Works matching DE "PROTEIN models"
Results: 1116
PIPENN-EMB ensemble net and protein embeddings generalise protein interface prediction beyond homology.
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- Scientific Reports, 2025, v. 15, n. 1, p. 1, doi. 10.1038/s41598-025-88445-y
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Multiple combinatorial interactions among natural structural variants of Brassica SOC1 promoters and SVP: conservation of binding affinity despite diversity in bimolecular interactions.
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- Molecular Biology Reports, 2025, v. 52, n. 1, p. 1, doi. 10.1007/s11033-024-10182-8
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Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction.
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- Nature Communications, 2025, v. 16, n. 1, p. 1, doi. 10.1038/s41467-025-56526-1
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El arte del modelamiento molecular de proteínas y su reconocimiento con el premio nobel de Química 2024.
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- Revista Lasallista de Investigación, 2024, v. 21, n. 2, p. 5
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GlyCompute: towards the automated analysis of protein N-linked glycosylation kinetics via an open-source computational framework.
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- Analytical & Bioanalytical Chemistry, 2025, v. 417, n. 5, p. 957, doi. 10.1007/s00216-024-05522-3
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Chemical- and photo-activation of protein-protein thiol-ene coupling for protein profiling.
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- Communications Chemistry, 2025, v. 8, n. 1, p. 1, doi. 10.1038/s42004-025-01412-6
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Post-genomic analysis of Monosporascus cannonballus and Macrophomina phaseolina - potential target selection.
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- Acta Scientiarum: Agronomy, 2024, v. 46, p. 1, doi. 10.4025/actasciagron.v46i1.65794
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Conservation and divergence of protein pathways in the vertebrate heart.
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- PLoS Biology, 2019, v. 17, n. 9, p. 1, doi. 10.1371/journal.pbio.3000437
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Automatically obtaining a cellular automaton scheme for modeling protein folding using the FCC model.
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- Natural Computing, 2019, v. 18, n. 2, p. 275, doi. 10.1007/s11047-018-9705-y
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A Euclidean distance matrix model for protein molecular conformation.
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- Journal of Global Optimization, 2020, v. 76, n. 4, p. 709, doi. 10.1007/s10898-019-00771-4
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Anti-inflammatory potential of baicalein combined with silk fibroin protein in a zebrafish model (Danio rerio).
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- Biotechnology Letters, 2023, v. 45, n. 2, p. 235, doi. 10.1007/s10529-022-03334-y
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A novel method for the in vitro assembly of virus-like particles and multimeric proteins.
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- Biotechnology Letters, 2021, v. 43, n. 6, p. 1155, doi. 10.1007/s10529-021-03093-2
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Small design from big alignment: engineering proteins with multiple sequence alignment as the starting point.
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- Biotechnology Letters, 2020, v. 42, n. 8, p. 1305, doi. 10.1007/s10529-020-02914-0
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Feasible development of stable HEK293 clones by CRISPR/Cas9-mediated site-specific integration for biopharmaceuticals production.
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- Biotechnology Letters, 2019, v. 41, n. 8/9, p. 941, doi. 10.1007/s10529-019-02702-5
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A guideline for homology modeling of the proteins from newly discovered betacoronavirus, 2019 novel coronavirus (2019‐nCoV).
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- Journal of Medical Virology, 2020, v. 92, n. 9, p. 1542, doi. 10.1002/jmv.25768
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Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning.
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- Molecular Medicine, 2023, v. 29, n. 1, p. 1, doi. 10.1186/s10020-023-00610-z
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Optimal clustering for quantum refinement of biomolecular structures: Q|R#4.
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- Theoretical Chemistry Accounts: Theory, Computation, & Modeling, 2023, v. 142, n. 10, p. 1, doi. 10.1007/s00214-023-03046-0
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HBFormer: a single-stream framework based on hybrid attention mechanism for identification of human-virus protein–protein interactions.
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- Bioinformatics, 2024, v. 40, n. 12, p. 1, doi. 10.1093/bioinformatics/btae724
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Sensitivities in protein allocation models reveal distribution of metabolic capacity and flux control.
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- Bioinformatics, 2024, v. 40, n. 12, p. 1, doi. 10.1093/bioinformatics/btae691
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STRPsearch: fast detection of structured tandem repeat proteins.
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- Bioinformatics, 2024, v. 40, n. 12, p. 1, doi. 10.1093/bioinformatics/btae690
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ADTGP: correcting single-cell antibody sequencing data using Gaussian process regression.
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- Bioinformatics, 2024, v. 40, n. 11, p. 1, doi. 10.1093/bioinformatics/btae660
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p-IgGen: a paired antibody generative language model.
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- Bioinformatics, 2024, v. 40, n. 11, p. 1, doi. 10.1093/bioinformatics/btae659
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Prediction of human O-linked glycosylation sites using stacked generalization and embeddings from pre-trained protein language model.
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- Bioinformatics, 2024, v. 40, n. 11, p. 1, doi. 10.1093/bioinformatics/btae643
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EuDockScore: Euclidean graph neural networks for scoring protein–protein interfaces.
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- Bioinformatics, 2024, v. 40, n. 11, p. 1, doi. 10.1093/bioinformatics/btae636
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Expert-guided protein language models enable accurate and blazingly fast fitness prediction.
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- Bioinformatics, 2024, v. 40, n. 11, p. 1, doi. 10.1093/bioinformatics/btae621
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Pair-EGRET: enhancing the prediction of protein–protein interaction sites through graph attention networks and protein language models.
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- Bioinformatics, 2024, v. 40, n. 10, p. 1, doi. 10.1093/bioinformatics/btae588
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DockQ v2: improved automatic quality measure for protein multimers, nucleic acids, and small molecules.
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- Bioinformatics, 2024, v. 40, n. 10, p. 1, doi. 10.1093/bioinformatics/btae586
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Towards the accurate modelling of antibody−antigen complexes from sequence using machine learning and information-driven docking.
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- Bioinformatics, 2024, v. 40, n. 10, p. 1, doi. 10.1093/bioinformatics/btae583
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Prediction of antibiotic resistance mechanisms using a protein language model.
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- Bioinformatics, 2024, v. 40, n. 10, p. 1, doi. 10.1093/bioinformatics/btae550
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learnMSA2: deep protein multiple alignments with large language and hidden Markov models.
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- Bioinformatics, 2024, v. 40, p. ii79, doi. 10.1093/bioinformatics/btae381
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Accurate and efficient protein embedding using multi-teacher distillation learning.
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- Bioinformatics, 2024, v. 40, n. 9, p. 1, doi. 10.1093/bioinformatics/btae567
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DTI-LM: language model powered drug–target interaction prediction.
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- Bioinformatics, 2024, v. 40, n. 9, p. 1, doi. 10.1093/bioinformatics/btae533
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Are genomic language models all you need? Exploring genomic language models on protein downstream tasks.
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- Bioinformatics, 2024, v. 40, n. 9, p. 1, doi. 10.1093/bioinformatics/btae529
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PGAT-ABPp: harnessing protein language models and graph attention networks for antibacterial peptide identification with remarkable accuracy.
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- Bioinformatics, 2024, v. 40, n. 8, p. 1, doi. 10.1093/bioinformatics/btae497
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Benchmarking of AlphaFold2 accuracy self-estimates as indicators of empirical model quality and ranking: a comparison with independent model quality assessment programmes.
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- Bioinformatics, 2024, v. 40, n. 8, p. 1, doi. 10.1093/bioinformatics/btae491
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Enhancing predictions of protein stability changes induced by single mutations using MSA-based language models.
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- Bioinformatics, 2024, v. 40, n. 7, p. 1, doi. 10.1093/bioinformatics/btae447
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LMCrot: an enhanced protein crotonylation site predictor by leveraging an interpretable window-level embedding from a transformer-based protein language model.
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- Bioinformatics, 2024, v. 40, n. 5, p. 1, doi. 10.1093/bioinformatics/btae290
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TemStaPro: protein thermostability prediction using sequence representations from protein language models.
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- Bioinformatics, 2024, v. 40, n. 4, p. 1, doi. 10.1093/bioinformatics/btae157
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iNGNN-DTI: prediction of drug–target interaction with interpretable nested graph neural network and pretrained molecule models.
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- Bioinformatics, 2024, v. 40, n. 3, p. 1, doi. 10.1093/bioinformatics/btae135
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CryoTransformer: a transformer model for picking protein particles from cryo-EM micrographs.
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- Bioinformatics, 2024, v. 40, n. 3, p. 1, doi. 10.1093/bioinformatics/btae109
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Selection among site-dependent structurally constrained substitution models of protein evolution by approximate Bayesian computation.
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- Bioinformatics, 2024, v. 40, n. 3, p. 1, doi. 10.1093/bioinformatics/btae096
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Insights into the inner workings of transformer models for protein function prediction.
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- Bioinformatics, 2024, v. 40, n. 3, p. 1, doi. 10.1093/bioinformatics/btae031
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Protein language models meet reduced amino acid alphabets.
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- Bioinformatics, 2024, v. 40, n. 2, p. 1, doi. 10.1093/bioinformatics/btae061
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Guiding discovery of protein sequence-structure-function modeling.
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- Bioinformatics, 2024, v. 40, n. 1, p. 1, doi. 10.1093/bioinformatics/btae002
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Embedding-based alignment: combining protein language models with dynamic programming alignment to detect structural similarities in the twilight-zone.
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- Bioinformatics, 2024, v. 40, n. 1, p. 1, doi. 10.1093/bioinformatics/btad786
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M-Ionic: prediction of metal-ion-binding sites from sequence using residue embeddings.
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- Bioinformatics, 2024, v. 40, n. 1, p. 1, doi. 10.1093/bioinformatics/btad782
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Local Disordered Region Sampling (LDRS) for ensemble modeling of proteins with experimentally undetermined or low confidence prediction segments.
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- Bioinformatics, 2023, v. 39, n. 12, p. 1, doi. 10.1093/bioinformatics/btad739
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PLM-ARG: antibiotic resistance gene identification using a pretrained protein language model.
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- Bioinformatics, 2023, v. 39, n. 11, p. 1, doi. 10.1093/bioinformatics/btad690
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PROSTATA: a framework for protein stability assessment using transformers.
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- Bioinformatics, 2023, v. 39, n. 11, p. 1, doi. 10.1093/bioinformatics/btad671
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THPLM: a sequence-based deep learning framework for protein stability changes prediction upon point variations using pretrained protein language model.
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- Bioinformatics, 2023, v. 39, n. 11, p. 1, doi. 10.1093/bioinformatics/btad646
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