Progress in protein structure prediction.

By David C. Jones. 1997

How researchers see this paper

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

1. Jinbo Xu
2. Sheng Wang
3. Yang Zhang
4. Hongyi Zhou
5. Jianzhu Ma
6. Jianwei Zhu
7. Björn Wallner
8. Liam J. McGuffin

Citations in the corpus

• Protein threading using residue co-variation and deep learning (2018, background): “…and correct template recognition, both of which are challenging when only distantly-related templates are available for a protein sequence under prediction (Cozzetto and Tramontano, 2004; Hou, et al., 2018; Jo, et al., 2015; Jones, 1997; Peng and Xu, 2011a; Peng and Xu, 2011b; Zhu, et al., 2017).”
• Enhanced genome annotation using structural profiles in the program 3D-PSSM. (2000, background): “In addition to such sequence-based approaches to fold recognition, many groups have developed techniques that incorporate structural information at a variety of levels (for a general review, see Jones, 1997).”
• Artificial neural networks for computer-based molecular design. (1998, methodology): “Most of the current tertiary structure prediction methods are based on very successful sequence alignment methods (Jones, 1997).”
• TOUCHSTONE II: a new approach to ab initio protein structure prediction. (2003, unknown): “There are three classes of theoretical approaches to the problem in the recent literature (Murzin, 2001): homology modeling (Guex and Peitsch, 1997; Sanchez and Sali, 1997); threading (Bowie et al., 1991; Panchenko et al., 2000; Skolnick and Kihara, 2001); and ab initio folding (Pillardy et al.,…”
• Ab initio protein structure prediction using chunk-TASSER. (2007, methodology): “Protein structure prediction methods can be classified into three categories (4): comparative modeling, fold recognition, and ab initio methods.”