ArticleTheScientificWorldJournal2014
acACS: improving the prediction accuracy of protein subcellular locations and protein classification by incorporating the average chemical shifts composition.
Article in TheScientificWorldJournal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Improving Protein Subcellular Location Classification by Incorporating Three-Dimensional Structure Information.Biomolecules · 2021Article
- Predicting Gram-Positive Bacterial Protein Subcellular Location by Using Combined Features.BioMed research international · 2020Article
- Predicting Cell Wall Lytic Enzymes Using Combined Features.Frontiers in bioengineering and biotechnology · 2020Article
- Identifying anticancer peptides by using improved hybrid compositions.Scientific reports · 2016Article
- Identifying the subfamilies of voltage-gated potassium channels using feature selection technique.International journal of molecular sciences · 2014Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The chemical shift is sensitive to changes in the local environments and can report the structural changes. The structure information of a protein can be represented by the average chemical shifts (ACS) composition, which has been broadly applied for enhancing the prediction accuracy in protein subcellular locations and protein classification. However, different kinds of ACS composition can solve different problems. We established an online web server named acACS, which can convert secondary structure into average chemical shift and then compose the vector for representing a protein by using the algorithm of auto covariance. Our solution is easy to use and can meet the needs of users.
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