Artificially patterned biological systems

Since the SECM response is a function of the rate of the heterogeneous reaction at the substrate, it can be used to image the local chemical and electrochemical reactivity of surface features. A technique called reaction-rate imaging, which is unique to SECM, is particularly useful in imaging the areas on a surface where reactions occur. Membranes (5-7), leaves (8-10), polymers (11,12), surface films (13-17), and artificially patterned biological systems (7,18-20) have been imaged with SECM. 

This complex process of dissipative structure-assisted self-assembly plays an important role for pattern formation in biological systems and many other artificial systems. So far as the authors know, this concept was firstly proposed by Lefever in 2000 (12), We may extend his idea to think of an alternative concept a self-assembly-assisted dissipative structure. It is obvious that most biological dissipative structures such as traveling waves along giant axons and... 

Artificial neural networks A machine or program for supervised or unsupervised learning based on a layered network of neurons. Normally, a network is trained to best describe a biological or chemical system, in order to classify new systems. Used for pattern recognition in cheminformatics, QSAR, and bioinformatics. 

Several types of artificial neural networks have been used as pattern recognition engines. In general, neural networks are mathematical models that emulate some of the observed properties of biological nervous systems, in particular the ability to learn complex relationships. Examples of drug-like molecules were taken from the WDI, CMC or MDDR databases, while compounds from the ACD database exemplified nondrugs. Molecules were represented by a large number of descriptors, such as ISIS... 

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