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As the development of high-throughput techniques in both biology and its related disciplines (chemistry or medicine), the huge number of biological entries are available. The discovered relationship between them (e.g. interactions or associations) reveals important biological facts, which are never found in individual-based biological experiments. A biological network is an appropriate tool to systematically...
Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there...
Symptoms and signs (symptoms in brief) are the essential clinical manifestations for traditional Chinese medicine (TCM) diagnosis and treatments. To gain insights into the molecular mechanism of symptoms, this paper presents a network-based data mining method to integrate multiple phenotype-genotype data sources and predict the prioritizing gene rank list of symptoms. The result of this pilot study...
In the post-genome era, as an essential filternative of experimental method, the computational method is becoming popular. The prediction of protein structural class from protein sequence becomes one of research's concerns because the knowledge of protein structural class can simplify and accelerate in the computational determination of the spatial structure of a newly identified protein. As one of...
In order to extract compact and effective feature to characterize protein structure, this paper presents a feature extraction of protein fold by mapping into 2-D distance matrix which is regarded as gray level image and further analyzed by image processing techniques. Firstly, gray level co-occurrence matrix (CoM) of distance matrix image (DMI) is calculated and its singular values are taken as the...
One of the most important research aims is to understand the relationship between structure and function of protein. Inspired by this motivation, automatic classification of protein structure becomes one of major research approaches. However, how to extract compact and effective feature to characterize protein structure is still a challenge to it. In this paper, 3-D tertiary structure of protein fold...
Despite the success of tyrosine kinase-based cancer therapeutics, for most solid tumors the tyrosine kinases that drive disease remain unknown, limiting our ability to identify drug targets and predict response. Here we present the first large-scale survey of tyrosine kinase activity in lung cancer. Using a phosphoproteomic approach, we characterize tyrosine kinase signaling across 41 non-small cell...
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