Question: (Closed) Is proper feature selection possible before all imperatively hidden objects required for conceptualizing aging adequately are fully discovered?
gravatar for tfhahn
3.1 years ago by
tfhahn50 wrote:

Is proper feature selection for machine learning training data even possible before all imperatively hidden objects, factors, dimensions and parameters required for conceptualizing aging adequately are fully discovered? About imperatively hidden objects and the need for new concept discoveries to select all necessary features required to fully understanding aging, immigration and other phenomena.

Humans are very bias in choosing their method of conducting experimental measurements or make observations without being aware of it. What percentage of the entire electromagnetic wave spectrum can we perceive? No more than 5% for sure. But the changes, of which we must be aware, before we can understand aging, are most likely much more distinct outside our narrow sensory window because our sensory limitations did not affect the evolution of aging in any way. For example, humans can only hear part of the sound an elephant makes because humans cannot hear such low frequencies as the elephant can.

This tends to prevent the full understanding of the elephant’s communication options. Humans cannot distinguish such low sound frequencies from background noise, i.e. environment, because they cannot perceive the low elephant sound frequencies from being different from the background environment. But without considering those imperatively hidden factors we cannot fully understand elephant communication. Therefore, humans tend to miss cellular processes, which can only be distinguished from background noise outside the electromagnetic wavelength interval, for which humans have evolved sensory organs, i.e. eyes, ears and skin. The mechanism by which the tongue and nose operate is of an entirely different dimension because they cannot sense any wavelength.

For example, before magnets were discovered, they remained for us an imperatively hidden object because we could not even suspect them in any way. But still, just because we lack any senses for perceiving any kind of magnetism does not stop it from affecting our lives. Only after we discovered the consequences of the forces, which the magnetic field has on some metals, prompted us to search outside the limited window, within which we can sense differences in waive length. Magnetic fields could affect life in many positive ways because they are used to treat major depressive disorder and cause involuntary muscle contraction. But has anybody even thought of measuring the magnetic field of a cell or brain, which I expect to be strong enough for us to measure with sensitive devices? Since any electric current causes a perpendicular radiating magnetic field, it can be hypothesized that the weak magnetic field is pulse-like and depends on the temporal pattern by which neurons fire action potentials. The changes in the magnetic field of a cell is expected to be enriched for the cellular component membrane because they have proton pumps and maintain an electric gradient to produce ATP. But what if changes in this magnetic field are causing us to age? Then we could stop the aging process by any intervention, which sets our cellular magnetic field pattern back to its youthful benchmark.

I suspect that the reason for our only rudimentary understanding of the aging process is caused by us missing such kind of imperatively hidden objects, which are required for making the essential key observations without which aging cannot be fully explained. I view a magnetic field as a concept, which exists regardless weather we are aware of it. There may be many more other hidden concepts, which we must develop, before we can reverse aging. I use an analogy to explain this concept, which came to me in a dream, and which does not appear to concern anybody, except for me.

Let’s say that an immortal interstellar alien highly intelligent out-of-space critter has landed on Earth. Lets imagine that he can only perceive waive lengths within the limits of the magnetic field. Then we humans would not even notice this out of space interstellar visitor because he/she remains an imperatively hidden object that we cannot even suspect. Let’s say this interstellar species has not evolved a body or anything to which our senses are sensitive. Let’s say that this life can be fully defined by irregularities within the magnetic field. But this interstellar critter can perceive us humans because our magnetic field disrupt the homogeneity of the background environment and must therefore be something other than background noise. Let’s say that this immortal interstellar critter can perceive and process all the magnetic fields on Earth. Could he maybe develop the concept of siblings or parents on its own? Is the magnetic field of relatives more similar to each other than expected by chance? It is very likely because humans vary a lot in their neuronal wiring architecture. Hence, each human could be defined by the pattern of his/her action potentials. This inevitably causes a very weak unique perpendicularly acting electromagnetic field that cannot be detected by our instruments. Therefore, instead of humans, we should use the giant squid as model organism to understand the relationships between life, aging and changes in magnetic field because it has the thickest neuron. Therefore, it must fire stronger action potentials than our human neurons. This will inevitably cause a stronger perpendicularly acting electromagnetic field, which may be strong enough to be detected by our instruments.

Lets say that this interstellar critter wants to use machine learning to predict the risk of any particular university student in the USA for having to return home after graduation because they lost their immigration status and could not find a job, which would have made them eligible for one year OPT (Optional Practical Training). Lets say that this interstellar critter has no concept of aging and that his most important goal is to develop a classifier by developing a new machine learning algorithm, which can predict in advance the risk that any particular student is facing to no longer been allowed to reside in the United States. Let’s say that accomplishing this objective has the same meaning and importance to this critter as for us the cure from aging.

What should he do? He cannot talk. No human even suspects him. He could start using supervised machine learning by observing thousands of students to find out what those students share, who are forced to leave, or what they lack compared to citizens, who are always welcome here.

I hypothesize that no matter how clever and sensitive to irregular interruption of the homogenous electromagnetic field, which is the only dimension in which he can sense the presence of humans and any other form of life, he has no chance to understand the risk factors for being forced to leave because they are an imperatively hidden concept to the critter, which he cannot even suspect in any way. But without developing the right concepts in advance, this critter can never the discover risk factors for having to leave the USA after graduation. The same applies to aging. We are still missing essential concepts without which we cannot fully understand it. But even if somebody by chance could detect the magnetic irregularities caused by this foreign interstellar critter, he/she could never suspect that it is highly intelligent. This means that even if we measured a cell across the entire wavelength spectrum and could clearly detect its presence we would never suspect it to have any kind of intelligence because we would consider the anomalies in the magnetic field as background noise. Our visiting interstellar critter has a similar problem. He cannot develop the essential concepts without which he could never develop a machine learning algorithm to predict all the correct risk factors, which impair the chances for somebody to be allowed to keep residing in the US while not full time enrolled. As long as this critter has no concept of “country”, e.g. the USA, he has absolutely no chance to discover nationalities because even if he could figure out the nationality of everyone, it would make no sense to him. But words like “American” “German”, “French” or “Indian” cannot make any sense to this critter as long as the concept of “country” remains an imperatively hidden object for him. How can somebody be considered “German” or “American” as long as the concept of Germany or USA are still lacking? One can only be German if Germany exists. Without at least suspecting the concept of a country, e.g. Germany, there is absolutely no way to discover the required concept of citizenship. But without determining the feature “citizenship” no machine learning algorithm could learn to make correct predictions. .

The same applies to aging. We are still lacking so many essential concepts without which aging can never be understood For example, as long as the concept of a ribosome is lacking we have no way of understanding the changes in the relative abundance ratio of mRNA and proteins. We may have some initially success with building a model to predict protein abundance and concentration because it is about 70% similar of the transcriptome. But no matter how many training samples we use to train our predictor, it must fail, unless we have developed a mental concept of a ribosome. I believe we face a similar predicament with understanding the causes and regulation of epigenetic changes over time with advancing age, despite being able to measuring them so clearly that we can use them to determine the biological age. But unfortunately, as long as we lack any concept, by which epigenetic changes could be connected to other cellular processes, we cannot understand how epigenetic changes are regulated.

Before we could correctly conceptualize the role and scope of the ribosome we had no way to explain the mechanism by which mRNA and protein abundance are linked. But even after we conceptualized the role of the ribosome correctly any machine learning algorithm to predict protein concentration would inevitably fail as long as we lack the correct concept of the poly-AAA-tail. Similarly, there are still lots of imperatively hidden concepts, factors, dimensions or objects, which we cannot suspect because we cannot perceive them, which prevent us from fully understanding aging. However, the fact that our current observations fail to fully explain aging, indicate the presence of imperatively hidden factors of which we can see the consequences without being able to detect them. But since every consequence must have a cause, any unexplained consequence indicates the presence of imperatively hidden inperceptable factors without which we cannot succeed to improve our feature selection.

As I tried to explain in my immigration example, only when selecting the correct feature, e.g. citizenship, the risk for being asked to leave by the federal government can be predicted. Could I convince anybody of the high likelihood of the presence of imperatively hidden factors, which we cannot perceive yet as being distinctly different from their environment? The current bottleneck to defeat aging is not to focus on improving our machine learning algorithms and increase the training samples, but instead, we must focus on proper feature selection. My main contribution towards defeating aging is to predict features, measurement types and intervals between measurements, which could show the actions of aging much clearer than the features, we have currently selected, to stop aging and defeat death. That is why I keep dreaming about all my crazy hypotheses, which come to me while sleeping, showering, eating or biking. While still working on my master’s thesis I had similar dreams but I pushed them away and ignored them because I had no data to support the concepts I kept dreaming about. Then I found an article last spring break supporting one of my very intensively hypothesis according to which there is a life cycle, which splits homogenous long intervals by inhomogeneous short intervals similar to the cell cycle implying that cyclical (i.e. cell cycle) and linear biological clocks (i.e. lifespan) must have evolved from a single mother clock in the very distant past and diverged a lot ever since. I came up with all my crazy aging hypothesis, which could theoretically be true, in my dreams of being an aged dying yeast cell, which is desperately trying to test any intervention to save its life. Now it is up to wet-lab scientists to test my hypotheses. But even if all of them can be ruled out, the possibilities, by which the mechanism of aging could function, would be reduced. This would leave us with fewer hypotheses left to test. Since the options we have for fully understanding the aging process are large but yet finite, any crazy hypothesis, which can be ruled out, brings us a tiny step closer to immortality.

The reason why I claim that correct feature selection, but not the machine learning algorithms, are the current bottleneck to progress in our understanding of the aging process is that our machine learning algorithms have improve over time but our feature selection has not.

The fact that I cannot find any data for measuring the transcriptome in five-minute intervals for more than 3 out of the average 25 replications, which is considered the average WT yeast replicative lifespan, indicates that nobody has seriously suspected that we could at least observe the effects of the aging mechanism by selecting new periodic features, such as period length or amplitude, which only make sense if we replace our linear with a periodic concept of life. However, this requires us to change our concepts about life to be driven by linearly acting trends to cyclical periodically acting trends in order to expand our feature selection options to periodic quantities, such as period length, amplitude or oscillation pattern, which would have been impossible to imagine when holding on to the old linear concept. In this case – although we could clearly measure the period length - we could not detect it as a feature affected by aging until we explicitly define, select and measure this new feature, e.g. the period length.

Please let me know if this writing makes sense to you because so for nobody, except for me, seems to worry about this problem.

ADD COMMENTlink modified 3.0 years ago by Michael Dondrup48k • written 3.1 years ago by tfhahn50

Wait! I know this person - please don't close the thread. S/He is in my Skype list and I had been helping him/her with various things related to bioinformatics. There is a disability related to vision in question here.

I would appreciate that the thread remained open, just out of courtesy.

ADD REPLYlink modified 3.1 years ago • written 3.1 years ago by Kevin Blighe69k

Hello tfhahn!

We believe that this post does not fit the main topic of this site.

"Could I convince anybody of the high likelihood of the presence of imperatively hidden factors, which we cannot perceive yet as being distinctly different from their environment?" You are making a hypothesis that cannot be rejected because of imperatively hidden factors. Claiming ("god-like"?) factors that are in principle inaccessible to measurement is against the scientific method. Therefore you cannot base any scientific hypothesis on them, as it could never be rejected. Even less so for a specific bioinformatics related question.

As bioinformaticians we are good in analysing data that are available and building hypotheses and models based on the available data. We cannot conclude anything in a valid way from data that are unavailable, or faulty. No measurement device or model can capture or represent all potential magnitudes and effects. If you wish to propose a hypothesis it should be evident how it could be eventually rejected or validated, and ideally an experiment should be described to do exactly this.

For this reason we have closed your question. This allows us to keep the site focused on the topics that the community can help with.

If you disagree please tell us why in a reply below, we'll be happy to talk about it.


ADD REPLYlink modified 3.0 years ago • written 3.0 years ago by Michael Dondrup48k

I have described a method by which such kind of Imperatively Hidden Objects/Factors (IHO/F) can be uncovered. In the past, it was often by accident, but I have described a kind of formal procedure how to better deal with the problems caused by anything we don't know yet. However, it is 33 pages long and does not fit here. But before I could start thinking about a solution I first had to understand the problem. Therefore, both, problem and solution description together take up 33 pages. Now I am looking for editors, who can rephrase it in such a way that people can understand it so it can be presented at conferences and published in peer-reviewed journals. I am not an expert in machine learning. I have discovered this by accident while I was trying to understand the reasons for not making much progress in discovering how to reverse aging and escape death. Here is the link to my 33-page long description. Is this link accessible?

ADD REPLYlink written 3.0 years ago by tfhahn50

I now wrote an abstract for this post telling why and when it could be useful. It had the highest votes from all my postings. Here it is for your understanding and decision.


Thomas Hahn


Incomplete feature selection causes reproducible prediction errors. Such prediction errors are the consequences of still Imperatively Hidden Objects (IHO). They are called IHO because – even though they cannot be directly observed or measured – they affect the predicted outcome. Such IHOs are often the hidden causes. Their consequences are exposed by reproducible prediction errors.

IHOs are challenging because their exact impact on the observation of interest cannot be fully considered until they have been fully uncovered. But, since feature selection must be completed before any supervised ML algorithm can be properly trained, such kind of IHOs must be discovered before feature selection can be fully completed.


To distinguish IHOs from one another and from background noise, the measuring methods and their surrounding experimental environment must be varied. Independent features can be considered as singlets, e.g. the impact of transcription, length of poly-(A)-tails and ribosomal coverage on protein abundance, because they don’t depend on one another. However, codons must be considered as atomic triplets only.

When the prediction can be made by different methods in different dimensions feature selection can be considered as fully completed, e.g. when transcription can be fully predicted either by considering the trajectories of time series plots or Transcription Factor Binding Site (TFBS) distributions, Transcription Factor (TF) ratios and TF abundance.

New features can be discovered by creating external experimental conditions, which cause any until then correctly ML prediction algorithm to fail, because it indicates another still unknown dimension by which IHO differ from one another and their background noise environment. Strategies for uncovering IHOs are discussed.


Focusing on IHO discovery can speed up our scientific progress because each newly uncovered IHO should be added to the selected features for training new ML algorithms because IHOs prevents better understanding of complex phenomena, such as aging.

ADD REPLYlink written 2.9 years ago by tfhahn50

can I close 'this' ?

ADD REPLYlink modified 3.1 years ago • written 3.1 years ago by Pierre Lindenbaum133k

No - I remember previous threads of OP. It's not spam, but someone who needs more help than an online Q&A forum can offer.

ADD REPLYlink written 3.1 years ago by WouterDeCoster45k

You're correct. See my other comment

ADD REPLYlink written 3.1 years ago by Kevin Blighe69k

What other comment? I am still struggling with navigating this website interface properly and find all the replies, answers and comments to my last fundamental question. I emailed you back. Please try to contact me by voice. That is much easier for me than having to read. Check your Skype messages. I replied. Sorry it took me more than a day to find your Skype message. Thanks a lot for taking your time to understand ...

ADD REPLYlink written 3.1 years ago by tfhahn50

Hi friend, I will call you later today on Skype. Kevin

ADD REPLYlink written 3.1 years ago by Kevin Blighe69k

What does "OP" stands for?

ADD REPLYlink written 3.1 years ago by tfhahn50

OP = "Original poster", essentially the one who opened the thread and a convenient gender-neutral name.

ADD REPLYlink written 3.1 years ago by WouterDeCoster45k

If the OP don't rephrase the question then yes

ADD REPLYlink written 3.1 years ago by Nicolas Rosewick9.3k

I've read it and it's primarily about shortcomings in current study designs and alludes to factors about which we are neither aware nor can measure. The person takes a focus on electromagnetic waves and how these permeate the Universe and may influence biology in certain ways, again ways that we are not to understand (yet).

Finally the person focuses on aging and how, for example, in order to better understand aging from a transcriptomic perspective, we'd have to take many snapshots of life in the cell (yeast is mentioned) in order to gauge any idea of cellular mechanisms related to aging.

I'll leave it to the admins to decide whether this should be closed.

ADD REPLYlink modified 3.1 years ago • written 3.1 years ago by Kevin Blighe69k

I have read this, nothing of this text has relevance for bioinformatics, it is full of speculation, inadequate comparisons, and unscientific lingo. OP needs to write a question that fits the format of this site and adheres to our posting standards. Minimum: a single question related to bioinformatics that can be answered. This requirement is mandatory, irrespective of OP as a person or any factors such as impairment of any sort. There is no way to adequately handle esoteric discussions on this page.

ADD REPLYlink modified 3.0 years ago • written 3.0 years ago by Michael Dondrup48k

Am I the "OP"? Is my question still open or did it get closed?

I have many more of such kinds of questions written out in MS-Word consisting of at least 2 and up to more than 100 pages. May I post them here too? Is there a character-limit per question? Was posting this question a good or a bad idea?

Many of my much longer, more comprehensive, but also much harder to understand questions, which I'd like to share, can only make sense to anyone, who considers this question as important enough to think about. Since at least one other person indicated to me on Skype that he understands, what I am trying to tell, and why I think this issue is very important, I am ready to post the next group of questions, which are build on this most fundamental one.

In some of my own answers to this fundamental question I proposed partial remedies to the problems and challenges, which I have described in my original posting. However, as long as I am the only one, who considers this a big enough problem to be seriously addressed, any of my proposed solutions to it will remain inherently imperatively hidden objects as long as any mutually shared and agreed upon concept about the nature of challenges, which they help to overcome, is still lacking.

I am almost blind and hence; my reading efficiency is that of a 2nd-grade elementary school student, i.e. it is only 1/10th of what is considered to be normal. Therefore, I can only finish my degree, if I can create conditions, in which the answers I need are coming to my questions on their own, i.e. delivered by my readers, instead of me trying in vain to search for them visually online. That is why I have invested so much time and effort in writing such long complex questions, which unfortunately face a much higher risk for getting closed, before anyone had the time and chance to really understand them, than could be expected by random chance alone. My sincere hope is that well-written questions will attract high-quality answers by those, who take the time to read them carefully to understand them well.

Currently, it is still generally expected that everyone must take lots of efforts to search and find the answers to his/her questions on his/her own. But since this option is not available to me, I must find new ways to write my questions in such a manner that they attract their answers to be actively brought to them by other readers, who they got interested.

Almost all people try to find the right answers to their questions based on their own search efforts. But since that does not work for me, I try to write my questions in a manner that they can be actively sought out/found by their answers by getting others interested in bringing the right answers to my questions rather than me trying in vain to take my questions and bring them to their right answers.

Most people tend to believe that each question must find its answer. But I am limited to reverse this commonly accepted approach by trying to rephrase my questions in a manner that allows them to be actively sought out/found by their answers automatically without requiring my efforts. Therefore, instead of me trying in vain to actively take a question and move it to/seek out/match it with its answer, I must experiment with new methods, which allow the right answer to actively move to/seek out/get matched with my question automatically without requiring me to invest my efforts into any - for me visually way too demanding - procedures of actively matching my questions with their answers.

In a nutshell, I must strive to ask questions, which can be actively sought out by their answers, instead of me having to actively seek out the answers to my questions. I apologize that this approach tends to result in much longer and partially repetitive questions. However, according to my experiences, longer and partially repetitive questions, which consist of many analogies, have much better chances to be actively sought out/found by the kind of answers I am looking for as long as interested readers can find them. The partial repetitiveness and information redundancies of my questions seems to be overall beneficial because before any reader can bring the right answers to my question, it must invoke the right shared concept in the minds of my readers.

My readers are vehicles, which my questions must program, to bring the right answers back to me. The more efforts I spend in programming my readers, the higher their chances for being able to bring back the kinds of answers I am looking for. It’s like a novel biological form of fuzzy subconsciously controlled humanoid-based analogy-driven new type of machine learning capable of independently discovering very novel and unexpectedly surprising innovative concepts.

ADD REPLYlink written 3.1 years ago by tfhahn50

Hi friend, I will call you later today on Skype. Kevin

ADD REPLYlink written 3.1 years ago by Kevin Blighe69k

Did you try to call me? I have not seen a call from you. I would love to blog if you could tell me where. Thanks and until soon. Thomas

ADD REPLYlink written 3.1 years ago by tfhahn50

I'm not sure if Biostars is the best platform for this, have you considered blogging?

ADD REPLYlink written 3.1 years ago by WouterDeCoster45k

Do you have a better recommendation for such kinds of conceptual questions should be posted, i.e. where there are better chances for finding people, who are interested in understanding them? If so, please provide URL. Thanks OP

ADD REPLYlink written 3.1 years ago by tfhahn50
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