ArticleBioinformatics (Oxford, England)2012
A conditional neural fields model for protein threading.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
45 citing papers in PubMed.
- Protein Structure Prediction Methods.Advances in experimental medicine and biology · 2026Review
- Natural L-Hexapeptides with Therapeutic Potential for Alzheimer's Disease and Tauopathies.ACS omega · 2025Article
- Artificial intelligence in fusion protein three-dimensional structure prediction: Review and perspective.Clinical and translational medicine · 2024Review
- An interactive visualization tool for educational outreach in protein contact map overlap analysis.Frontiers in bioinformatics · 2024Article
- Protein Structure Prediction: Challenges, Advances, and the Shift of Research Paradigms.Genomics, proteomics & bioinformatics · 2023Review
- Functional assessment of AtPAP17; encoding a purple acid phosphatase involved in phosphate metabolism in Arabidopsis thaliana.Biotechnology letters · 2023Article
- Contact-Assisted Threading in Low-Homology Protein Modeling.Methods in molecular biology (Clifton, N.J.) · 2023Article
- CRFalign: A Sequence-Structure Alignment of Proteins Based on a Combination of HMM-HMM Comparison and Conditional Random Fields.Molecules (Basel, Switzerland) · 2022Article
- DisCovER: distance- and orientation-based covariational threading for weakly homologous proteins.Proteins · 2022Article
- ProALIGN: Directly Learning Alignments for Protein Structure Prediction via Exploiting Context-Specific Alignment Motifs.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- A tale of solving two computational challenges in protein science: neoantigen prediction and protein structure prediction.Briefings in bioinformatics · 2022Review
- FALCON2: a web server for high-quality prediction of protein tertiary structures.BMC bioinformatics · 2021Article
- FVIII inhibitors display FV-neutralizing activity in the prothrombin time assay.Journal of thrombosis and haemostasis : JTH · 2021Article
- The Protective A673T Mutation of Amyloid Precursor Protein (APP) in Alzheimer's Disease.Molecular neurobiology · 2021Review
- Deep template-based protein structure prediction.PLoS computational biology · 2021Article
- Article
- Recent Advances in Protein Homology Detection Propelled by Inter-Residue Interaction Map Threading.Frontiers in molecular biosciences · 2021Review
- GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins.BioImpacts : BI · 2021Article
- New highly antigenic linear B cell epitope peptides from PvAMA-1 as potential vaccine candidates.PloS one · 2021Article
- Template-based prediction of protein structure with deep learning.BMC genomics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
motivationAlignment errors are still the main bottleneck for current template-based protein modeling (TM) methods, including protein threading and homology modeling, especially when the sequence identity between two proteins under consideration is low (<30%).
resultsWe present a novel protein threading method, CNFpred, which achieves much more accurate sequence-template alignment by employing a probabilistic graphical model called a Conditional Neural Field (CNF), which aligns one protein sequence to its remote template using a non-linear scoring function. This scoring function accounts for correlation among a variety of protein sequence and structure features, makes use of information in the neighborhood of two residues to be aligned, and is thus much more sensitive than the widely used linear or profile-based scoring function. To train this CNF threading model, we employ a novel quality-sensitive method, instead of the standard maximum-likelihood method, to maximize directly the expected quality of the training set. Experimental results show that CNFpred generates significantly better alignments than the best profile-based and threading methods on several public (but small) benchmarks as well as our own large dataset. CNFpred outperforms others regardless of the lengths or classes of proteins, and works particularly well for proteins with sparse sequence profiles due to the effective utilization of structure information. Our methodology can also be adapted to protein sequence alignment.
Indexed as
Identifiers
What OpenQuestion holds
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.