Evaluating the absolute quality of a single protein model using structural features and support vector machines

By Zheng Wang, Allison N. Tegge, Jianlin Cheng. 2009

103 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, 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 Computational Theory and Mathematics

1. Jianlin Cheng
2. Badri Adhikari
3. Renzhi Cao
4. Debswapna Bhattacharya
5. Yang Zhang
6. Jie Hou

In Materials Chemistry

1. Jianlin Cheng
2. Renzhi Cao
3. Debswapna Bhattacharya
4. Badri Adhikari
5. Jilong Li
6. Jinbo Xu
7. Jie Hou
8. Mohammed Alquraishi

In Molecular Biology

1. Jianlin Cheng
2. Badri Adhikari
3. Renzhi Cao
4. Debswapna Bhattacharya
5. Jilong Li
6. Jinbo Xu
7. Jie Hou
8. Sheng Wang

Citations in the corpus

• Large-scale model quality assessment for improving protein tertiary structure prediction (2015, methodology): “The multi-model QA methods include ModFOLDclust2 (McGuffin and Roche, 2010); Pcons (Wallner and Elofsson, 2006); APPOLLO (Wang et al. , 2011); QApro— a weighted combination of ModelEvaluator and APOLLO (Cao et al. , 2014a).”