A combined statistical model for multiple motifs search

Transcription factor binding sites (TFBS) play key roles in genebior 6.8 wavelet expression and regulation. They are short sequence segments with de¯nite structure and can be recognized by the corresponding transcription factors correctly. From the viewpoint of statistics, the candidates of TFBS should be quite di®erent from the segments that are randomly combined together by nucleotide. This paper proposes a combined statistical model for ¯nding over- represented short sequence segments in di®erent kinds of data set. While the over-represented short sequence segment is described by position weight matrix, the nucleotide distribution at most sites of the segment should be far from the background nucleotide distribution. The central idea of this approach is to search for such kind of signals. This algorithm is tested on 3 data sets, including binding sites data set of cyclic AMP receptor protein in E.coli, PlantProm DB which is a non-redundant collection of proximal promoter sequences from di®erent species, collection of the intergenic sequences of the whole genome of E.Coli. Even though the complexity of these three data sets is quite di®erent, the results show that this model is rather general and sensible.

A new flow field and its two-dimension model for polymer electrolyte membrane fuel cells (PEMFCs)

A new flow field was designed to search flow fields fitting polymer electrolyte membrane fuel cells (PEMFCs) better due its extensible. There are many independent inlets and outlets in the new flow field. The new flow field we named NINO can extend to be more general when pressures at the inlet and outlet vary and some usual flow fields will be obtained. A new mathematical model whose view angle is obverse is used to describe the flow field.