Have you ever wondered what would happen if we could predict what the future holds for us in a particular field, given our talent and the amount of effort we put into it? Then we can choose a better path and not waste our time and life in different ways. We all know that genetics and success are related, but to what extent? If genes affect success, then what role does effort play? Arian Akbari has answered these questions by designing a formula and equation called genetic success formula. by inserting a series of data in this formula, you can predict the approximate outcome of the future. But what is the basis of this formula? Every trait in humans has a part called genetic contribution called heritability. In short, the heritability of any particular trait determines the extent of the role of genetics in that trait. This means that the higher the heritability of a trait, the more meaningless your efforts will be! Yes,now you might wonder whether effort affects success? then what happens to "You can achieve anything with hard work" We ask Arian Akbari: would you say this saying is not true? the Answer is, it definitely isn’t, these are just motivational sentences which can actually ruin the lives of many. If you are not prone to a trait that is highly heritable, the effort will do nothing for you. Question : So where does effort work? Your effort only affects areas and traits that are less heritable. Scientists know that genes affect success, and I’m quite sure everyone knows that it's better for you to enter a field where you have a talent gene. So what new meaning does this formula convey? There is a point here! Your talent becomes more effective when a trait’s heritability is high which makes the role of effort less significant. someone with less talent can not reach you in that field even with more effort, but if you are prone to a trait with low heritability other people can easily eliminate the effect of your talent with more practice. Let me give you an example Suppose Jack has 50% susceptibility genes/predisposing genes in a specific trait we are going to call A, (such as singing), and in trait B (mathematics, for example), he has 30% susceptibility genes/predisposing genes. In which field do you think he has the best chance of success? You might say singing. but no. This is the distinguishing point of this formula. According to this formula, with the same amount of effort in both fields, Jack will be more successful in B because it has less heritability and the amount of effort can change the course of things. Let's take a look at the components of this formula. COE=EU *ER ýCOS = COE + (APG*h2 ) ýDOS=CS +[ (COS - RFE /t/year) ]*RFE*100 ýCOE= Coefficient of effort ýEF=effort unit ýER=environment role ýCOC= Coefficient of change ýAPG= amount of predisposing gene ýh2=heritablity ýDOS=Degree of success ýCS= Current situation ýRFE= Remaining to the world fullest extent What is the COE? Coefficient of effort. Includes EU (effort unit) multiplied by the ER (environment role). The coefficient of change equals the coefficient of effort plus the multiplication of the susceptibility genes/predisposing genes by heritability(h2). We should also remember the extent of the role of heritability and environment role have an inverse relationship. APG is the amount of a person's susceptibility genes/predisposing genes that can be determined through DNA sequencing analysis or depending on the field in question through special tests. h2 is the heritability of any trait, the number is rapidly becoming more and more precise through QTL mapping. The more precise the number the more accurate the formula. These numbers are the result of QTL studies and tools and methods such as GWA (genome wide association) analysis that examine different variants of genes affecting traits. In this formula DOS is the degree of success which equals one’s current situation plus the coefficient of the result of subtraction of the coefficient of change from the ultimate possibility of success in that field, per year. Let me give you an example Suppose a particular trait, such as singing, has an 90% heritability (these numbers are approximate). In this case, the environment role is 10%. A person possesses 90% singing genes and does not have much practice and his current situation is 0.8 the output of this formula for him is 0.96 It’d be difficult for an ordinary person who possesses 50% of the genes to compete with this person. he reaches 0.7 with the same amount of effort. You might suggest he can reach that person with more effort. Let's set the EU number to the highest possible number, which is 1 to see what happens. Yes, you can see that even if he tries with all his might, it still wouldn’t change much and he will not succeed. so the effort alone is not important. Also, your efforts and genes are not enough either, in addition to that, the heritability of each trait must be considered separately. Therefore you can not do whatever you want with effort! Another example If the heritability of a trait is low, say 20%. then, person A with 90% susceptibility genes/predisposing genes without much training will have the score of 0.6 And an ordinary person who has 50% susceptibility genes/predisposing genes can compensate with more practice! Was that interesting? This is a logical relationship, and this formula has the potential to evolve in the future, this balance can provide a logical relationship between genetics and success. Arian Akbari is an iranian geneticist who started teaching genetics as a free course since he was 19 years old. Now at 37 he has been teaching genetics at undergraduate, graduate and doctoral levels for 18 years. He says he came up with the idea of this formula while he was teaching genetics. He hopes he can have the opportunity to expand this formula. in the near future, people will be able to have a more lucid image of their future and they will realize how their efforts can be a factor in success. The time of millions and billions of people would no longer be wasted and people would be able to choose the right path for themselves. so far, This has been a simple and comprehensible explanation of this formula.
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