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Protein structure prediction is one of the most important subjects in computational structural biology. In the process of protein structure prediction, many structure decoys are obtained. It has remained an unsolved and challenging problem to select the best model from the structure decoys that are closest to the native structure. One of the important methods for selecting the near-native structure...
Cryo-electron microscopy is a fast emerging biophysical technique for structural determination of large protein complexes. While more atomic structures are being determined using this technique, it is still challenging to derive atomic structures from density maps produced at medium resolution when no suitable templates are available. A critical step in structure determination is how a protein chain...
The detection of secondary structure of proteins using three dimensional (3D) cryo-electron microscopy (cryo-EM) images is still a challenging task when the spatial resolution of cryo-EM images is at medium level (5–10Å). Prior researches focused on the usage of local features that may not capture the global information of image objects. In this study, we propose to use deep learning methods to extract...
Data is becoming the world's new natural resource and big data use grows quickly. The trend of computing technology is that everything is merged into the Internet and 'big data' are integrated to comprise complete information for collective intelligence. With the increasing size of big data, refining big data themselves to reduce data size while keeping critical data (or useful information) is a new...
This paper presents an approximation algorithm for word-replacement under a bi-gram language model. Words replacement is an key step in the decoding part of statistical machine translation. However, the word or phrase replacement step is often done at the same time with the target language generating process in machine translation while our algorithm focus on the special replacement model without...
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