Cells also have cell repair mechanisms such as the proteozone, or the autophagy system. And the central processing system in a cell could be considered the cell signalling network and the gene regulatory network, which would be the main focus of our course. [FOREIGN]
