Machine Learning Techniques for Protein Secondary Structure Prediction:An Overview and Evaluation

By P. Yoo, Bing Bing Zhou, Albert Y. Zomaya. 2008

37 citations recorded by the source corpus.

Subfields: Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Xin Gao
2. George K. Karagiannidis
3. Han Zhang
4. Panagiotis D. Diamantoulakis
5. Bin Liu
6. V. M. Kapinas

Citations in the corpus

• Big Data Analytics for Dynamic Energy Management in Smart Grids (2015, methodology): “In addition, the proposed scheme should be utilizing the model averaging technique [80] in order to improve the stability and accuracy of ML algorithms via reducing variance [56,81,82].”
• BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches (2019, background): “Residue composition One-hot Basic one-hot (17) Position-specific-2 Position-specific of two nucleotides (18)”