Name: Jianlin Cheng
Type: User
Company: University of Missouri - Columbia
Bio: I am a Curators' Distinguished Professor and Thompson Professor in the Department of Electrical Engineering and Computer Science at University of Missouri.
Location: Columbia, MO 65211, USA
Blog: http://calla.rnet.missouri.edu/cheng/
Jianlin Cheng's Projects
An Unsupervised Learning Approach for Fully Automated Single Particle Picking in Cryo-EM Images
This repository contains the frequently asked questions, their answers and the description of resources in the Bioinformatics and Machine Learning Lab (BML).
A central web portal to manage CASP13 predictions of all MULTICOM predictors
Collaborative Attentive-Autoencoder for scientific article recommendation
Deep learning tools for converting cryo-EM density maps to protein structures
A dataset for training and testing machine learning methods for denoising cryo-EM density maps
The program of mapping protein sequences into protein Ca trace derived from cryoEM image data
Customized foundational image segmentation models for picking protein particles in cryo-EM images
CryoTEN: Efficiently Enhancing Cryo-EM Density Maps Using Transformers
A transformer model for picking protein particles in cryo-EM images
Deep learning prediction of inter-chain contacts of protein complex
Deep learning prediction of protein complex structures from sequences
Deep learning methods for CryoEM data analysis
The software package to align cryo-EM particles to create 3D density maps of proteins
Deep learning methods to predict protein backbone trace from cryoEM images
Deep learning for predicting the properties of graphene
Deep learning for modeling gene regulatory network
A deep learning bioinformatics pipeline for protein-ligand complex structure prediction
The deep learning method for ranking protein structural models
Deep learning prediction of the quality of protein structural models with inter-residue distance maps
The distance-based protein folding
Deep learning prediction of protein domains from distance maps
Prediction of the quality of single protein model using deep learning and residue-residue distance maps
Predicting inter-protein contacts using DNCON2
Designing and benchmarking deep learning architectures for protein contact prediction
The DNCON4 system for training deep learning for protein contact prediction and making predictions
Deep dilated convolutional residual neural network for predicting interchain contacts of protein homodimers
Deep learning method for predicting interchain contacts in heterodimers
Deep reinforcement learning for protein complex modeling