Experience with complex systems more primitive than the brain teaches important lessons about big data in biology. Chief among them is that physical laws, relationships among measured things that are always true, emerge out of chaos, not the other way around. Correct prediction (as opposed to incorrect prediction) from large data sets requires understanding of these laws. The reason is that the same processes that make them also make the system wildly error-intolerant if the errors are too large. This instability routinely causes computer simulations of even primitive systems to fail by enabling mistakes to cascade into ever worsening falsehoods. The more complex and sophisticated the system is, the more intolerant to errors it becomes
Scientific theories seek to provide simple explanations for significant empirical regularities based...
The brain is arguably the most complex system known to man. Under the eyes of a physicist, brains sh...
In this NeuroView, Engert discusses the challenges for the connectomics field in making insights abo...
Experience with complex systems more primitive than the brain teaches important lessons about big da...
Complexity is an indisputable, well-known, and broadly accepted feature of the brain. Despite the ap...
Despite the widely-spread consensus on the brain complexity, sprouts of the single neuron revolution...
The current interest in big data, machine learning and data analytics has generated the widespread i...
Human beings' approach to the real world is about incompleteness: incompleteness of understanding, r...
It is commonly believed that our brains serve as information processing systems. Therefore, common m...
Computation a b s t r a c t Scientific theories seek to provide simple explanations for significant ...
Complexity science is the study of systems that give rise to a priori unexpected macroscopic patter...
Abstract: Why are there several sciences instead of only one? Are higher “levels of organization” r...
Regarding the widespread confusion about the concept and nature of complexity, information and biolo...
Healthy functioning is an emergent property of the network of interacting biomolecules that comprise...
Background: how mind functions is subject to continuing scientific discussion. A simplistic approach...
Scientific theories seek to provide simple explanations for significant empirical regularities based...
The brain is arguably the most complex system known to man. Under the eyes of a physicist, brains sh...
In this NeuroView, Engert discusses the challenges for the connectomics field in making insights abo...
Experience with complex systems more primitive than the brain teaches important lessons about big da...
Complexity is an indisputable, well-known, and broadly accepted feature of the brain. Despite the ap...
Despite the widely-spread consensus on the brain complexity, sprouts of the single neuron revolution...
The current interest in big data, machine learning and data analytics has generated the widespread i...
Human beings' approach to the real world is about incompleteness: incompleteness of understanding, r...
It is commonly believed that our brains serve as information processing systems. Therefore, common m...
Computation a b s t r a c t Scientific theories seek to provide simple explanations for significant ...
Complexity science is the study of systems that give rise to a priori unexpected macroscopic patter...
Abstract: Why are there several sciences instead of only one? Are higher “levels of organization” r...
Regarding the widespread confusion about the concept and nature of complexity, information and biolo...
Healthy functioning is an emergent property of the network of interacting biomolecules that comprise...
Background: how mind functions is subject to continuing scientific discussion. A simplistic approach...
Scientific theories seek to provide simple explanations for significant empirical regularities based...
The brain is arguably the most complex system known to man. Under the eyes of a physicist, brains sh...
In this NeuroView, Engert discusses the challenges for the connectomics field in making insights abo...