A New Method for Database Searching and Clustering
スポンサーリンク
概要
- 論文の詳細を見る
An iterative database searching method is introduced and applied to the design of a database clustering procedure. The search method virtually never produces false positive hits while determining meaningfully large sets of sequences related to the query. A novel set-theoretic database clustering algorithm exploits this feature and avoids a traditional, distance-based clustering step. This makes it fast and applicable to data-sets of the size of, e. g., the Swiss-Prot database. In practice we achieve unambiguous assignment of 80% of Swiss-Prot sequences to non-overlapping sequence clusters in an entirely automatic fashion.
- 日本バイオインフォマティクス学会の論文
日本バイオインフォマティクス学会 | 論文
- Performance Improvement in Protein N-Myristoyl Classification by BONSAI with Insignificant Indexing Symbol
- A combined pathway to simulate CDK-dependent phosphorylation and ARF-dependent stabilization for p53 transcriptional activity
- A versatile petri net based architecture for modeling and simulation of complex biological processes
- XML documentation of biopathways and their simulations in Genomic Object Net
- Prediction of debacle points for robustness of biological pathways by using recurrent neural networks