Why Is The Cell Theory A Theory And Not A Law?

Why Is The Cell Theory A Theory And Not A Law
Cell theory is a theory, not a law because the cell theory does not have enough support to become a law. Cell theory is referred to as the history of scientific theory. All cells come from pre-existing cells, and that is the basic unit reproduction and a basic unit of all organisms.

Why is the cell theory a theory and not a law quizlet?

Which of the following explains why cell theory will not ever become the law of cells? Scientists theories are well-tested explanations, while laws are well-tested descriptions of natural phenomena; one cannot become the other.

Are cells a theory or a law?

Cell theory – Credit for developing cell theory is usually given to two scientists: Theodor Schwann and Matthias Jakob Schleiden, While Rudolf Virchow contributed to the theory, he is not as credited for his attributions toward it. In 1839, Schleiden suggested that every structural part of a plant was made up of cells or the result of cells.

  • He also suggested that cells were made by a crystallization process either within other cells or from the outside.
  • However, this was not an original idea of Schleiden.
  • He claimed this theory as his own, though Barthelemy Dumortier had stated it years before him.
  • This crystallization process is no longer accepted with modern cell theory,

In 1839, Theodor Schwann states that along with plants, animals are composed of cells or the product of cells in their structures. This was a major advancement in the field of biology since little was known about animal structure up to this point compared to plants.

  • From these conclusions about plants and animals, two of the three tenets of cell theory were postulated.1.
  • All living organisms are composed of one or more cells 2.
  • The cell is the most basic unit of life Schleiden’s theory of free cell formation through crystallization was refuted in the 1850s by Robert Remak, Rudolf Virchow, and Albert Kolliker,

In 1855, Rudolf Virchow added the third tenet to cell theory. In Latin, this tenet states Omnis cellula e cellula, This translated to: 3. All cells arise only from pre-existing cells However, the idea that all cells come from pre-existing cells had in fact already been proposed by Robert Remak; it has been suggested that Virchow plagiarized Remak and did not give him credit.

Why is the cell theory considered a scientific theory?

Why is the cell theory considered a scientific theory? It has always been proven to be correct. It was proposed by several scientists. It is an explanation that is well supported.

Can the cell theory ever become a law?

One common misconception is that theories turn into laws over time. In fact, theories do not become laws after repeated experiments, no matter the amount of supporting evidence.

What is the difference between a theory and a law quizlet?

A theory is an explanation for what has been shown many times. A scientific law is a relationship in nature that has been proved many times and there are no exceptions.

Can the cell theory be proven wrong?

According to the cell theory, the cell is the smallest unit of structure and function of all living organisms, all living organisms are made up of at least one cell, and living cells always come from other living cells. Once again, no evidence has been identified that proves this theory is incorrect.

How does a theory differ from a law in science?

In simplest terms, a law predicts what happens while a theory proposes why. A theory will never grow up into a law, though the development of one often triggers progress on the other.

Can a theory contain a law?

Can A Theory Evolve Into A Law? On this A Moment of Science we clear up the difference between a scientific theory and a scientific law. You know, that’s something like the argument that if the theory of evolution were true, it would actually be a law.

  1. In fact, scientists get a little weary of some people saying that the fact that evolution is a theory means that modern science itself isn’t convinced it really happens.
  2. So, it seemed like it would be a good idea to go over the terminology one more time.
  3. Well, the definition of a law is easy.
  4. It’s a description-usually mathematical-of some aspect of the natural world—such as gravity.

The law of gravity describes and quantifies the attraction between two objects. But the law of gravity doesn’t explain what gravity is or why it might work in this way. That’s because that kind of explanation falls into the realm of theory. And the theory that explains gravity is the theory of general relativity.

According to the National Academy of Sciences, a scientific theory is a “well-substantiated explanation of some aspect of the natural world that can incorporate facts, laws, inferences, and tested hypotheses.” In other words, all scientific theories are supported by evidence, and you can test them, and—most importantly—you can use them to make predictions.

So based on that definition, theories never change into laws, no matter how much evidence out there supports them. Formulating theories, in fact, is the end goal of science. So to say evolution is just a theory is actually an argument for it and not against it.

Do we legally own our cells?

by Corinna Cornejo W hether people realize it or not, their every move online, and sometimes offline as well, is being captured by data brokers. These brokers feed a $50 billion market research industry with information that is primarily used to sell us things.

  1. Like those awesome wireless headphones you recently searched for and now seem to see everywhere you go online! This same data gathering and brokering is now being applied to patient data.
  2. Personal health information, genetic data, and even human cells themselves are being freely traded for commercial gain — often without the consumer being aware.

While there are some consumer protections in place, technological developments have outstripped their effectiveness. The implications for individual privacy and property rights are significant, and consumers are beginning to look for better ways to protect and manage their personal health data. Data brokers capture individuals’ every move online and off to build profiles used to market goods and services — Source In the U.S., patient data is feeding the $3.3 trillion healthcare industry at virtually every level. This is in addition to a $156 billion medical device market and a $450 billion pharma industry,

  • To get a sense of just how much personal health data is being collected, look at the 2017 10K filing for IQVIA, the leading healthcare research and data firm.
  • IQVIA reports having “the largest and most comprehensive collection of healthcare information in the world.” TechWith more than 530 million patient records, IQVIA says the data set they hold is more than 30 petabytes (a single petabyte is a million gigabytes) of proprietary data gathered from more than 120,000 data suppliers.

IQVIA also boasts that it can provide information and insights about 85% of pharmaceuticals worldwide (measured against worldwide pharmaceutical sales in 2016). Perhaps the largest broker of healthcare data in the world, IQVIA, boasts having over half a billion comprehensive, anonymized patient records in its database — Source All kinds of health data are being scooped up, archived, and sold. Anything found in an electronic health record, from a diagnosis to your doctor’s notes, is being anonymized and then collected.

Every sales transaction at a pharmacy is archived. Your steps, heart rate, and location data are being sent to the cloud. Even human cells and genetic material from biopsies are being captured and resold. The many ways patient data is used may surprise you. Some of it is used to develop new drugs, medical devices, and therapies.

Some to market healthcare services and insurance coverage. Still other data finds its way to law enforcement agencies. In 1951, a woman named Henrietta Lacks died of cervical cancer. Before she died, and without her or her family’s knowledge, scientists at Johns Hopkins gathered her cells to be used in research. This portrait of Henrietta Lacks hangs in the Smithsonian National Portrait Gallery acknowledging her as “one of the most powerful symbols for informed consent.” — Source HeLa cells, the first human biological materials ever bought and sold, launched a biomedical industry that today is worth hundreds of billions of dollars.

In her bestselling book, The Immortal Life of Henrietta Lacks, Rebecca Skloot explains that neither Henrietta Lacks nor her family received any compensation for the use of her cells. Henrietta’s story launched a robust debate about issues around informed consent, patient privacy, and biological property rights,

It’s a debate that shows no signs of slowing down. On the contrary, recent developments like the partnership between the consumer genomic company 23andMe and pharmaceutical giant GSK have only served to keep these debates going. The 23andMe announcement that it would share genetic data with GSK for the purpose of developing new drugs and therapies once again pushed the issue of biological property rights to the forefront.

Through this agreement, both companies share the rights to profits and royalties that result from the use of their shared genetic data. The consumers who supplied the raw genetic data are not entitled to any compensation. Several companies sell home genealogical DNA kits. Their ads promise that anyone can find out where their ancestors come from just by submitting a sample of saliva and paying around $100.

One company offers a way to fill out your family tree by matching your DNA to living relatives who have matching DNA samples in their database. For a slightly higher fee some of these companies also report certain genetic predispositions to illness the consumer may have, such as breast cancer or psoriasis. Some home DNA kits include reporting on genetic predisposition for certain illnesses — Source What the ads don’t make clear is how this genetic data may be sold to third parties, including pharmaceutical or medical device companies, and nonprofit research organizations.

  1. While all genealogical genetic data shared or sold by these companies is “anonymized” or “de-identified” privacy advocates, researchers, and the DNA kit companies themselves point out that this is not a guarantee of anonymity.
  2. Just recently genetic material was used to identify and arrest a suspect in the case of the Golden State Killer from the 1970s.

Investigators linked DNA found at a crime scene to a person who had a relative in the GEDmatch open source genealogical DNA database. Commercial DNA companies have policies in place requiring a subpoena before surrendering genetic information to law enforcement.

But, in this case, no subpoena was needed because the records searched by law enforcement were voluntarily submitted to an open source database. Investigators found a DNA match to a distant relative (who lived in the 1800s) with their suspect, and from there created dozens of family trees made up of several thousand people.

Based on their data model, police set up surveillance and collected a matching DNA sample from a 72-year-old retiree, who was eventually arrested and charged. Home DNA kit companies offer people a way to opt out of having their data shared. However, more than 80% of 23andMe’s two million customers have consented to their genetic data being used for research.

  • As the Golden State Killer case illustrates, since a person can be identified based on the DNA of a biological relative, opting out may not be sufficient to protect privacy.
  • In our everyday lives we generate an incredible amount of data that can be linked to our health, often in surprising ways.
  • Take digital activity trackers.

Much has been made of how these devices can improve health and healthcare, And their use continues to grow. In its annual consumer digital health survey, Rock Health found that use of digital health wearables grew from 13% in 2015 to 24% in 2017. These trackers collect and store data, often in the cloud, and typically include tools to enable data-sharing.

But trackers are just one of countless sources. Loyalty card purchases are tracked as well. Our jobs and hobbies are used as data points for statistical profiling. Our zip code is used as a source of socio-demographic data. All of these data sources are being used to piece together our digital footprints.

Most of us don’t think about how our shopping habits, hobbies, or zip code could be compiled and interpreted in the context of our health. In a recent article entitled Health Insurers Are Vacuuming Up Details About You — And It Could Raise Your Rates, Propublica reported that health insurers are joining forces with data brokers to collect personal information about hundreds of millions of Americans with little oversight or regulatory scrutiny. Use of fitness trackers while on deployment has raised security concerns — Source Do those of us using trackers know where all our data is going? Or how it’s being used? Probably not. Turns out, the U.S. military didn’t either. Not until it was discovered that some fitness trackers were enabling the enemy to use heat maps on the internet to see the location of service personnel who were running or cycling.

The heat maps revealed both the location and traffic patterns within military bases around the world — including some classified locations. As a result U.S. military personnel are now prohibited from using trackers while on deployment. There are few legal protections when it comes to the privacy and ownership of our health identity data.

Laws governing the use of personal health data were enacted before the widespread use of wearables, activity trackers and the rise of big data. Laws affording us greater protection need to be updated or enacted to address the reality of today’s hyper-connected digital landscape.

HIPAA, the Health Insurance Portability and Accountability Act of 1996, protects only the privacy of patient information held by healthcare providers, insurers, data clearinghouses, and their partners. HIPAA doesn’t apply to any health information that can be collected from wearables, at-home health tests, social media, or other online repositories,

GINA, the Genetic Information Nondiscrimination Act of 2008, bans employers and health insurance companies from accessing DNA information. However, GINA does not apply to life insurance, disability insurance, or long-term care policies, Which means that insurance companies selling these policies can access genetic data and use it to make decisions about price and coverage.

Individuals who’ve gone through any genetic testing must disclose that information when asked by one of these insurers. Questions remain as to just how far an individual’s biological property rights go, It’s commonly accepted that health records belong to the healthcare provider. Individuals often give up their ownership rights, without even realizing it, when they agree to the terms and conditions on social media platforms or some apps.

And court cases like Moore v. Regents of University of California (1990) have ruled that an individual does not actually own their own biological cells. Few people expect legislation anytime soon that will strengthen individual biological property or privacy rights.

  1. In June 2016, the U.S.
  2. Department of Health and Human Services issued a report to Congress on the information not covered by HIPAA,
  3. The report was six years late and did not include any recommended policy changes.
  4. In the face of legislative gridlock in Washington and strong financial incentives at work, consumers can’t necessarily count on policy or industry solutions.
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A new approach is needed. There is a group of entrepreneurs and healthcare companies are working to bring new thinking and approaches to to collecting, securing, and trading the data that makes up our health identities. In my next article I’ll explore these new solutions in more detail.

How do you explain the cell theory?

The Cell Theory Is a Unifying Principle of Biology – The cell theory states that all biological organisms are composed of cells; cells are the unit of life and all life come from preexisting life. The cell theory is so established today that it forms one of the unifying principles of biology.

  • The word cell was first used by Robert Hooke (1635–1703) when he looked at cork with a simple microscope and found what appeared to be blocks of material making up the cork.
  • The term today describes a microscopic unit of life that separates itself from its surroundings by a thin partition, the cell membrane.

Most biologists believe that life arose spontaneously from inanimate matter, but the details of how this could have happened remain unknown, and the time scale was long. Rudolf Virchow, a German pathologist (1821–1902), famously wrote “omnis cellula e cellula”—all cells come from other cells—meaning that spontaneous generation of living things from inanimate matter does not occur over periods as short as our lifetimes.

Do scientists believe in the cell theory?

Cell Theory Scientists once thought that life spontaneously arose from nonliving things. Thanks to experimentation and the invention of the microscope, it is now known that life comes from preexisting life and that cells come from preexisting cells.

What is cell theory answer in short?

The cell theory was proposed by two scientists- Schleiden (1838)and Schwann (1839). It says that all the plants and animals are composed of cells and the cell is the basic unit of life. The cell theory was further expanded by Virchow (1855) by suggesting that all cells arise from pre-existing cells.

Why there is no law in biology?

Laws of biology: why so few? 1 Synthetic Biology Lab, W 120, RIKEN Advanced Sciences Institute, 1-7-22, Suehiro Cho, Tsurumi, Yokohama, 230-0045 Japan Find articles by 2 Department of Environment and Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy Find articles by 1 Synthetic Biology Lab, W 120, RIKEN Advanced Sciences Institute, 1-7-22, Suehiro Cho, Tsurumi, Yokohama, 230-0045 Japan 2 Department of Environment and Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy Pawan K. Corresponding author. Received 2009 Jul 10; Revised 2009 Nov 5; Accepted 2009 Nov 24. © The Author(s) 2009 This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Finding fundamental organizing principles is the current intellectual front end of systems biology. From a hydrogen atom to the whole cell level, organisms manage massively parallel and massively interactive processes over several orders of magnitude of size. To manage this scale of informational complexity it is natural to expect organizing principles that determine higher order behavior.

Currently, there are only hints of such organizing principles but no absolute evidences. Here, we present an approach as old as Mendel that could help uncover fundamental organizing principles in biology. Our approach essentially consists of identifying constants at various levels and weaving them into a hierarchical chassis.

  1. As we identify and organize constants, from pair-wise interactions to networks, our understanding of the fundamental principles in biology will improve, leading to a theory in biology.
  2. Eywords: Mendel, Laws, New, Standards, Constants, Biology In scientific jargon, law describes a true, absolute and unchanging relationship among interacting elements.

Unlike in some fields, social customs and authorities do not determine the establishment of laws in science. Given that laws are derived from empirical observations, it implies that laws symbolize regularities endorsed by a majority opinion. People also use terms like rules and principles to describe consistent relationships expressed by mathematical equations e.g., Heisenberg uncertainty principle, the causality principle of physics.

  • Here we will adopt the less demanding and the more useful definition of law as ‘a frequently observed regularity that allows for a substantial improvement of our prediction ability in well-defined systems’.
  • The distinction among terms rule, principle, theory and hypothesis, is beyond the scope of this paper.

Our knowledge of laws, theories and hypotheses can be traced to physical sciences. While physicists have identified a number of laws related to mass, energy, momentum and so on, some of the ‘laws’ known to biologists are those of Mendelian Inheritance (Mendel ), metabolic scaling (Kleiber ) and the recent power laws (Jeong et al.).

However, even these laws are not absolute—they come with exceptions. For example, non-random segregation of chromosomes (White et al.) and homozygous mutants parenting a normal offspring, are deviation from Mendelian Inheritance (Lolle et al.). The prevailing effect of these exceptions with the overwhelming role of boundary conditions makes paradigms of scientific laws too demanding, like those based on Popper’s falsifiability concept which is of little or no use in biology (Stamos ).

It is therefore useful to think of biological regularities as broad generalizations than stiff relationships among interacting components. Here we would like to discuss why absolute generalizations are rare in biology, and what can be done to fill the gap? Broadly speaking, to discover new regularities and laws we either follow top–down or the bottom–up approach (Fig.).

  1. In the top–down approach, the search begins with an external observation e.g., Newton’s laws of motion.
  2. The observer intuitively imagines a set of elements, a set of interactions and a mathematically expressible form to connect the two.
  3. Components are weaved into a mental map and experiments are planned to verify or nullify the model.

If the experimental observations repeatedly support the model under different environmental settings, the model takes a more generalized form and may be ultimately adopted, with a broad consensus, as a law. In the bottom–up approach, one begins by collecting data on individual elements i.e., experimentally determine properties of components in isolation and in association with other interacting elements.

Data are collected in different environmental settings and patterns are searched. Once patterns are found, experiments are repeated to confirm observations. The evidence of consistent relationship among interacting components in different environmental settings provides a strong basis to represent patterns in a logical form.

This approach was typically used by Gregor F. Mendel to deduce Laws of Inheritance (Mendel ). In both the approaches, scientists contribute their own subjective judgment in terms of what is contingent (exceptions to the rule) and what is essential (obeying the rule).

  • The extent of exceptions and commonalities vary among different instances and clearly has to do with the scale at which the observations are made.
  • In both top–down and bottom–up approaches, the key is to find a consistent pattern.
  • For example, an equation consistently explaining regularity is a strong indication of a law.

The top–down approach i.e., from imagination to observation, has been often used in physics, while the bottom–up approach i.e., from observation to imagination has been used in biology. Interestingly, we have laws for things that we cannot see e.g., light, gravity and sound, but no laws for things that we see e.g., DNA, RNA, proteins and cells.

This is due to the fact that former are based on the consistent behavior of elementary particles compared to the latter where interactions are frequently probabilistic. Going further, one understands that the well-known law of gravity is nothing but a name given to the striking regularity observed in the motion of the bodies.

However, even this regularity is obtained by a subjective choice of what is essential. Pure observation tells us that some bodies e.g., leaves on a windy day, go up and down and not directly down towards the earth. Due to this reason Aristotle spoke about two kinds of bodies: light and heavy.

Only in the XVII century Galileo decided to think of the difference between lightness and heaviness as contingent and identified the tendency to fall down (gravity) as the key feature. Thus the concept of gravity is essentially a rationalization of the observed behavior of bodies. The search for the material counterpart of this force in terms of particles (gravitons) is still elusive and highly uncertain.

In the same way if we clap our hands a nearby mouse will surely run away with a reliability degree of predictability, comparable to that of falling bodies. However, if we try to explain this very repeatable pattern in terms of mouse microarray profile, before and after the clap we will surely have a hard time.

  1. The key message is that the molecular level description is sometimes inadequate to explain higher-level behavior of organisms.
  2. The reason why bottom–up approach is preferred in biology is due to the presence of the large variety of context-dependent data types.
  3. Due to this reason, a good imagination i.e., top down approach, cannot assure a consistent molecular level description.

Furthermore, a rule in biology often comes with exceptions. For example, in the early 1990s telomerase-dependent telomere elongation was considered a kind-of rule in biology. However, the discovery of transposon-dependent telomere maintenance in Drosophila (Levis et al.) demonstrated an exception to this rule.

  1. This is not to indicate that exceptions are strange phenomena—they simply point to the undiscovered states of the system.
  2. Given the impracticality of studying all possible system states v/s contexts, one should expect to see exceptions along with common trends in biology.
  3. For example, the genetic code that has a fairly straightforward implementation comes with the codon bias (Sharp and Li ).

The mouse example (described earlier) indicates that the macroscopic level of observation is repeatable and reliable but unhelpful to describe the workings of a system in its entirety. In this case, like in any other complex system, the most fruitful layer of analysis is the mesoscopic level i.e., half-way between trivial determinism (escapability) and pure stochasticity (assumed fluctuation of protein concentration before and after the escape).

  • It is at the mesoscopic level that physiological and anatomical ‘links’ between microscopic and macroscopic levels are formed e.g., nervous system organization and dynamics (Laughlin et al.).
  • As a matter of fact any law dealing with the organized matter, from paramagnetic materials to organisms, resides where meaningful correlations between elementary units give rise to macroscopic regularities that are largely independent from microscopic details.

This independence from microscopic description is at the basis of the observed resilience of biological systems at large. Given the background setting of immense data scarcity, how could Mendel succeed in discovering laws of inheritance when people had no clue about underlying components and interactions? The field of biochemistry was still in its infancy and molecular biology was unheard of.

  • There was hardly any technological aid to help Mendel ask the important fundamental questions in biology.
  • In our opinion, the key reason for his success was his clear understanding that he needed to find ‘constants’.
  • It is interesting that the word “constant” appeared 69 times in his paper (Mendel )! Mendel chose seven pairs of contrasting characteristics and ensured (through in-breeding) that each plant consistently exhibited the same feature.

Even if he had included the eighth feature or considered only six pairs of contrasting characteristics, he would have still reached the same conclusion. That is because Mendel “artificially eliminated” noise from his samples and considered only those plants exhibiting consistent patterns both in isolation i.e., monohybrid crosses and in a group i.e., di-hybrid crosses.

It is important to understand that these seven pairs of contrasting features i.e., phenotype-level constants, did not change with time, fluctuating environment and so on. Due to this reason i.e., the strength of the data quality, Mendel only used elementary mathematics i.e., addition and division, to obtain the Laws of Inheritance.

In contrast, these days we are inundated with a morass of expression data, have huge computational power, apply advance mathematical techniques, but are nowhere close to identifying the network equivalent of Mendelian laws. This is because moving from the consistent phenotype level to the dynamic molecular level exposes us to a large body of variables e.g., stochastic gene expression (Elowitz et al.

; Cai et al.) and concentration gradients influencing cell–cell interactions (Gurdon and Bourillot ). The key, therefore, is to mine this vast space of variables for biological constants. The endpoints i.e., the top-level phenotype and the bottom-level genome sequence may be considered as ‘boundary conditions’ of the living systems.

These two ends must be connected through intermediate levels, to understand biology as a whole. Since the concept of “constant” is important here, it is useful to give the word ‘constant’ a definition. At its core, a constant is a measurement that comes out the same every time (Laughlin ).

  • The seven pairs of contrasting characters (Mendel’s work) are examples of constants at the phenotype level.
  • The genome sequence may be considered as another “constant” level, even though breaks, transposons, error-prone repairs affect the composition of the original DNA sequence.
  • Nevertheless, the DNA repair mechanisms actively repair DNA breaks maintaining the integrity of essential genome sequence.

Moving from the constant-phenotypic to the constant-sequence level, one comes across several layers of variables e.g., cell–cell interaction, network and pathway dynamics, molecular interactions and stochastic gene expressions. In this space between genome and phenotype, probabilities, fluctuating concentrations, molecular crowding, context dependencies and emergent phenomenon play a significant role.

Due to this reason, this layer is the domain of statistical laws. It is the mesoscopic level where, in our opinion, useful principles for understanding the organization of biological systems, reside. But this is not the place to get deeper (we will come back indirectly on this aspect in terms of emergent phenomena).

Here we would like to concentrate on the ‘law-like’ style of reasoning. Clearly the mesoscopic scale has been mined for laws e.g., thermodynamics is the home of the most precise and reliable laws in physics, but this precision comes from the averaging over huge ensembles of units, each unit being almost completely ‘unaware’ of the ensemble features.

  1. So, how about mechanistic, microscopic, laws in biology? To address this issue, even though the genome is an attractive ‘microscopic level’ to begin with, it cannot provide all the answers.
  2. The genome sequence does not directly control downstream interactions of molecules the pathway and network levels.
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Moving from the sequence level to the interaction level, it is important to find relationship constants, i.e., a unique gene (or a group of unique genes) controlling a process. Another example of an interaction constant is a protein consistently interacting with another protein in several organisms under well-defined conditions.

  1. However, it is unlikely that we will ever find an absolute ‘interaction constant’ common to all the organisms.
  2. A trend rather than an absolute correlation is what we should probably expect in biology.
  3. It would be useful to identify consistent interaction patterns at the RNA–DNA level, protein–DNA level, pathway and network level, cell–cell interaction level, and build a ‘constant chassis’ from the sequence level to the phenotype level (Table ).

Such a ‘chassis’ could help identify core biological processes, around which variables operate. If such a chassis is built, we should expect to see connectivity constant in the beginning, followed by quantitative constants e.g., thresholds. Laws/rules/patterns at various levels of biological systems

Feature Laws/rules/patterns
Social networks, population based Power law, small world, Hardy–Weinburg law
Organism level Metabolic rate correlations
Cell level Cell division
Molecular networks Power law, small world
Information transfer Genetic code options
Molecular socialization Folding and interaction options
Atomic interactions Laws of chemistry
Atom Laws of physics

Although Fig. describes a partial list of constants, there are obviously more levels/sublevels and, in fact, several ways of representing the data. At the sequence level, sequence motifs (DNA and proteins) seem to be reasonable examples of genome-level constants.

At the protein structure level, highly conserved folds and binding domains (e.g., helix-turn-helix, zinc finger, and leucine zipper) seem to be examples of structure-level constants. At the molecular-interaction level, conserved folds could be the examples of interaction constants. At the network level, the ‘power law distribution’ (Jeong et al.) and ‘the small world phenomenon of metabolic networks’ (Wagner and Fell ) are examples of network level constants.

A partial list of constants in Biology Furthermore, it would be useful to find relationship among: (1) constants at the same level, (2) among constants at different levels and (3) among constants and variables at the same and different levels, to get a hierarchical systems perspective of the constants-organization.

  • In such a setting relationships among elements could be described in the form of a ‘periodic’ table (Dhar ).
  • A bio-periodic table is a tabular arrangement of elementary interacting components that, when connected, lead to higher-level properties of systems.
  • In our opinion, the mesoscopic level of “protein fold”, instead of a microscopic level of DNA sequence, represents a reasonable building block of such a periodic table.

The concept of a unit in this sense is not a structural irreducible minimum but a “workable unit” that provides enough description to reliably compose circuits. In the field of engineering one also uses higher-level abstraction and does not compose electronic circuits from a collection of atoms or subatomic particles (as elementary units).

  1. Likewise in biology, a cell can be considered a unit for a tissue-level description.
  2. An interaction can be considered a unit for a network-level description.
  3. Folds are reasonable fundamental units of a bio-periodic table, as they show less redundancy than the sequence level data and are directly responsible for most of the interactions, at the level of pathways and networks.

Moving from folds upwards, a bio-periodic table can connect fold-level description to the cell-level response through a series of hierarchical information transfers. Two key issues arise in such a description: the need to build a ‘fold interaction table’ and, the need to build ‘interaction management’ table.

  1. An ‘interaction management table’ would set “boundary conditions” to all possible interactions by adding regulatory loops, quantitative thresholds and contextual descriptions.
  2. It would be interesting to see how a bio-periodic table performs and evolves, as data comes in.
  3. Even though the term ‘table’ has been used to bring conceptual clarity from engineering design perspective, the bio-periodic table would most likely resemble a tree.

Standards are created to establish quality norms and requirements for the community. A scientific standard is a reference measurement used for comparisons. Once tested, validated and published, standards are adopted widely. The BioBricks project (Shetty et al.) is an engineering inspired approach to create de facto standards for building organisms.

  1. Though the approach is novel and interesting, it is unclear whether engineering level standards will ever be possible in composing biological systems.
  2. Also we do not know of a biobrick-based system that cannot be constructed without biobricks, or the boundary conditions beyond which adding more biobricks will result in the loss of control.

In general, even though reverse engineering of organisms is a logical approach, it is early to say if the bottom up construction is going to be easier than disassembling them top–down. The key difference between standards and constants is in the system they belong to.

  • Standards” are artificially created reference points against which other things can be evaluated.
  • Constants” describe consistent observations derived from natural systems.
  • To specifically describe this concept in the context of biology-constructing systems bottom–up would be easier if there are standards in biology.

However, to understand naturally evolved systems on the whole, systems biology would need constants e.g., a constant interaction, a constant phenotype, a constant expression profile and so on. The question is: can standards and constants meet at some point in the future i.e., can human created reference points turn out to be naturally occurring constants in biological systems? In our opinion, standards are reasonable constraints on the system that can help us uncover new information in a controlled environment.

By creating standards in biology and applying them for the in vivo construction, it is quite possible to identify naturally occurring biological constants and rules of biological composition, leading to the discovery of new regularities in biology. Laws are formal representations of objective reality.

They do not necessarily represent the total reality but symbolize a specific feature of the system. Richard Feynman prefers to view Laws as rhythms or pattern in nature apparent only to the eye of the observer (Feynman ). While studying these patterns sometimes we tend to overlook the influence of one pattern on the other.

A case in point is the well-known Law of Gravitation. Newton’s Law of universal gravitation describes attraction between bodies with mass and is widely used in planetary studies. However, this Law does not truly describe how bodies behave. For bodies with significant mass and charge, the Law of universal gravitation and Coulomb’s Laws of electric charges must interact to determine the final force.

Neither of these describes how bodies behave real time (Cartwright ). Newton’s theory does not capture the impact of gravitational force from other heavenly bodies in determining the final force. Also, the modern thinking is that Newton’s Laws are emergent i.e., these laws symbolize a collective property exhibited by aggregation of quantum matter into macroscopic fluids and solids (Laughlin, ).

Similarly, the well-known laws of pressure and volume break down when the numbers of gas molecules reduce below a certain threshold. In other words, laws hold well only in a certain range below or above which, uncertainty exists. It is important to recognize that collective coordination of entities, at several levels of organizational hierarchy is not only fundamental to our existence but also provide the right material for discovering new laws in science.

More than 7 million protein sequences and more than 50,000 protein structures have been experimentally determined (Kelley and Scott ). With the emergence of the new direction of metagenomics, many more molecular components and interactions are waiting to be discovered.

  1. Therefore, it is logical to assume a fundamental organizing principle to explain how information is efficiently transferred over large bio-molecular networks.
  2. Whatever happens within the organisms might be interpreted as biology but it is important to clearly understand the distinction between chemistry and biology.

Everything an organism is composed of does not belong to the realm of biology. The construction of matter from atoms and molecules can be described with the help of Physics and Chemistry. The layer of atomic structure is described by Physics. The layer of atomic interaction is described by chemistry.

One might think of protein–protein or protein–DNA interactions in terms of laws and rules in biology. However, even these bio-molecular structures and interactions are the outcome of physical processes. The question is: “where does the real biology begin”? In our opinion, the real biology is composed of space that exists between interaction and function i.e., biology must operate at levels higher than that of atoms and molecules.

In other words, the real biology exists in the purpose and not just plain physical interactions. One may consider feedback loops as the physical equivalent of the purpose, In fact, organisms may be abstracted as “similar-input v/s unique-output” black boxes that vary in terms of feedback loops, more than the building blocks themselves.

In search of new laws in biology, it would be pertinent to ask: ‘why it exists’ in addition to ‘how it exists’? This question is actually a subset of a broader question concerning the purpose of our existence i.e., why life exists? Probably the ultimate answer resides somewhere at the boundary of philosophy and material science.

At a physical level, the laws exist because of an inherent order in the system. Science simply describes this inherent order in the form of rules, principles and laws. So, the question—why laws exist is because regularities exist. Why regularities exist is because molecular structures fit into each other—the structure-enabled interactions is the root cause of higher-level regularities.

  • If an object does not interact it is probably an evolutionary appendage, waiting to be recycled or to be structurally modified for a minimal interaction.
  • Laws are human-invented formalisms created to make a sense of what’s naturally available and build new designs from existing raw materials.
  • The discovery of laws, based on well known constants in physics e.g., Planck’s constant, speed of light, laws of motion) encourages search for similar regularities in biology.

At the phenotypic level, Mendelian Laws of Inheritance provide a reasonable framework. However, at the cell–cell interaction and molecular networks levels, fundamental organizing principles remain to be discovered. In biology, it is difficult to conceive the existence of (1) components with predictable behavior, (2) non-decomposable components similar to the elements of a periodic table and (3) universal biological constants equivalent to those of the physical constants.

In essence there is no ‘standard trajectory’ in biology—every biological decision is optimal in a given environmental context. However, due to complex nature of biological organization it is difficult to think of a universal law or a theory in biology connecting all the levels, from atoms to ecosystems.

One should look for generalizations at various levels instead. To find such generalizations it is useful to develop novel measurement technologies that capture the dynamic nature of biological systems and more importantly catch emergent properties arising from a group behavior of interacting components.

Once the core principles of collective organization are uncovered, the species-specific variation can be explained by considering metabolic/regulatory plug-ins into the fundamental framework. It will be similar to describing foundational rules of automobile construction and adding unique functionalities to build unique car models.

Although it is unclear whether we will ever be successful in finding new laws/principles in biology, our paper presents a fresh approach to address this issue. From qualitative data, some static constants have been identified e.g., sequence and structural motifs, power laws and so on.

However, one needs to extract dynamic constants from quantitative data e.g., concentration thresholds. One must be aware that the term ‘constant’ does not catch the value that remains the same independent of the boundary conditions. Each ‘apparently local constant’ takes along a ‘non local’ character by the inheritance of the structure and dynamics of the network.

This matches very strictly with the problem of impedance in electrical engineering and was exploited in terms of an electrical based metaphor (Palumbo et al., ). The correlation of metabolic rate with the body mass in both prokaryotes and eukaryotes (Kleiber ) tells us that the search for regularities in biology is a worthwhile effort.

  • However, in future we need to address the issue at molecular network complexity.
  • Finally, one may ask if it makes sense to identify regularities from data that is often incomplete and sometimes incorrect too.
  • The question is: can we make generalizations from incompletely understood systems? There is another school of thought that says laws in biology simply do not exist.

According to this belief, organisms emerge from spontaneous order. We would like to argue that spontaneous order does not point towards a randomly organized system. Spontaneous order merely indicates that components find each other and create a robust system.

Unless the act of finding each other is based on well-defined rules, it is difficult to explain how consistent phenotype can repeatedly show up from molecular interactions. In this paper we have explored the possibility of using Mendelian approach for finding new laws in biology. There maybe several, more efficient approaches than constant-based approach.

Irrespective of all this, it is important to recognize that laws formalize consistent observations; they do not explain them. This work was supported by intramural funding from RIKEN. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Cai L, Friedman N, Xie XS. Stochastic protein expression in individual cells at the single molecule level. Nature.2006; 440 :358–362. doi: 10.1038/nature04599. Cartwright N. How the laws of physics lie. Oxford: Oxford University Press; 1983.p.57. Dhar PK. The next step in biology: a periodic table? J Biosci.2007; 32 :1005–1008. doi: 10.1007/s12038-007-0099-8. Elowitz MB, Levine AJ, Siggia ED, Swain PS. Stochastic gene expression in a single cell. Science.2002; 297 :1183–1186. doi: 10.1126/science.1070919. Feynman R. The character of physical law. Cambridge: MIT Press; 1967.p.13. Gurdon JB, Bourillot P-Y. Morphogen gradient interpretation. Nature.2001; 413 :797–803. doi: 10.1038/35101500. Jeong H, Tombor B, Albert R, Oltvai ZN, Barabási AL. The large-scale organization of metabolic networks. Nature.2000; 407 :651–654. doi: 10.1038/35036627. Kelley LA, Scott MA. The evolution of biology. A shift towards the engineering of prediction-generating tools and away from traditional research practice. EMBO Rep.2008; 9 :1163–1167. doi: 10.1038/embor.2008.212. Kleiber M. Body size and metabolism. Hilgardia.1932; 6 :315–353. Laughlin RB. A different universe: reinventing physics from the bottom down. London: Basic Books; 2005. Laughlin RB, Pines D, Schmalian J, Stoykovic BP, Wolynes P. The middle way. Proc Natl Acad Sci USA.2000; 97 :32–37. doi: 10.1073/pnas.97.1.32. Levis RW, Ganesan R, Houtchens K, Tolar LA, Sheen FM. Transposons in place of telomeric repeats at a Drosophila telomere. Cell.1993; 75 :1083–1093. doi: 10.1016/0092-8674(93)90318-K. Lolle SJ, Victor JL, Young JM, Pruitt RE. Genome-wide non-mendelian inheritance of extra-genomic information in Arabidopsis. Nature.2005; 434 :505–509. doi: 10.1038/nature03380. Mendel JG (1865) Versuche über Plflanzenhybriden Verhandlungen des naturforschenden Vereines in Brünn, Bd. IV für das Jahr; Abhandlungen, pp 3–47 Palumbo MC, Colosimo A, Giuliani A, Farina L. Functional essentiality from topology features in metabolic networks: a case study in yeast. FEBS Lett.2005; 579 :4642–4646. doi: 10.1016/j.febslet.2005.07.033. Palumbo MC, Colosimo A, Giuliani A, Farina L. Essentiality is an emergent property of metabolic network wiring. FEBS Lett.2007; 581 (13):2485–2489. doi: 10.1016/j.febslet.2007.04.067. Sharp PM, Li W-H. The codon adaptation index—a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res.1987; 15 :1281–1295. doi: 10.1093/nar/15.3.1281. Shetty RP, Endy D, Knight TF., Jr Engineering BioBrick vectors from BioBrick Parts. J Biol Eng.2008; 2 :5. doi: 10.1186/1754-1611-2-5. Stamos DN. Popper laws, and the exclusion of biology from genuine science. Acta Biotheor.2007; 55 (4):357–375. doi: 10.1007/s10441-007-9025-6. Wagner A, Fell DA. The small world inside large metabolic networks. Proc Biol Sci.2001; 268 :1803–1810. doi: 10.1098/rspb.2001.1711. White MA, Eykelenboom JK, Lopez-Vernaza MA, et al. Nonrandom segregation of sister chromosomes in Escherichia coli, Nature.2008; 455 :1248–1250. doi: 10.1038/nature07282.

: Laws of biology: why so few?

Can a theory become a fact?

When does a theory become a fact and who decides? Pillip/Alamy Wolf Kirchmeir Blind River, Ontario, Canada A theory never becomes a fact. It is an explanation of one or more facts. Tim Lewis Narberth, Pembrokeshire, UK A well-supported evidence-based theory becomes acceptable until disproved. It never evolves to a fact, and that’s a fact.

  • Nick Canning Coleraine, County Londonderry, UK Many scientists, including the late Stephen Hawking, are happy to say that a theory never becomes a fact.
  • It is always an interpretive structure that links facts, which are themselves reproducible experimental observations.
  • The “truth” of a theory is determined by its usefulness in linking the largest number of facts and predicting new ones that haven’t been observed yet.

Discovery of facts that don’t fit the theory will lead to the search for a new theory.

  • Matt Chamings
  • Barnstaple, Devon, UK
  • This question misunderstands what a theory is in the same way that creationists dismiss evolution as “just a theory”.

A theory isn’t speculation about what might be true. It is a set of propositions that seek to explain a particular phenomenon or set of facts. A theory can be tested and shown to be accurate or modified as the evidence requires. Even when a theory is accepted as fact, it remains a theory.

Alan Harding London, UK While a scientific theory such as Isaac Newton’s theory of gravitation makes an infinite number of predictions, it can only be verified by a finite number of observations, so it can never be seen as irrefutably correct. In philosophy, this is the problem of induction. The fact that science rests on rather fragile epistemological foundations opens it to attack from anti-science movements, for example when creationists claim that Darwinian evolution is “only a theory”.

All science is, to some extent, “only a theory”, but its great strength is that theories that don’t fit real world observations are eventually discarded. This has happened with Newton’s theory of gravitation, now seen to be a special case of general relativity.

  1. So in reality, in science we do not have facts or proof, all we have is the best-available, most widely accepted theory at the time.
  2. John Wallace
  3. Liverpool, UK

Evolutionary pressures have favoured some organisms that are aware of their surroundings and able to react to them. Humans have become rather good at this. We also have curiosity, which leads us to look hard at our surroundings and try to make sense of what we find.

So, we gather information, and try to invent theories that could explain what we see. The better theories don’t just explain all the data so far observed, they enable predictions. If confirmed by data, this strengthens our reliance on the theory, Take satnav systems, for example. These rely on the predictions of relativity and quantum theories.

Every time a satnav system is used, the theories it was based on are tested again. But, until we know “everything”, theories, even the successful ones, will still be theories. To answer this question – or ask a new one – email, Questions should be scientific enquiries about everyday phenomena, and both questions and answers should be concise.

We reserve the right to edit items for clarity and style. Please include a postal address, daytime telephone number and email address. New Scientist Ltd retains total editorial control over the published content and reserves all rights to reuse question and answer material that has been submitted by readers in any medium or in any format.

: When does a theory become a fact and who decides?

Can a law become a theory if so how?

Not really, because conceptually they actually refer to two different concepts. In general, a scientific law is the description of an observed phenomenon. It doesn’t explain why the phenomenon exists or what causes it. The explanation of a phenomenon is called a scientific theory.

Which is more correct a theory or law?

Law – Scientific laws are short, sweet, and always true. They’re often expressed in a single statement and generally rely on a concise mathematical equation. Laws are accepted as being universal and are the cornerstones of science. They must never be wrong (that is why there are many theories and few laws).

  1. If a law were ever to be shown false, any science built on that law would also be wrong.
  2. Examples of scientific laws (also called “laws of nature”) include the laws of thermodynamics, Boyle’s law of gasses, the laws of gravitation.
  3. A law isn’t better than a theory, or vice versa.
  4. They’re just different, and in the end, all that matters is that they’re used correctly.

A law is used to describe an action under certain circumstances. For example, evolution is a law — the law tells us that it happens but doesn’t describe how or why. A theory describes how and why something happens. For example, evolution by natural selection is a theory.

  1. It provides a host of descriptions for various mechanisms and describes the method by which evolution works.
  2. Another example is Einstein’s famous equation E=mc^2.
  3. The equation is a law that describes the action of energy being converted to mass.
  4. The theories of special and general relativity, on the other hand, show how and why something with mass is unable to travel at the speed of light.

Hopefully, this has helped expand your understanding of what it means when scientists call something a hypothesis, a theory, or a law. And if you see someone in Internet Land using the terms inappropriately, please, shoot them this article.

Which statement best explains the difference between a law and a theory?

A) A law is truth; a theory is mere speculation.

Is a theory an explanation of a law?

Theory and law are two terms that we encounter in the field of sciences. Although theories and laws explain various concepts in science, there is a definitive difference between theory and law. Theory explains why something happens whereas law describes what happens when certain conditions are present.

What violates the cell theory?

How do viruses violate the cell theory. Answer Verified Hint: According to cell theory, living things are made up of one or more cells, that the cell is the basic unit of life, and that new cells arise from existing cells. Cell theory describes the organelles of a cell and how their functions give cells their names.

Complete answer: According to the hypothesis, all living beings are composed of cells and cell components, which are the smallest substances that can be called ‘living.’ A life form’s useful unit is the cell. Viruses are acellular constructions with nucleic acid corrosive and an external protein coat.Viruses are not made of cells, and they are incapable of maintaining a stable state, growing, or producing their own energy.

Viruses, despite their ability to adapt to their surroundings and replicate, are more akin to androids than real living organisms.As a result, they are a special case for cell hypothesis because all living beings are capable of DNA replication and multiplication without the assistance of anyone else.

Cells are life’s smallest unit. Every cell is a semi-permeable phospholipid film folded over cytosol or a solution of water and broken down solutes. All cells rely on DNA to store the information needed to create the atoms they need to function.Since viruses are not made of cells, and do not use cells in any of their processes, they are not related to the cell theory.

A virus is nothing more than a protein coat surrounding a piece of DNA or RNA. Sure, they can adapt to the environment and respond to stimuli, but they do not use energy, nor do they grow. Note: Infection is nothing more than a protein coat encasing a piece of DNA or RNA.

Who disproved cell theory?

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  • In the 17th century, observations of microscopic life led to the development of the cell theory: the idea that the fundamental unit of life is the cell, that all organisms contain at least one cell, and that cells only come from other cells. Despite sharing certain characteristics, cells may vary significantly. The two main types of cells are prokaryotic cells (lacking a nucleus) and eukaryotic cells (containing a well-organized, membrane-bound nucleus). Each type of cell exhibits remarkable variety in structure, function, and metabolic activity. This chapter will focus on the historical discoveries that have shaped our current understanding of microbes, including their origins and their role in human disease. We will then explore the distinguishing structures found in prokaryotic and eukaryotic cells.

    • 3.E: The Cell (Exercises)
    • 3.0: Spontaneous Generation The theory of spontaneous generation states that life arose from nonliving matter. It was a long-held belief dating back to Aristotle and the ancient Greeks. Experimentation by Francesco Redi in the 17th century presented the first significant evidence refuting spontaneous generation by showing that flies must have access to meat for maggots to develop on the meat. Louis Pasteur is credited with conclusively disproving the theory and proposed that “life only comes from life.”
    • 3.1: Foundations of Modern Cell Theory Although cells were first observed in the 1660s by Robert Hooke, cell theory was not well accepted for another 200 years. The work of scientists such as Schleiden, Schwann, Remak, and Virchow contributed to its acceptance. Endosymbiotic theory states that mitochondria and chloroplasts, organelles found in many types of organisms, have their origins in bacteria. Significant structural and genetic information support this theory. The miasma theory was widely accepted until the 19th century.
    • 3.2: Unique Characteristics of Prokaryotic Cells Prokaryotic cells differ from eukaryotic cells in that their genetic material is contained in a nucleoid rather than a membrane-bound nucleus. In addition, prokaryotic cells generally lack membrane-bound organelles. Prokaryotic cells of the same species typically share a similar cell morphology and cellular arrangement. Most prokaryotic cells have a cell wall that helps the organism maintain cellular morphology and protects it against changes in osmotic pressure.
    • 3.3: Unique Characteristics of Eukaryotic Cells Eukaryotic cells are defined by the presence of a nucleus containing the DNA genome and bound by a nuclear membrane (or nuclear envelope) composed of two lipid bilayers that regulate transport of materials into and out of the nucleus through nuclear pores. Eukaryotic cell morphologies vary greatly and may be maintained by various structures, including the cytoskeleton, the cell membrane, and/or the cell wall The nucleolus in the nucleus of eukaryotic cells is the site of ribosomal synthesis.

    Thumbnail: A 3D rendering of an animal cell cut in half. Image used with permission (CC -BY-SA 4.0; Zaldua I., Equisoain J.J., Zabalza A., Gonzalez E.M., Marzo A., Public University of Navarre).

    Which cell theory is true?

    Cell Theory – The microscopes we use today are far more complex than those used in the 1600s by Antony van Leeuwenhoek, a Dutch shopkeeper who had great skill in crafting lenses. Despite the limitations of his now-ancient lenses, van Leeuwenhoek observed the movements of protista (a type of single-celled organism) and sperm, which he collectively termed “animalcules. Why Is The Cell Theory A Theory And Not A Law Figure \(\PageIndex \): Structure of an Animal Cell: The cell is the basic unit of life and the study of the cell led to the development of the cell theory. By the late 1830s, botanist Matthias Schleiden and zoologist Theodor Schwann were studying tissues and proposed the unified cell theory.

    • The unified cell theory states that: all living things are composed of one or more cells; the cell is the basic unit of life; and new cells arise from existing cells.
    • Rudolf Virchow later made important contributions to this theory.
    • Schleiden and Schwann proposed spontaneous generation as the method for cell origination, but spontaneous generation (also called abiogenesis) was later disproven.

    Rudolf Virchow famously stated “Omnis cellula e cellula” “All cells only arise from pre-existing cells. “The parts of the theory that did not have to do with the origin of cells, however, held up to scientific scrutiny and are widely agreed upon by the scientific community today.

    1. The cell is the fundamental unit of structure and function in living things.
    2. All organisms are made up of one or more cells.
    3. Cells arise from other cells through cellular division.

    The expanded version of the cell theory can also include:

    • Cells carry genetic material passed to daughter cells during cellular division
    • All cells are essentially the same in chemical composition
    • Energy flow (metabolism and biochemistry) occurs within cells

    Why is the cell theory considered a scientific theory quizlet?

    What makes the cell theory a scientific theory? It is based on the work of many scientists and leads to accurate predictions. As the concentration of molecules increases outside of a cell, more and more molecules enter the cell.

    Can a theory become a law quizlet?

    One common misconception is that theories become laws after they have been proved by an experiment. In reality, theories do not become laws. When new evidence presents itself, scientists change theories to match up with the evidence.

    What is the cell theory quizlet?

    What is the cell theory? The cell theory states that: – All living organisms are composed of cells. Multicellular organisms (example: humans) are composed of many cells while unicellular organisms (example: bacteria) are composed of only one cell. Cells are the basic unit of structure in all organisms.

    What is cell theory simple answer?

    Modern cell theory. noun. theory that cells are the basic structural, functional, and organizational units of both single-celled and multicellular organisms; cells divide and pass on hereditary information; and energy flows within cells.