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BMC Bioinformatics
|
December 16, 2011
MSACompro: protein multiple sequence alignment using predicted secondary structure, solvent accessibility, and residue-residue contacts
Xin Deng, Jianlin Cheng
BMC Bioinformatics
|
March 19, 2013
DNdisorder: predicting protein disorder using boosting and deep networks
Jesse Eickholt, Jianlin Cheng
Scientific Reports
|
May 11, 2016
A Stochastic Point Cloud Sampling Method for Multi-Template Protein Comparative Modeling
Jilong Li, Jianlin Cheng
Biomolecules
|
January 21, 2023
Improving Protein-Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge
Nabin Giri, Jianlin Cheng
Bioinformatics (Oxford, England)
|
October 11, 2012
Predicting protein residue-residue contacts using deep networks and boosting
Jesse Eickholt, Jianlin Cheng
International Journal of Molecular Sciences
|
September 28, 2021
Four-Dimensional Chromosome Structure Prediction
Max Highsmith, Jianlin Cheng
Arxiv
|
February 17, 2023
Geometry-Complete Diffusion for 3D Molecule Generation and Optimization
Alex Morehead, Jianlin Cheng
BMC Bioinformatics
|
October 24, 2015
A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11
Jilong Li, Renzhi Cao, Jianlin Cheng
Communications Biology
|
November 17, 2025
Boosting AlphaFold protein tertiary structure prediction through MSA engineering and extensive model sampling and ranking in CASP16
Jian Liu, Pawan Neupane, Jianlin Cheng
Bioinformatics (Oxford, England)
|
July 27, 2023
Single-cell Hi-C data enhancement with deep residual and generative adversarial networks
Yanli Wang, Zhiye Guo, Jianlin Cheng
Page
of 30
Search research articles
Search
Showing results (41-50 of 298) with videos related to
Sort By:
Page
of 30
BMC Bioinformatics
|
December 16, 2011
MSACompro: protein multiple sequence alignment using predicted secondary structure, solvent accessibility, and residue-residue contacts
Xin Deng, Jianlin Cheng
BMC Bioinformatics
|
March 19, 2013
DNdisorder: predicting protein disorder using boosting and deep networks
Jesse Eickholt, Jianlin Cheng
Scientific Reports
|
May 11, 2016
A Stochastic Point Cloud Sampling Method for Multi-Template Protein Comparative Modeling
Jilong Li, Jianlin Cheng
Biomolecules
|
January 21, 2023
Improving Protein-Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge
Nabin Giri, Jianlin Cheng
Bioinformatics (Oxford, England)
|
October 11, 2012
Predicting protein residue-residue contacts using deep networks and boosting
Jesse Eickholt, Jianlin Cheng
International Journal of Molecular Sciences
|
September 28, 2021
Four-Dimensional Chromosome Structure Prediction
Max Highsmith, Jianlin Cheng
Arxiv
|
February 17, 2023
Geometry-Complete Diffusion for 3D Molecule Generation and Optimization
Alex Morehead, Jianlin Cheng
BMC Bioinformatics
|
October 24, 2015
A large-scale conformation sampling and evaluation server for protein tertiary structure prediction and its assessment in CASP11
Jilong Li, Renzhi Cao, Jianlin Cheng
Communications Biology
|
November 17, 2025
Boosting AlphaFold protein tertiary structure prediction through MSA engineering and extensive model sampling and ranking in CASP16
Jian Liu, Pawan Neupane, Jianlin Cheng
Bioinformatics (Oxford, England)
|
July 27, 2023
Single-cell Hi-C data enhancement with deep residual and generative adversarial networks
Yanli Wang, Zhiye Guo, Jianlin Cheng
Page
of 30