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Clustering sequences with a statistical content evaluation method.
| Content Provider | CiteSeerX |
|---|---|
| Author | Bogan-Marta, Alina Robu, Nicolae |
| Abstract | Abstract: The clustering of biological sequences into biologically meaningful classes denotes two computationally complex challenges: the choice of a biologically pertinent and computable criterion to evaluate the clusters homogenity, and the optimal exploration of the solution space. Here we are analysing the clustering potential of a new method of sequence similarity based on statistical sequence content evaluation. Its computational efficiency and high accuracy of the results is encouraging for further development that could make it an appealing alternative to the existent methods. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Statistical Content Evaluation Method Solution Space Complex Challenge Computable Criterion Computational Efficiency Optimal Exploration Sequence Similarity Existent Method Cluster Homogenity Statistical Sequence Content Evaluation Meaningful Class High Accuracy New Method Biological Sequence |
| Content Type | Text |
