Dear Alberto,

Let imagine that we are at the naturist beach, i.e. naked.
You will see all what I am and I will se the same for you.

Well, will you know what I think or shall I know the same for you?

Simple answer: NOT!

No Data base may contain any data about my current thoughts and feelings.
Yes, the stupid part of humanity may be controlled by big data centers.
But all times it had been controlled. Nothing new.

The pseudo scientists may analyze data and may create tons of papers.
For such “production” there was and will exist corresponded more and more big 
I had edited more than one thousand papers.
Only several was really very important and with great scientific value !!!

Collection of data is important problem and it will be such for ever.
But the greater problem for humanity is collection of money 

And the last cause the former!
And the last is many times more dangerous than former!

Do not worry of Data-ism!
Be worried of the Money-ism!

I will continue next week because this is my second post  ( Thanks to wisdom of 
Pedro who had limited Writing-letter-ism in our list! ).

Friendly greetings

From: Alberto J. Schuhmacher 
Sent: Tuesday, March 06, 2018 10:23 PM
To: fis 
Subject: [Fis] Is Dataism the end of classical hypothesis-driven research and 
the beginning of data-correlation-driven research?

Dear FIS Colleagues,

I very much appreciate this opportunity to discuss with all of you.

My mentors and science teachers taught me that Science had a method, rules and 
procedures that should be followed and pursued rigorously and with 
perseverance. The scientific research needed to be preceded by one or several 
hypotheses that should be subjected to validation or refutation through 
experiments designed and carried out in a laboratory. The Oxford Dictionaries 
Online defines the scientific method as "a method or procedure that has 
characterized natural science since the 17th century, consisting in systematic 
observation, measurement, and experiment, and the formulation, testing, and 
modification of hypotheses". Experiments are a procedure designed to test 
hypotheses. Experiments are an important tool of the scientific method.

In our case, molecular, personalized and precision medicine aims to anticipate 
the future development of diseases in a specific individual through molecular 
markers registered in the genome, variome, metagenome, metabolome or in any of 
the multiple "omes" that make up the present "omics" language of current 

The possibilities of applying these methodologies to the prevention and 
treatment of diseases have increased exponentially with the rise of a new 
religion, Dataism, whose foundations are inspired by scientific agnosticism, a 
way of thinking that seems classical but applied to research, it hides a 
profound revolution.

Dataism arises from the recent human desire to collect and analyze data, data 
and more data, data of everything and data for everything-from the most banal 
social issues to those that decide the rhythms of life and death. “Information 
flow” is one the “supreme values” of this religion. The next floods will be of 
data as we can see just looking at any electronic window.

The recent development of gigantic clinical and biological databases, and the 
concomitant progress of the computational capacity to handle and analyze these 
growing tides of information represent the best substrate for the progress of 
Dataism, which in turn has managed to provide a solid content material to an 
always-evanescent scientific agnosticism.

On many occasions the establishment of correlative observations seems to be 
sufficient to infer about the relevance of a certain factor in the development 
of some human pathologies. It seems that we are heading towards a path in which 
research, instead of being driven by hypotheses confirmed experimentally, in 
the near future experimental hypotheses themselves will arise from the 
observation of data of previously performed experiments. Are we facing the end 
of the wet lab? Is Dataism the end of classical hypothesis-driven research (and 
the beginning of data-correlation-driven research)?

Deep learning is based on learning data representations, as opposed to 
task-specific algorithms. Learning can be supervised, semi-supervised or 
unsupervised. Deep learning models are loosely related to information 
processing and communication patterns in a biological nervous system, such as 
neural coding that attempts to define a relationship between various stimuli 
and associated neuronal responses in the brain. Deep learning architectures 
such as deep neural networks, deep belief networks and recurrent neural 
networks have been applied to fields including computer vision, audio 
recognition, speech recognition, machine translation, natural language 
processing, social network filtering, bioinformatics and drug design, where 
they have produced results comparable to and in some cases superior to human 
experts. Will be data-correlation-driven research the new scientific method for 
unsupervised deep learning machines? Will computers became fundamentalists of 

Best regards,



Alberto J. Schuhmacher, PhD.
Head, Molecular Oncology Group

Aragon Health Research Institute (IIS Aragón)
Biomedical Research Center of Aragon (CIBA)
Avda. Juan Bosco 13, 50009 Zaragoza (Spain)
Phone:(+34) 637939901

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