Yaoqi Zhou
Affiliations: | State University of New York, Buffalo, Buffalo, NY, United States |
Area:
General Biophysics, Bioinformatics BiologyGoogle:
"Yaoqi Zhou"Mean distance: (not calculated yet)
Children
Sign in to add trainee| Qianqian Zhu | grad student | SUNY Buffalo (FlyTree) | |
| Beisi Xu | grad student | 2007-2008 | Indiana University - Purdue University in Indianapolis Medical School (Neurotree) |
| Yuedong Yang | post-doc | 2006-2012 | Indiana University (Chemistry Tree) |
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Publications
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| Song Y, Yuan Q, Chen S, et al. (2023) Fast and accurate protein intrinsic disorder prediction by using a pretrained language model. Briefings in Bioinformatics |
| Zhou B, Ding M, Feng J, et al. (2022) EVlncRNA-Dpred: improved prediction of experimentally validated lncRNAs by deep learning. Briefings in Bioinformatics |
| Singh J, Paliwal K, Litfin T, et al. (2022) Predicting RNA distance-based contact maps by integrated deep learning on physics-inferred secondary structure and evolutionary-derived mutational coupling. Bioinformatics (Oxford, England) |
| Singh J, Paliwal K, Litfin T, et al. (2022) Reaching alignment-profile-based accuracy in predicting protein secondary and tertiary structural properties without alignment. Scientific Reports. 12: 7607 |
| Singh J, Litfin T, Singh J, et al. (2022) SPOT-Contact-LM: Improving Single-Sequence-Based Prediction of Protein Contact Map using a Transformer Language Model. Bioinformatics (Oxford, England) |
| Yuan Q, Chen J, Zhao H, et al. (2021) Structure-aware protein-protein interaction site prediction using deep graph convolutional network. Bioinformatics (Oxford, England) |
| Singh J, Litfin T, Paliwal K, et al. (2021) SPOT-1D-Single: Improving the Single-Sequence-Based Prediction of Protein Secondary Structure, Backbone Angles, Solvent Accessibility and Half-Sphere Exposures using a Large Training Set and Ensembled Deep Learning. Bioinformatics (Oxford, England) |
| Zhou B, Ji B, Liu K, et al. (2020) EVLncRNAs 2.0: an updated database of manually curated functional long non-coding RNAs validated by low-throughput experiments. Nucleic Acids Research |
| Zhao B, Katuwawala A, Oldfield CJ, et al. (2020) DescribePROT: database of amino acid-level protein structure and function predictions. Nucleic Acids Research |
| Hanumanthappa AK, Singh J, Paliwal K, et al. (2020) Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network. Bioinformatics (Oxford, England) |