Biological computation electronic computers

In the same spirit, the concept of complexity has been taken under consideration for the investigation of electron density functions. Complexity has appeared in many fields of scientific inquiry e.g., physics, statistics, biology, computer science and... 

A state-of-the-art electronic computer can easily do 100 million (10 ) instructions per second. Since molecular computers work with chemical reactions, they can perform only a fractional computational step per second. However, this drawback is completely outweighed by the massive parallelism of biological computers. It is the product of the number of parallel operations and the time for one computational step that determines the duration of a computation. Since the number of parallel operations is proportional to the number of molecules in a test tube, which is of the order of 10 , molecular computers are superior in speed to electronic computers by several orders of magnitude (10 vs. 10 ) [6]. 

All three tasks are generally too complicated to be solved from first principles. They are, therefore, tackled by making use of prior information, and of information that has been condensed into knowledge. The amount of information that has to be processed is often quite large. At present, more than 41 million different compounds are known all have a series of properties, physical, chemical, or biological all can be made in many different ways, by a wide range of reactions all can be characterized by a host of spectra. This immense amount of information can be processed only by electronic means, by the power of the computer. 

Empirical energy functions can fulfill the demands required by computational studies of biochemical and biophysical systems. The mathematical equations in empirical energy functions include relatively simple terms to describe the physical interactions that dictate the structure and dynamic properties of biological molecules. In addition, empirical force fields use atomistic models, in which atoms are the smallest particles in the system rather than the electrons and nuclei used in quantum mechanics. These two simplifications allow for the computational speed required to perform the required number of energy calculations on biomolecules in their environments to be attained, and, more important, via the use of properly optimized parameters in the mathematical models the required chemical accuracy can be achieved. The use of empirical energy functions was initially applied to small organic molecules, where it was referred to as molecular mechanics [4], and more recently to biological systems [2,3]. 

Reactions on the surface are interesting. The adsorptions of unsaturated organic molecules on the surface provide a means for fabricating well-ordered monolayer films. Thin film organic layers can be used for diverse applications such as chemical and biological sensors, computer displays, and molecular electronics. 

The interaction of dihalogens, particularly diiodine, with sulfur and selenium electron donors has been an area of increasing interest over the past decade because of potential biological, pharmaceutical, and electronic materials applications [35,179]. Devillanova and coworkers have recently reviewed the solution behavior of a large number of chalcogenides and I2, particularly thiones, selones, sulfides, and selenides [180]. Correlations between computational methods, thermodynamic parameters, and spectroscopic data (UV/Vis, 13C NMR, Raman, UPS) were discussed. 

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