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  1. Accurate contact predictions using covariation techniques and machine learning.
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    Journal: Proteins. 2016 Sep;84 Suppl 1(Suppl Suppl 1)
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  2. MoFvAb: Modeling the Fv region of antibodies.
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    Journal: MAbs. 2015;7(5)
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  3. A Multi-Objective Approach for Protein Structure Prediction Based on an Energy Model and Backbone Angle Preferences.
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    Journal: Int J Mol Sci. 2015 Jul 03;16(7)
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  4. Protein structure refinement by optimization.
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    Journal: Proteins. 2015 Sep;83(9)
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  5. DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach.
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    Journal: PLoS One. 2015;10(6)
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  6. Identify five kinds of simple super-secondary structures with quadratic discriminant algorithm based on the chemical shifts.
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    Journal: J Theor Biol. 2015 Sep 07;380
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  7. Customised fragments libraries for protein structure prediction based on structural class annotations.
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    Journal: BMC Bioinformatics. 2015 Apr 29;16(1)
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  8. Building a better fragment library for de novo protein structure prediction.
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    Journal: PLoS One. 2015;10(4)
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  9. Conformational sampling and structure prediction of multiple interacting loops in soluble and β-barrel membrane proteins using multi-loop distance-guided chain-growth Monte Carlo method.
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    Journal: Bioinformatics. 2015 Aug 15;31(16)
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  10. AIDA: ab initio domain assembly for automated multi-domain protein structure prediction and domain-domain interaction prediction.
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    Journal: Bioinformatics. 2015 Jul 01;31(13)
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