Assessment of CASP10 contact‐assisted predictions

By Todd J. Taylor, Hongjun Bai, Chin-Hsien Tai, Byungkook Lee. 2014

23 citations recorded by the source corpus.

Subfields: 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 Materials Chemistry

1. David T. Jones
2. Daniel W. A. Buchan
3. Alexander Rives
4. Tom Sercu
5. Roshan Rao
6. Adam Belsom
7. Joshua Meier
8. Oliver Brock

In Molecular Biology

1. David T. Jones
2. Sergey Ovchinnikov
3. Daniel W. A. Buchan
4. Alexander Rives
5. Tom Sercu
6. Joshua Meier
7. Roshan Rao
8. Adam Belsom

Citations in the corpus

• Transformer protein language models are unsupervised structure learners (2020, background): “| − | In general, all contacts provide information about protein structure and important interactions, with shorter-range contacts being useful for secondary and local structure, while longer range contacts are useful for determining global structure (Taylor et al., 2014).”
• Blind testing of cross‐linking/mass spectrometry hybrid methods in CASP11 (2016, background): “16 However, the provided contact sets had idealized properties.”
• De novo Protein Structure Prediction by Coupling Contact With Distance Profile (2020, background): “More and more researchers are working on improving accuracy of PSP by using contact information [17], [18], [19], [20].”
• Improved protein contact predictions with the MetaPSICOV2 server in CASP12 (2017, methodology): “This was a marked improvement from the prior CASP10 where the best precision remained around 20% (Taylor et al. 2014).”