ReviewBioengineering (Basel, Switzerland)2024
Artificial Intelligence Transforming Post-Translational Modification Research.
Review in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Post-translational modification-regulating biomaterials for regeneration.Bioactive materials · 2026Review
- AI-Predicted Model-Guided Rebuilding of the Experimental Structure of Mouse δ-Aminolevulinic Acid Dehydratase.International journal of molecular sciences · 2026Article
- SCSEQ: A web tool for analyzing single-cell RNA-seq data.GigaScience · 2026Article
- Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome.Journal of cardiovascular development and disease · 2026Review
- Artificial intelligence in antibody design and development: harnessing the power of computational approaches.Medical & biological engineering & computing · 2025Review
- Posttranslational modifications of phosphodiesterase type 4 enzymes represent novel points for therapeutic targeting.The FEBS journal · 2025Review
- Review
- Integrating Redox Proteomics and Computational Modeling to Decipher Thiol-Based Oxidative Post-Translational Modifications (oxiPTMs) in Plant Stress Physiology.International journal of molecular sciences · 2025Review
- Exosome-based immunotherapy in hepatocellular carcinoma.Clinical and experimental medicine · 2025Review
- The Role of Lactate and Lactylation in the Dysregulation of Immune Responses in Psoriasis.Clinical reviews in allergy & immunology · 2025Review
- ProCaliper: functional and structural analysis, visualization, and annotation of proteins.Bioinformatics advances · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Post-Translational Modifications (PTMs) are covalent changes to amino acids that occur after protein synthesis, including covalent modifications on side chains and peptide backbones. Many PTMs profoundly impact cellular and molecular functions and structures, and their significance extends to evolutionary studies as well. In light of these implications, we have explored how artificial intelligence (AI) can be utilized in researching PTMs. Initially, rationales for adopting AI and its advantages in understanding the functions of PTMs are discussed. Then, various deep learning architectures and programs, including recent applications of language models, for predicting PTM sites on proteins and the regulatory functions of these PTMs are compared. Finally, our high-throughput PTM-data-generation pipeline, which formats data suitably for AI training and predictions is described. We hope this review illuminates areas where future AI models on PTMs can be improved, thereby contributing to the field of PTM bioengineering.
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.