Normal Mode Analysis (NMA) is forecast for a macro-molecule possible movement powerful tool,and can display the present known above half protein movement, analyzing and using most two kind of low frequency normal vibration pattern. Normal Mode Analysis can be used in a variety of application including structure biology with broad domain, for example protein structure change research, membrane channel's opening and closure, ribosome latent movement, and outside viral granule nuclear maturation. Here we use a network “EIN' emo” the web to provide fast and the simple tool for computation, and an analysis of macro-molecule of low frequency Normal Mode. Frequency and in the collectivity movement data for the member from 50 kinds of patterns αC b-factor can be obtained. The data for this research including (Bovine Spongiform Encephalopathy,BSE) obtain from the mad cow disease and from all Alpha and all Beta proteins in SCOP databases, and then uploads EIN' emo to analyze 50 kinds of low frequency patterns, and has a set of comprehensive description parameter. we obtains the collective degree movement and the B-factor correlation data, and analyze their structure difference using the two-dimensional coordinates
