Dear Plamen, Pedro and Collegues,
I am enjoying a lot this forum.
I absolutely foresee Scientific Blockchain as a continuously growing
list of scientific records and contributions (blocks) linked and secured
using cryptography, somehow a kind of peer reviewed process. Would you
be able to publish it in a journal based on their scientific value?
Dataist-machines won chess players but still are learning Science, they
are completing their "Bachelor". Their use for biomedical applications
is growing everyday. For example, their accuracy for in biomedical
imaging diagnosis will be similar to humans soon. For other
applications, such as genetic predisposition and health
prediction/prognosis the conversion to a fanatic dataism may abuse of
"predictivity" and forget the relevance of the organism-environment. It
will take some time for machines to complete their "Philosophical
Doctorate". Technology could be ready soon for data driven hypothesis
but our knowledge of fundamental aspects of life are still weak.
All the best,
AJ
El 10-03-2018 21:05, PEDRO CLEMENTE MARIJUAN FERNANDEZ escribió:
> 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.
>
> best--Pedro
>
> 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.
>
> Plamen
>
> ____________________________________________________________
>
> On Thu, Mar 8, 2018 at 6:15 PM, PEDRO CLEMENTE MARIJUAN FERNANDEZ <
> pcmarijuan.i...@aragon.es [1]> wrote:
>
> head>
>
> Dear Alberto,
>
> Many thanks for the kickoff text. I will try to produce a couple of direct
> comments.
>
> You have reminded me of the early 70's, when I first approached science. A
> few computers had made their entrance in the university halls. During those
> years, and for some decades to come, a new mantra was to be ensconced:
> modeling, simulations. Thanks to computers, we had a fascinating new tool; a
> mathematical machine that was opening a new window to the world of science,
> equivalent to the telescope or the microscope in the scientific revolution.
> Now, almost 50 years later, after having provoked their own "information
> revolution" it seems that computers are more than a new tool. Dataism coupled
> with artificial intelligence, deep learning and the other techniques, have
> taken them to the command post, so that they are becoming direct "agents" of
> the scientific progress. And this is strange. They have already defeated
> masters of chess, of go and of other contests... are they going to defeat
> scientists too? Are they the "necessary" new lords of all quarters of
> techno-social complexity?
>
> You have depicted very cogently the new panorama of biomedical research,
> probably the mainstream, and I wonder whether this is the most interesting
> direction of advancement. In some sense, yes (or no!), as it is where big
> biomed companies, technological firms, and management establishment are
> pointing at. It is easy to complain that they are leaving aside the
> integrative vision, the meaningful synthesis that facilitate our
> comprehension, the "soul" in the machine... But we have been complaining in
> this way at least during the last two decades. So I really do not know.
> Fashions in science come and go: maybe all of this is a temporary illusion.
> Or a taste of the science of the future.
>
> In any case, it was nice hearing from a biomedical researcher in the wet lab.
>
> Best wishes--Pedro
>
> On Tue, 06 Mar 2018 21:23:01 +0100 "Alberto J. Schuhmacher" wrote:
> blockquote>
>
> 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 Biology.
>
> 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 _Dataism_?
>
> Best regards,
>
> AJ p>
>
> ---
>
> 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) br> email: ajime...@iisaragon.es
> [2]
> Phone: (+34) 637939901 [3]
>
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