Summary of A Three-stage Algorithm For the Closest String Problem on Artificial and Real Gene Sequences, by Alireza Abdi et al.
A Three-Stage Algorithm for the Closest String Problem on Artificial and Real Gene Sequences
by Alireza Abdi, Marko Djukanovic, Hesam Tahmasebi Boldaji, Hadis Salehi, Aleksandar Kartelj
First submitted to arxiv on: 17 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel three-stage algorithm is proposed for solving the Closest String Problem (CSP), an NP-hard problem aiming to find a string with minimum distance from all sequences in a given set. The CSP has applications in coding theory, computational biology, and designing degenerated primers. Efficient exact algorithms have been developed for binary sequences, but there is still room for improvement over DNA and protein sequences. The proposed algorithm consists of alphabet pruning, beam search with an expected distance heuristic score guiding function, and local search to improve solution quality. Experimental results show the proposed method outperforms previous approaches on real-world datasets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way is found to solve a tricky problem called the Closest String Problem. This problem helps us find the best string that’s farthest from all other strings in a group. It’s useful for things like coding and biology research. Right now, we can do this easily with simple strings, but it gets harder when we try to work with DNA or protein sequences. The new method uses three steps: first, we get rid of some search options to make it easier; next, we find a good starting point using a special guide; and finally, we fine-tune the answer to make it even better. We tested this method on real-world data and found that it works better than other methods people have tried. |
Keywords
» Artificial intelligence » Pruning
