References

[1] Quadir, F., Roy, R., Halfmann, R., & Cheng, J. (2021). DNCON2_Inter: Predicting interchain contacts for homodimeric and homomultimeric protein complexes using multiple sequence alignments of monomers and deep learning. Scientific Reports, (accepted). (https://doi.org/10.21203/rs.3.rs-228041/v1)

[2] Hou, J., Wu, T., Guo, Z., Quadir, F. & Cheng, J. The MULTICOM Protein Structure Prediction Server Empowered by Deep Learning and Contact Distance Prediction. in Methods in Molecular Biology vol. 2165 13–26 (Humana Press Inc., 2020)

[3] Soltanikazemi, E., Quadir, F., Roy, R. S. & Cheng, J. Distance-based Reconstruction of Protein Quaternary Structures from Inter-Chain Contacts. bioRxiv 2021.05.24.445503 (2021) doi:10.1101/2021.05.24.445503

[4] Quadir, F., Roy Raj, Soltanikazemi, E. & Cheng, J. DeepComplex. https://github.com/jianlin-cheng/DeepComplex

[5] Hou, J., Wu, T., Cao, R., & Cheng, J. (2019). Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13. Proteins, accepted. (https://doi.org/10.1002/prot.25697)

[6] Li, J., Deng, X., Eickholt, J., & Cheng, J. (2013). Designing and benchmarking the MULTICOM protein structure prediction system. BMC structural biology, 13(1), 2.

[7] Cheng, J., Li, J., Wang, Z., Eickholt, J., & Deng, X. (2012). The MULTICOM toolbox for protein structure prediction. BMC bioinformatics, 13(1), 65.

[8] Wang, Z., Eickholt, J., & Cheng, J. (2010). MULTICOM: a multi-level combination approach to protein structure prediction and its assessments in CASP8. Bioinformatics, 26(7), 882-888.