Dear Plamen and Colleagues,
If it can be feasible, I would very much welcome what you propose. Yes, it would be great developing a general articulation amongst all our exchanges. Roughly, I feel that a fundamental nucleous of neatly conceptualized information is still evading us, but outside that nucleous, and somehow emanating from it, there are different branches and sub-branches in quite different elaboration degrees and massively crisscrossing and intermingling their contents. A six-pointed star, for instance, radiating from its inner fusion the computational, physical, biological, neuronal, social, and economic. The six big branches in perfect periferic colussion and confusion. Could a blockchain, along its full develpment in time, represent a fundamental cartography of the originating fusion nucleous? About dataism enchantment, well, too many times we have been said "look, finally this is the great, definitive scientific approach"--behaviorism, artificial intelleigence, artifficial catastrophe & complexity theory, and so on. Let us wait and see. Welcome in the extent to which it really responds to unanswered questions. And let us be aware of the technocratic lore it seems to drag.
This was my second cent for the week.

On Fri, 9 Mar 2018 10:30:01 +0100 "Dr. Plamen L. Simeonov"  wrote:
These are wise words, Pedro.
What I was meaning with my previous posting on FIS was that there is a 
foundational emerging technology - blockchain - that could give us, scientists 
organized in fora like FIS, IB, IS4IS etc. to become a valuable currency of the 
future. I am speaking not about finances or resources like petrol, gold, water, 
etc. What we are doing all the time with the exchange of ideas online are in 
fact transactions, often with huge potential. Why do not

try to elevate them to the level that they deserve? 

I am not sure if the FIS forum members can follow me. Can you?

All the best.



<> wrote:

head>Dear Alberto,

Many thanks for the kickoff text. I will try to produce acouple of direct 
You have reminded me of the early70's, when I first approached science. A few 
computers had made theirentrance in the university halls. During those years, 
and for somedecades to come, a new mantra was to be ensconced: 
modeling,simulations. Thanks to computers, we had a fascinating new tool; 
amathematical machine that was opening a new window to the world ofscience, 
equivalent to the telescope or the microscope in thescientific revolution. Now, 
almost 50 years
later, after havingprovoked their own "information revolution" it seems that computersare more than a new tool. Dataism coupled with artificialintelligence, deep learning and the other techniques, have taken themto the command post, so that they are becoming direct "agents" of thescientific progress. And this is strange. They have already defeatedmasters of chess, of go and of other contests... are they going todefeat scientists too? Are they the "necessary" new lords of allquarters of techno-social complexity?
You have depicted verycogently the new panorama of biomedical research, 
probably themainstream, and I wonder whether this is the most 
interestingdirection of advancement. In some sense, yes (or no!), as it is 
wherebig biomed companies, technological firms, and managementestablishment are 
pointing at. It is easy to complain that they areleaving aside the integrative 
vision, the
meaningful synthesis thatfacilitate our comprehension, the "soul" in the machine... But we havebeen complaining in this way at least during the last two decades. SoI really do not know. Fashions in science come and go: maybe all ofthis is a temporary illusion. Or a taste of the science of the future.
In any case, it was nice hearing from a biomedical researcher inthe wet lab.
Best wishes--Pedro

On Tue, 06Mar 2018 21:23:01 +0100 "Alberto J. Schuhmacher"  wrote:
blockquote>Dear FIS Colleagues,
I very much appreciate thisopportunity to discuss with all of you.
My mentors and scienceteachers taught me that Science had a method, rules and 
proceduresthat should be followed and pursued rigorously and with 
perseverance.The scientific research needed to be preceded by one or 
severalhypotheses that should be subjected to validation or refutationthrough 
experiments designed and
carried out in a laboratory. TheOxford Dictionaries Online defines the scientific method as "a methodor procedure that has characterized natural science since the 17thcentury, consisting in systematic observation, measurement, andexperiment, and the formulation, testing, and modification ofhypotheses". Experiments are a procedure designed to test hypotheses.Experiments are an important tool of the scientific method.
Inour case, molecular, personalized and precision medicine aims toanticipate the future development 
of diseases in a specific individualthrough molecular markers registered in the genome, 
variome,metagenome, metabolome or in any of the multiple "omes" that make upthe present 
"omics" language of current Biology.
Thepossibilities of applying these methodologies to the prevention andtreatment 
of diseases have increased exponentially with the rise of anew religion, 
whose foundations are inspired byscientific agnosticism, a way of thinking that seems classical butapplied to research, it hides a profound revolution.
Dataismarises from the recent human desire to collect and analyze data, dataand 
more data, data of everything and data for everything-from themost banal social 
issues to those that decide the rhythms of life anddeath. “Information flow” is 
one the “supreme values” of thisreligion. The next floods will be of data as we 
can see just lookingat any electronic window.
The recent development of giganticclinical and biological databases, and the 
concomitant progress of thecomputational capacity to handle and analyze these 
growing tides ofinformation represent the best substrate for the progress of 
Dataism,which in turn has managed to provide a solid content material to 
analways-evanescent scientific agnosticism.
On many occasions
theestablishment of correlative observations seems to be sufficient toinfer about the relevance of a certain factor in the development ofsome human pathologies. It seems that we are heading towards a path inwhich research, instead of being driven by hypotheses confirmedexperimentally, in the near future experimental hypotheses themselveswill arise from the observation of data of previously performedexperiments. Are we facing the end of the wet lab? Is Dataism the endof classical hypothesis-driven research (and the beginning ofdata-correlation-driven research)?
Deep learning is based onlearning data representations, as opposed to 
task-specific algorithms.Learning can be supervised, semi-supervised or 
unsupervised. Deeplearning models are loosely related to information processing 
andcommunication patterns in a biological nervous system, such as neuralcoding 
that attempts to define a
relationship between various stimuliand associated neuronal responses in the brain. Deep learningarchitectures such as deep neural networks, deep belief networks andrecurrent neural networks have been applied to fields includingcomputer vision, audio recognition, speech recognition, machinetranslation, natural language processing, social network filtering,bioinformatics and drug design, where they have produced resultscomparable to and in some cases superior to human experts. Will bedata-correlation-driven research the new scientific method forunsupervised deep learning machines? Will computers becamefundamentalists of Dataism?
Best regards,
p> ---
Alberto J. Schuhmacher,PhD.
Head, MolecularOncology Group

AragonHealth Research Institute (IIS Aragón)
Biomedical Research Center of Aragon (CIBA)
Avda. Juan Bosco 13, 50009 Zaragoza (Spain)br> email: <>
Phone:(+34) 637939901 <unknown://tel:+34%20637%2093%2099%2001>

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