Summary of Position Specific Scoring Is All You Need? Revisiting Protein Sequence Classification Tasks, by Sarwan Ali et al.
Position Specific Scoring Is All You Need? Revisiting Protein Sequence Classification Tasks
by Sarwan Ali, Taslim Murad, Prakash Chourasia, Haris Mansoor, Imdad Ullah Khan, Pin-Yu Chen, Murray Patterson
First submitted to arxiv on: 16 Oct 2024
Categories
- Main: Machine Learning (cs.LG)
- 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 The paper proposes a novel kernel function, called weighted PSS kernel matrix (W-PSSKM), which combines position-specific scoring (PSS) representation of protein sequences with the string kernel. The W-PSSKM outperforms existing approaches for protein sequence classification, achieving up to 45.1% improvement in accuracy. The authors demonstrate the effectiveness of their method through extensive experimentation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about using a new way to look at proteins and how they are made up of amino acids. This can help us understand more about proteins and develop ways to make new medicines or policies. Scientists have been trying different methods to do this, but it’s not clear which one works best. The researchers propose a new method called W-PSSKM that combines two other techniques to get better results. They test their method with lots of data and show that it does much better than the old ways. |
Keywords
* Artificial intelligence * Classification
