Yuan Yan Chen

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Hsp70s (heat shock protein 70s) are a class of molecular chaperones that are highly conserved and ubiquitous in organisms ranging from microorganisms to plants and humans. Most research on Hsp70s has focused on the mechanisms of their functions as molecular chaperones, but recently, studies on stress responses are coming to the forefront. Hsp70s play key(More)
This paper applies a recently developed neural network called plausible neural network (PNN) to function approximation. Instead of using error correction, PNN estimates the mutual information of neurons between input layer and hidden layer. The simple theory and training algorithm of PNN lead to a faster converging rate over that of feedforward neural(More)
Many researchers have observed that neurons process information in an imprecise manner - if a logical inference emerges from neural computation, it is inexact at best. Thus, there must be a profound relationship between belief logic and neural networks. In Chen (2002), a plausible neural network model that can compute probabilistic and possibilistic logic(More)
Most literature that attempts to explain the neural network computation and the uncertainty of inference based on the probability measure; e.g. see [2], [10], [11], [12] and [13]. This paper discusses a new neural network model, that uses a statistical inference model proposed in [5] and [6]; under such a model the interpretation of neural networking is(More)
Currently, novel antibiotics are urgently required to combat the emergence of drug-resistant bacteria. Antimicrobial peptides with membrane-lytic mechanism of action have attracted considerable interest. Anoplin, a natural α-helical amphiphilic antimicrobial peptide, is an ideal research template because of its short sequence. In this study, we designed and(More)
Biological sequence usually contains yet to find knowledge, and mining biological sequences usually involves a huge dataset and long computation time. Common tasks for biological sequence mining are pattern discovery, classification and clustering. The newly developed model, plausible neural network (PNN), provides an intuitive and unified architecture for(More)
Fuzzy Analysis of Statistical Evidence (FASE) is utilizing the fuzzy set and the statistical theory for solving problems of pattern recognition and/or classification. Several features of FASE are similar to the human judgment. It can evaluate the weight of statistical evidence (information); it can update inference with new information; and it can(More)
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