ArticleProteins2019
Prediction of interresidue contacts with DeepMetaPSICOV in CASP13.
Article in Proteins, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
62 citing papers in PubMed.
- Unique molecular architecture of N-glycosylated TM4SF5 dimer highlights evolutionary and structural divergence among small four-transmembrane protein families.Journal of advanced research · 2026Article
- Transcriptomic profiling and structural characterization reveal UQCRC1 and COX4I1 as key mitochondrial regulators associated with oxidative stress in multiple sclerosis.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Protein Structure Prediction Methods.Advances in experimental medicine and biology · 2026Review
- CASP16 Protein Monomer Structure Prediction Assessment.Proteins · 2026Article
- AT-TSVM: Improving Transmembrane Protein Inter-Helical Residue Contact Prediction Using Active Transfer Transductive Support Vector Machines.International journal of molecular sciences · 2025Article
- Protein structure prediction via deep learning: an in-depth review.Frontiers in pharmacology · 2025Review
- Deep learning for the PSIPRED Protein Analysis Workbench.Nucleic acids research · 2024Article
- A large-scale assessment of sequence database search tools for homology-based protein function prediction.Briefings in bioinformatics · 2024Article
- Improving AlphaFold Predicted Contacts for Alpha-Helical Transmembrane Proteins Using Structural Features.International journal of molecular sciences · 2024Article
- Recent Advances in Protein Folding Pathway Prediction through Computational Methods.Current medicinal chemistry · 2024Review
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- A large-scale assessment of sequence database search tools for homology-based protein function prediction.bioRxiv : the preprint server for biology · 2023Article
- Improving AlphaFold predicted contacts in alpha-helical transmembrane proteins structures using structural features.Research square · 2023Article
- DeepChIA-PET: Accurately predicting ChIA-PET from Hi-C and ChIP-seq with deep dilated networks.PLoS computational biology · 2023Article
- Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15.bioRxiv : the preprint server for biology · 2023Article
- Contact-Assisted Threading in Low-Homology Protein Modeling.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Improved Protein Real-Valued Distance Prediction Using Deep Residual Dense Network (DRDN).The protein journal · 2022Article
- Benchmarking AlphaFold for protein complex modeling reveals accuracy determinants.Protein science : a publication of the Protein Society · 2022Article
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2 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
In this article, we describe our efforts in contact prediction in the CASP13 experiment. We employed a new deep learning-based contact prediction tool, DeepMetaPSICOV (or DMP for short), together with new methods and data sources for alignment generation. DMP evolved from MetaPSICOV and DeepCov and combines the input feature sets used by these methods as input to a deep, fully convolutional residual neural network. We also improved our method for multiple sequence alignment generation and included metagenomic sequences in the search. We discuss successes and failures of our approach and identify areas where further improvements may be possible. DMP is freely available at: https://github.com/psipred/DeepMetaPSICOV.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.