43 results
8 - Close only counts in horseshoes and hand grenades
- Eberhard O. Voit, Georgia Institute of Technology
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- The Inner Workings of Life
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- 05 May 2016
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Summary
It was allegedly major league baseball manager Frank Robinson who inspired the phrase, emphasizing that “close don't count in baseball.” Only one team wins the World Series in a given year, even if the point spread in Game 7 is just one. Indeed, “close” is unacceptable for many aspects of life. Proper bookkeeping does not tolerate missing dollars or even cents. Almost winning the lottery, or almost getting the dream job, let alone the dream girl or guy, simply isn't good enough. Sometimes, “almost” seems even worse than missing the target by a wide margin.
If life with all its vagaries and uncertainties is so often dissatisfied with “close” or “almost,” one would probably expect that hard-core science and engineering are even tougher when we miss the mark, even if only barely. And what does mathematics, the most precise of all human endeavors, have to say about “close enough”? It may come as a surprise, but science, engineering, and mathematics all embrace the concept of only being sufficiently close rather than 100 percent accurate, as long as the deviations are handled appropriately.
Two reasons make the quest for uncompromising precision infeasible, especially in a field like systems biology. First, we seldom know what the exact and precise truth is, and nature does not come with an instructions manual that offers guidance regarding the choice of perfect models. Second, the truth is usually too complicated for us to comprehend in its entirety, let alone convert into a computational representation. As an illustration, suppose we are interested in constructing a computational model of a cellular signaling process. With a coarse-grained perspective, the task is not all that difficult. The cell receives a signal in the form of a physical change in the environment, such as an electrical or mechanical impulse, or a chemical stimulus, such as the arrival of a hormone that was sent from a different location in the body, and responds by synthesizing the proteins or metabolites it needs. We could model this signaling mechanism like a light switch that turns the appropriate processes on or off. In mathematical terms, a simple toggle switch between 0 and 1 would do fine, and for some purposes, such a model might indeed be sufficient.
6 - Just a little bit
- Eberhard O. Voit, Georgia Institute of Technology
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A bit became a bit in the 1930s and 1940s. In medieval England it had been a bite-sized morsel. In the young US, it amounted to an eighth of a Spanish silver dollar, and one could allegedly get a shave and a haircut for two bits. Then, in 1936, the distinguished American inventor Vannevar Bush, the lead founder of the early technology start-up Raytheon and head of the US Office of Scientific Research and Development during the Second World War, wrote a fascinating and quite amusing article reviewing the truly amazing mechanical and electrical devices that were being used at the time for all kinds of computing tasks, including differentiation, integration, correlation analysis, the solving of systems of algebraic and differential equations, the evaluation of wind tunnel experiments, and the analysis of numerous other diverse applications. While affirming that, “the combination of such machines with punched cards has made arithmetic into an entirely new affair,” Bush lamented the size limitations of the cards and proposed that clever coding could increase their capacity to “over 300,000 bits of information.” About a decade later, the famous Bell Labs mathematician and statistician John Tukey, and the pioneer of information theory, Claude Shannon, formalized Bush's casual terminology by contracting binary and digit to describe a base unit of information as one bit, a flip-flop that could only take the values of 1 or 0, on or off.
Fast-forward to the twenty-first century, and there is no doubt that the little bit has conquered almost every bit of the world, and it is hard to think of any aspect of life that is not fundamentally affected by digitization. Building upon the visionary ideas of the nineteenth-century British inventor, engineer, mathematician, and philosopher Charles Babbage, who originated the concept of a programmable computer, ever-more sophisticated, powerful, and fast computers came to be, leading to today's huge supercomputers but, maybe more importantly, to huge numbers of very small computers that, in their own ways, are all supposed to make life simpler. Not surprisingly, computers have also become premier tools of systems biologists.
The most recognized and obvious help we get from computers is the handling of data. And whether it is the government, Walmart or systems biology, the amounts of some data have become so enormous that they are rightfully classified as BigData.
7 - Supermodels
- Eberhard O. Voit, Georgia Institute of Technology
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- The Inner Workings of Life
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Models come in many forms. We all use conceptual models on a daily basis. Driving to the store, we know when to turn right or left, because we have in our minds a mental picture of the street scenes. Even if we do not know a city well, we have learned how to read and interpret a street map, which in itself is a model of the city. Dolls and toy trains are physical models that allow children to learn much about the world of adults. A good architect sees from a blueprint what a building will look like. In addition to conceptual models, which always whirr about in a scientist's mind, systems biology makes heavy use of mathematical and computational models. The difference between the two is actually quite vague, as many mathematical models are analyzed with computers and computational models are based on mathematical formulae and equations.
A typical model in systems biology consists of a mathematical description of processes occurring in cells, organisms, populations or ecosystems. To see why such models can be helpful, consider, as an analogy, the computer system in an airplane as it prepares for landing. It takes input information from the real world, such as the speed and weight of the plane, power of the jets, current altitude, length of the runway, as well as environmental conditions like wind speed and direction, enters all these data into a large system of mathematical equations, evaluates these equations, and determines the appropriate settings of rudders, flaps, and slats that ensure a smooth landing. The concepts in biology are similar, and one might imagine inputs regarding the health status of a diseased person, which are computationally converted into suggestions for a treatment. The modeling process itself is more complicated than for engineered systems because we often do not know the biological component parts and processes sufficiently well. It also turns out that knowledge of the parts is not sufficient to reconstruct a biological system, as we will discuss later.
In his 1858 book, The Autocrat of the Breakfast Table, the American physician, writer and poet Oliver Wendell Holmes mused, “I find that the great thing in this world is not so much where we stand as in what direction we are moving.”
Acknowledgments
- Eberhard O. Voit, Georgia Institute of Technology
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18 - Redesigning perfect
- Eberhard O. Voit, Georgia Institute of Technology
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Whether we like bugs, viruses or creepy crawlies of various stripes does not really matter. But we do have to admit that each of them has, as a species, survived for a long time. Each one of these critters has consistently been more competitive than all challengers. It has been superior to others and therefore is in some sense optimal. Each has passed the strict test of evolution by surviving in an often hostile world. We might actually be forced to admit that each one of them is perfect in its own way.
So, if a bug is perfect, can it be improved? Why should we even think about changing it? Practitioners of the new fields of synthetic biology and metabolic engineering, which could be considered prominent applications of systems biology, certainly believe that exactly that could be very rewarding. Synthetic biologists and metabolic engineers have no problem with the argument that bugs are perfect, but their rationale for trying to change them derives from the fact that perfection may be judged by rather different criteria.
A mathematician might say that the bug has to solve a “multi-objective optimization” task. It must optimize many objectives simultaneously, and these objectives are often in conflict with each other. We deal with such tasks every day. For instance, buying a winter coat involves numerous objectives that should be satisfied and, ideally, optimized. The coat must have the right insulation for the expected temperatures, we really want to like the material and color and, of course, the price must be right. Abundant experience tells us that we are seldom able to satisfy all criteria completely and that we must prioritize or compromise by weighing different aspects against each other. Even the nicest coat is out of reach if we cannot afford it.
All organisms in the real world have this type of problem throughout their lives. Above all, they must ensure that their species survives and proliferates. This overarching objective involves uncounted smaller tasks, as the organisms need to be tolerant to environmental perturbations, fight off, avoid or flee from hostile challengers, appeal to potential mates, and bring their young ones to independence. The rationale of metabolic engineering for altering organisms is that if one relieves the organisms of some of these tasks they should be able to devote energy to others.
1 - Status: it's complicated!
- Eberhard O. Voit, Georgia Institute of Technology
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In 1635, the English scientist Robert Hooke made a fantastic discovery. Studying a slice of cork through a microscope, he discovered cavities that, as he said, used to contain the “noble juices” that once had nurtured the living tree from which the cork had been cut. He called the cavities cellulae, a Latin word for storage rooms and the root of the term that we still use today: cells. Because the cork was dead, Hooke was only able to see cell walls forming a honeycomb structure. As exciting as this discovery must have been at the time, we now know that Hooke merely saw the tip of the iceberg, actually missing most of what makes a cellula such an impressive object. Peeking into a cell today with an optical or electron microscope, we see how a whole new world of structures and molecules opens up. Most cells have a nucleus, mitochondria, and ribosomes, and there are all kinds of small organelles, vesicles, and membrane enclosures. Going even further, modern visualization and tagging techniques of molecular biology allow us to see more and finer structures, all the way down to the level of large individual molecules. A whole world, invisible to the human eye, is emerging, leaving no doubt: life is complicated!
We systems biologists love to work on real puzzles. For many of us, living systems are huge Sudokus, where some information is available, but lots of gaps in-between are to be filled in through experiments and with advanced logic that evaluates the experimental results in a systemic context. Trying to figure out how the multitudinous parts in cells work together to create something as incredible as a brain is very attractive to us. We are fully aware that we will not solve the whole puzzle in our lifetimes, but nature is modular, and every systems biologist hopes to solve a large sub-puzzle, or at least a few smaller puzzles. The intellectual challenge is the enormous complexity of every cell and organism, which requires us to invent new tools and methods, and that's what systems biology is all about.
The complexity of living systems is due to different features. First and foremost, there are just very many parts. The lowly bacterium E. coli contains between four and five thousand genes.
20 - Dessert
- Eberhard O. Voit, Georgia Institute of Technology
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“Are we there yet? When are we gonna be there?” Who does not recall the little voices of backseat drivers a couple of hours into a 300-mile trip? We smile, and somewhat exhausted may offer a platitude like “We'll get there when we get there,” which may grant us a short reprieve, although we know full well that it will only confuse a young, inquisitive mind.
Systems biology is in quite a similar situation. The young endeavor has been receiving a lot of attention, and excitement about its potential has led to widespread enthusiasm and support. These are very positive developments indeed, but we must realize that they also come with a hidden danger: the public, the funding agencies, and even colleagues from more traditional biological fields are not infinitely patient, and systems biology must expect that the initial hype and sometimes exaggerated promises may eventually turn into demands for major tangible successes. We have invested a lot; what have we gotten in return? Why has systems biology not yet cured cancer? Except for a very few isolated cases, personalized medicine is still a distant fantasy; when will we enjoy its fruits? Systems and synthetic biology still look like academic, if not totally esoteric, pursuits; what have they produced that we could not have achieved with traditional means?
There is no doubt: systems biology is not “there yet.” Maybe worse, it is entirely unpredictable when we are “gonna be there.” And in contrast to small children, the public and the national funding agencies can seldom be mollified with statements such as “Trust us, we'll get there” … with the occasional addition of “eventually” under our breath. Yes, we are a long way away from “there,” but we must not let doubt distract us from our noble quest. Systems biology is still young and simply has no choice but to stay the course and march onward, while asking for patience and carefully documenting our initially modest successes along the way. After all, we systems biologists are convinced to the core of our being that there is no alternative to dedicating our most fervent efforts to advancing this exciting field of endeavor, and we can indeed point to some early successes.
Selected further reading
- Eberhard O. Voit, Georgia Institute of Technology
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Contents
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14 - Can't we all get along?
- Eberhard O. Voit, Georgia Institute of Technology
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It has almost become a cliché. One African-American, one Asian, one Caucasian, one Hispanic, one Mid-Eastern and one Native American child are all playing cheerfully together, while advertising a new gadget or the best detergent of all time. And, of course, the group consists of three girls and three boys. The picture displays an idealized world we all want to see: peaceful, harmonic diversity. We are not just all equal before the law; if we set our mind to it, we can all get along just fine, in spite of our differences. In fact, we believe that diversity expands and enriches what we as a community can accomplish.
In nature, diversity takes on a dimension of an entirely different magnitude, and a few little Homo sapiens of different hues playing together are just that: child's play. A long-term investigation of a lake in Wisconsin identified roughly 10,000 different species of bacteria, all living together in what modern lingo calls a metapopulation or a microbiome. According to some estimates, a single liter of ocean water can contain 10 billion viruses; that is more than one virus per person in the entire world. These populations of populations can be found in essentially any place where life can thrive. They live in oceans, lakes, and rivers, below and above ground, as well as in and on plants and animals. A single gram of soil can contain enough microbial DNA to stretch almost 1,000 miles. Some microbial metapopulations form biofilms, which are thin layers on moist surfaces and in all kinds of pipes, sewage systems, and water tubing that one might find in less than sanitary dentists’ offices, and even on our teeth. All in all, it has been estimated that 5x1030 prokaryotic cells inhabit the earth – that is a 5 with 30 zeroes – and very few live in a monoculture.
Whether we are looking at the macro- or micro-world, no organism thrives in isolation, and the coexistence of many species indicates that complex communities have evolved together in a dynamic and adaptive combination of genomic and ecological processes. The human body is no exception. It serves as the host to an estimated 100 trillion microbes, a number that corresponds to roughly 10 times the total number of human cells in the body. Particularly fertile is the gut, where the density of microorganisms can reach 1 trillion cells per milliliter.
19 - Let's meet in the agorá!
- Eberhard O. Voit, Georgia Institute of Technology
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The agorá was the common gathering place and market of cities in ancient Greece. It was the center of activities, and nothing exhibited the pulse of the city better than the hustle and bustle in the agorá. If a philosopher felt compelled to share his wisdom with the world, if a vote were to be taken, or if one just needed to buy goods, the agorá was the place to be.
Combined with the all-important ancient concept of the division of labor, a common center for trading goods and thoughts is arguably one of the oldest and persistent creations of humankind. If I grow grain and my neighbor has sheep, it is quite natural to meet and barter. Another neighbor may trade wood or bricks, fine lace or expensive jewelry, and it soon makes a lot of sense to centralize the trading activities in a common market. While bartering is the most natural means of exchanging goods, the daily haggling soon becomes repetitive and tiring, and frequent traders develop guidelines and conversion factors, and eventually create a widely accepted currency.
Systems biology is the modern agorá in the intersection of many disciplines, most notably biology, chemistry, physics, math, computer science, and engineering. Scientists from different backgrounds meet because they see great value in solving “grand challenge” problems whose solutions are out of their own reach. It takes many bright minds and just the right confluence of knowledge and methods to address questions of cancer or the growing threat of microorganisms that are resistant to our best drugs. No single person or even discipline is capable of developing new agricultural products that can feed expanding populations, yet grow in impoverished soils under both drought and flood conditions. So the experts meet to discuss. Biologists pose complex problems and devise and execute experiments that shed light on the problem, engineers offer to create machines for collecting data more efficiently, mathematicians and physicists provide rigorous ways to formalize and address the problems with models that are anchored in a solid theoretical foundation, and computer scientists offer fast techniques for analyzing data and models. The practitioners of each discipline know that they alone cannot manage the entire spectrum of activities that are needed to solve the complex problems that arise time and again when we deal with biomedical and environmental systems.
Frontmatter
- Eberhard O. Voit, Georgia Institute of Technology
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11 - What hath God wrought!
- Eberhard O. Voit, Georgia Institute of Technology
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On July 15, 2013, the last telegram was sent by the only remaining telegraph office in the world, the Central Telegraph Office in Janpath, India. The technology had lasted for almost two centuries, since the American artist and inventor Samuel Morse in 1837 first experimented successfully with an electrical telegraph. In 1844, he demonstrated the feasibility of his invention to the world, by sending the message “What hath God wrought” from Washington, DC to his colleague Alfred Vail in Baltimore. By doing so, he ushered in the era of the electrical and electronic information age.
The appeal of sending information across long distances is obvious and, of course, was not new even in Morse's time. The Estonian diplomat Pavel Schilling had demonstrated the feasibility of an electrical telegraph a few years earlier, and French engineers had operated light signaling systems since the late eighteenth century. Long before these inventions, Native Americans had been using smoke signals to warn their peers of impending danger.
Considering the enormous importance of knowing what's going on at a distance, it is not surprising that the transmission of information is an integral part of essentially all biological systems. The specific mechanisms of signal transduction within and between cells vary greatly in their molecular basis, transmission distance, time scale, and a number of other features. For instance, the speed of signal transduction ranges from electrical signals at the order of milliseconds to protein-based signaling cascades responding at the order of minutes and signals involving genomic and physiological responses that occur within tens of minutes, hours or even days.
In many cases, multiple signals are transmitted in parallel. For instance, the demand for a metabolite often triggers feedback signals directly at the metabolic level. These signals modify the activity of enzymes that are responsible for the synthesis of the desired metabolite. They accomplish this typically by slightly altering the physical shape of the enzyme molecules, which occurs within seconds. If this mechanism is insufficient, the availability or activity of other proteins may be changed, which takes minutes or hours. Persistent demands are signaled to the genome, where the expression of appropriate genes is up-regulated and secondarily leads to higher enzyme activities over longer time horizons that may span hours, days or weeks. Intriguingly, metabolic, protein-based and genomic alterations may all be initiated simultaneously.
4 - Why?
- Eberhard O. Voit, Georgia Institute of Technology
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“Mommy, why is the sky blue? Why do zebras have stripes? Why has Aunt Maud got hair growing out of her nose? Why are bananas crooked?” All good parents try hard to answer such questions, or at least most of them, but it is hard-core scientists who most encourage their kids to ask a lot of questions. After all, questions are a sign of curiosity, and curiosity is the ultimate, indispensable prerequisite for becoming a good scientist. Yet, as soon as the same scientists return to their labs, “why” becomes a taboo word. Why? What happens on the way to work?
Many scientists subscribe to the tenet that “why?” is not a scientific question. “How?” and “what?” are scientific questions, but “why?” is not. The famous evolutionary biologist Richard Dawkins even derided it as a “silly” question. One reason for the discrepancy is probably that children are usually satisfied with a single answer. “Bananas grow faster on one side than on the other” might just do. No need for a lecture on phototropism or auxins or other phytohormones that play a role in coordinating growth processes in plants. Not so with scientists. Every answer leads to new questions, and while many in the chain may have answers, there comes the inevitable point at which one has to admit “I don't know” or “nobody knows,” or a supernatural deity is to be evoked quasi as a deus ex machina. None of these three options is particularly desirable to scientists, and “why” is therefore a priori to be excluded from scientific discussions as a preemptive measure. Answering “why” implies that biological processes are driven by intent toward a goal; it reeks of teleology, the many-centuries-old philosophical concept that searches for the ultimate reasons of being and the purpose of human existence. It also comes uncomfortably close to questions of creationism and intelligent design, which are counter-scientific because they do not admit testable hypotheses.
If we take a detour around the semantics of the “silly why,” it does not take long to discover that scientists really do look for explanations. Thousands of studies have searched for causes of cancer or other diseases, and the investigation of just about every mechanism in biology tries to answer a question of causality. In fact, chains of causes and effects are the most prominent means of explaining biology.
2 - I'd rather be fishin’
- Eberhard O. Voit, Georgia Institute of Technology
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Biological research has had a long and esteemed history. So it is not surprising that its concepts, approaches, and methods have been subjected to dramatic changes time and again. Early trial and error in agriculture and animal domestication matured into simple plant manipulations and animal husbandry. Observations of birth and death, growth and decay, led to methods for preserving food for times of dearth. Exploratory dissections of corpses turned into primitive forms of surgery. The worldview of biology exploded with the invention of the microscope, which opened a window into an entirely new world of cells and microorganisms and pathogens. The exploration of medicinal herbs and poisons, as well as the procedures of alchemy and chemistry, motivated the invention of ever-more accurate methods and refined measurement tools.
The search for scientific truth reached a high point in the seventeenth century with the acceptance of the so-called scientific method, which is still considered fundamental today. According to this method, scientific inquiry advances through well-structured, iterative cycles of posing a hypothesis, testing it with experiments, analyzing results, making predictions, testing them, and formulating new hypotheses. In all fairness, one should mention that the roots of this structured type of scientific thinking and experimentation can actually be traced back two millennia to the third century bc Greek physician and anatomist Herophilus, who cofounded the most famous medical school of the time in the Egyptian city of Alexandria. Herophilus performed systematic dissections, which he documented in great detail, and maintained that trustworthy scientific knowledge can only be found on an empirical basis. Nevertheless, the scientific method became the gold standard only in the seventeenth century.
Then the twentieth century rolled along and modern biomedical research exploded. Powerful experimental tools and custom-tailored machines rendered it possible to characterize biological phenomena with a resolution never seen before, down to the level of individual molecules. A prominent highlight was the identification of the structure of DNA, but many other classes of molecule were identified and characterized, and uncounted small and large discoveries occurred during the second half of the century. Most of these breakthroughs resulted directly from the application of the scientific method, which brought forth incredible amounts of precise data and unprecedented insights into the inner workings of life.
5 - Simply engenious!
- Eberhard O. Voit, Georgia Institute of Technology
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Whether it is acting, race car driving, or exploring the moon, it is usually the actors, drivers or astronauts who make the covers of magazines and receive celebrity accolades. And most of them certainly deserve praise for their hard work and the perfect execution of the task at hand. But we all know that their rise to stardom happened on the shoulders of uncounted others whose names flash by in very small font at the end of a movie or are not even mentioned. If we consider car racing, for example, a huge number of individuals contributed to the creation of the infrastructure for the complex system within which an Indy 500 victory is possible. Engineers not only designed and built the cars, but also thought up and actually realized the idea of tough yet light helmets, fire-resistant suits, pits custom-made for speed, the race track itself, and the entire support system allowing drivers to race, spectators to cheer, and venders to sell their wares. And so it happens in many situations that the thinkers and tinkerers and organizers, the makers and builders behind the scenes, remain in the shadows and out of the public eye, even though it is they who make miracles possible. To some degree this is not surprising, as engineers, mathematicians, computer scientists, and ingenious nerds of various types are not notorious for their interest in social hobnobbing or braggadocio. The situation in systems biology is not all that different. Here, it is experimental biologists or clinicians, founders of biotech start-up companies, or producers of novel medicines, who may receive at least a bit of attention from the public, and whose success rests firmly on the shoulders of uncounted, unsung heroes from the field of engineering.
The most dramatic example is arguably the paradigm of experimental systems biology itself, the –omics revolution, where widely noticed insights into the inner workings of genomes, micro-RNAs or protein interactions have only been possible due to ingenious engineering that led to miniaturization and permitted the high-throughput execution of many parallel experiments with robots. Unluckily for their image in the public eye, these robots are nothing like Star Wars’ R2-D2; they don't smile, they don't look sad when scolded, and they do not shake hands.
13 - Time for a change!
- Eberhard O. Voit, Georgia Institute of Technology
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More than 5,000 performances and translations into 17 languages leave little doubt that the off-Broadway musical I Love You, You're Perfect, Now Change hit a nerve with the theater community who vicariously enjoyed the trials and tribulations of their fellow humans in the ever-changing dating and mating turmoil of the late twentieth century. Life may be good, but there is this nagging feeling that something better could be just around the corner. Constancy is comfortable and calms the soul; change is exciting. Indeed, we know that nothing really stands still and that all is in flux, as Heraclitus of Ephesus proclaimed 2,500 years ago.
Except for the “Love You” part, it seems that nature has the same attitude toward its subjects and forces them to change without end. All species are in some way optimized and perfect, because they are clearly more successful than their competitors and survived for generation after generation where others did not. But this “optimal” is merely a current “optimal.” It resulted from unceasing change since life began and will most certainly transform into a new “optimal” in the future. Nature never stops exploring new options, and the only constant throughout the eons seems to have been change.
We all grow and age, and we really do not notice significant changes from one generation to the next, except, of course, that we are much more knowledgeable and sophisticated than all generations before us and most certainly incomparably wiser than our younger peers. But in spite of all evolutionary events, most of us have two eyes, two kidneys, and all those features that make us humans, and these just don't change, at least not fundamentally. Yes, we know that our roots go back to Neanderthals, Denisovans, Homo habilis, and early African hominids like Lucy, but those distant relatives disappeared a very long time ago. Evolution is a topic to be pondered among paleontologists and does not seem to have an urgent role in daily life.
It is actually not all that difficult to observe evolution at work. One only needs to start with a single bacterium and let it divide and multiply. All future cells should be the same, as there is no new source of genes. However, if we check merely a few weeks later, it is very likely that the genetic makeup of the population has become diverse.
Gentle jargon
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Abstraction
The intentional omission or simplification of details of a phenomenon, which allows the design of a manageable conceptual, mathematical or computational model. A representation that focuses on details relevant to the question of interest.
Activator
A molecule or entity that increases the capacity of a process.
Ad hoc model
A mathematical model that is constructed for a specific purpose and without adhering to prescribed model design rules, as opposed to a canonical model.
Adaptive system
A computational or natural system that adjusts its own internal settings to improve its tolerance toward changes in inputs or in its environment.
Affinity
An attractive force between entities. In the case of atoms or molecules, affinity may lead to a chemical reaction.
Agent-based modeling
A simulation method for discrete models, in which each component is an agent whose actions are determined by specific rules. Agents may be humans, animals, cells, molecules or even single atoms.
Algorithm
A sequence of operations or commands constituting a numerical procedure or computer code.
Alkaline
A chemical or solution that is basic, with a pH greater than 7.
Alternative splicing
A mechanism allowing peptides that were transcribed from the same gene and translated from the same mRNA to be combined into different proteins.
Amino acid
The molecular building blocks of proteins. While about 500 amino acids are known, only 22 are used in proteins, and only 20 are directly represented by the genetic code.
Antagonism
A situation where two components act against each other or diminish each other's effect. Antonym of synergism.
Antibody
One of many key proteins of the immune system that sense and neutralize foreign molecules and organisms in the blood. Antibodies are very specific in their binding to non-self entities. Also called an immunoglobulin.
Apoptosis
The technical term for programmed cell death. A complex process in which a cell is genetically programmed to die under certain conditions.
Approximation
The replacement of a (complicated) function with another (simpler) function that retains some, but not all, important features. Usually, the approximation and the approximated function have the same value and the same slope(s) at one point that can be selected as most important for representing a particular situation.
12 - Tell me with whom you go and I'll tell you who you are
- Eberhard O. Voit, Georgia Institute of Technology
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- The Inner Workings of Life
- Published online:
- 05 May 2016
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- 10 May 2016, pp 90-97
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Summary
It is an interesting exercise to surf the blogosphere and other, similarly reliable sources on the Internet in search of the origin of this saying. It's a Spanish quote. It's Russian, Arabic, Mexican. One blogger gives credit to his mother. Several websites assure us that the famous Greek bard Euripides proclaimed it in his tragedy Phoenissae (c. 410 bc) about a group of Phoenician women caught up in a fight among Oedipus’ sons for dominion over Thebes. As Euripides said, “every man is like the company he is wont to keep.” Some bloggers attribute the quote to Confucius’ Words of Wisdom. Others go even further back, crediting the saying to the Assyrians. It seems that we may never know the true origin. But whatever its long history, the widespread usage of this morsel of wisdom points to the universality of the deep human appreciation of companionship and the unique character that bonds a group of friends or associates. Whether it is membership of a club, guilt by association, Benjamin Franklin's pithy comment during the signing of the Declaration of Independence that “we must all hang together, or assuredly we shall all hang separately,” or the astounding popularity of social media: the company one keeps defines one's being and identity.
The observation that connectivity contains genuine information has not escaped the attention of systems biologists, who are utilizing this relationship within the realm of biological networks. We are well aware that nothing in biology occurs in a vacuum and that every component is connected to many others. The investigative challenge derives from the fact that biological networks and their connections are often only vaguely known. Because it is the task of scientists to discover the unknown, the rationale is the following: if the connectivity within a human group contains information about its members, the same could be true for biological networks. If so, it should be possible to extract novel information regarding unknown biological components from the analysis of better known components with which they associate.
The best-characterized associations and networks among biomolecules are formed by metabolites, due to two facts. First, biochemists had been working on metabolites long before DNA was identified and proteins could be manipulated with any efficiency. In fact, one of the important roots of systems biology is the work of nineteenth- and twentieth-century biochemists who formulated mathematical models for chemical reactions in metabolism.
9 - Emergence preparedness
- Eberhard O. Voit, Georgia Institute of Technology
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- Book:
- The Inner Workings of Life
- Published online:
- 05 May 2016
- Print publication:
- 10 May 2016, pp 68-74
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Surprises are great for children's birthday parties, but we surely don't like to receive them from our machines. We would find it rather annoying if the remote control changed TV channels on its own, and we would certainly not want to fly in an airplane that surprised us by deciding to start its descent while high over the ocean. Surprises are events that we do not expect to happen. In the more somber language of science, a surprise is quite similar to the notion of an emergence or emerging behavior. Many definitions of emergence have been proposed, but the core concept is that we cannot explain an emergent property of a system by only studying its parts. One does not have to look far to find emergence. Wave patterns on a lake are difficult to explain in terms of individual water molecules. Table salt enhances the taste of many foods in a pleasing manner, but we would not want to taste its constituents, sodium and chlorine. The parts of a clock by themselves do not tell time. Aristotle already wrote in his book Sophistical Refutations about this “fallacy of division” and the corresponding “fallacy of composition,” which debunks the faulty inference that everything that is true for a part is also true for the whole, and vice versa.
Emergence has had a prominent role for a long time, both in biology and in philosophy. This prominence is not surprising, because no emergence is more stunning than life itself. About 99 percent of the mass of our bodies consists of hydrogen, oxygen, nitrogen, carbon, sulfur, and phosphorus, and roughly 99 percent of all molecules in a typical living cell are water. Yet, if we would buy water and other chemicals, we would still be eons away from a human body. What exactly constitutes the difference between a functioning cell and its components? What is different just before and after the death of a cell or organism? Is emergence the secret of life? The difference between life and its nonliving parts poses a fundamental, unanswered question that has been keeping philosophers and biologists wondering and pondering for a very long time. Similar persistent puzzles can be found throughout nature, from insect colonies to the relationships between thought, memory, and consciousness and their biological foundation.