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Year Number of Results
1988 1
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1999 3
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2001 15
2002 21
2003 34
2004 41
2005 53
2006 94
2007 97
2008 135
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2012 202
2013 266
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2025 1324

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22,074 results

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Page 1
Directed Evolution of Fluorescent Genetically Encoded Biosensors: Innovative Approaches for Development and Optimization of Biosensors.
Kuldyushev NA. Kuldyushev NA. Chembiochem. 2025 Mar 16:e202401055. doi: 10.1002/cbic.202401055. Online ahead of print. Chembiochem. 2025. PMID: 40090897
Fluorescent protein-based biosensors are indispensable molecular tools in cell biology and biomedical research, providing non-invasive dynamic measurements of metabolite concentrations and other cellular signals. ...This review discusses recent advancements in the developm …
Fluorescent protein-based biosensors are indispensable molecular tools in cell biology and biomedical research, providing non-invasiv …
Unveiling the Role of Protein Posttranslational Modifications in Glioma Prognosis.
Jiang Z, Huang H, Guo Y, Wang Z, Huang H, Yin W, Huang H, Wang L, Liu W, Jiang X, Ren C. Jiang Z, et al. CNS Neurosci Ther. 2025 Mar;31(3):e70330. doi: 10.1111/cns.70330. CNS Neurosci Ther. 2025. PMID: 40090864
Despite their established role in tumor biology, the systematic characterization of PTM-mediated molecular mechanisms driving glioma progression remains unexplored. ...Differentially expressed genes (DEGs) were identified to construct a robust prognostic prediction model w …
Despite their established role in tumor biology, the systematic characterization of PTM-mediated molecular mechanisms driving glioma …
Screening necroptosis genes influencing osteoarthritis development based on machine learning.
Wang Y, Guo X, Wang B, Zheng J, Li K, Zhang Z, Zhang Y, Huang H. Wang Y, et al. Sci Rep. 2025 Mar 15;15(1):9019. doi: 10.1038/s41598-025-92911-y. Sci Rep. 2025. PMID: 40089565
Machine learning can be applied to identify key genes associated with osteoarthritis (OA). ...
Machine learning can be applied to identify key genes associated with osteoarthritis (OA). ...
ASiDentify (ASiD): A Machine Learning Model to Predict New Autism Spectrum Disorder Risk Genes.
Rynard KM, Han K, Wainberg M, Calarco JA, Lee HO, Lipshitz HD, Smibert CA, Tripathy SJ. Rynard KM, et al. Genetics. 2025 Mar 15:iyaf040. doi: 10.1093/genetics/iyaf040. Online ahead of print. Genetics. 2025. PMID: 40088463
To predict candidate ASD risk genes, we developed a simple machine learning model, ASiDentify (ASiD), using human genomic, RNA- and protein-based features. ...
To predict candidate ASD risk genes, we developed a simple machine learning model, ASiDentify (ASiD), using human genomic, RNA …
Deep representation learning for clustering longitudinal survival data from electronic health records.
Qiu J, Hu Y, Li L, Erzurumluoglu AM, Braenne I, Whitehurst C, Schmitz J, Arora J, Bartholdy BA, Gandhi S, Khoueiry P, Mueller S, Noyvert B, Ding Z, Jensen JN, de Jong J. Qiu J, et al. Nat Commun. 2025 Mar 14;16(1):2534. doi: 10.1038/s41467-025-56625-z. Nat Commun. 2025. PMID: 40087274
Electronic health records provide major opportunities for leveraging machine learning approaches to uncover novel patient subgroups. However, many existing approaches fail to adequately capture complex interactions between diagnosis trajectories and disease-relevant …
Electronic health records provide major opportunities for leveraging machine learning approaches to uncover novel patient subg …
Fingerprinting of Boletus bainiugan: FT-NIR spectroscopy combined with machine learning a new workflow for storage period identification.
Deng G, Liu H, Li J, Wang Y. Deng G, et al. Food Microbiol. 2025 Aug;129:104743. doi: 10.1016/j.fm.2025.104743. Epub 2025 Feb 6. Food Microbiol. 2025. PMID: 40086983
Guanosine and adenosine increased with storage time, and uridine has a decreasing trend. Multi-conventional machine learning and deep learning models are employed to identify the storage time of Boletus bainiugan, in which convolutional neural network (CNN) and back …
Guanosine and adenosine increased with storage time, and uridine has a decreasing trend. Multi-conventional machine learning a …
Yeast complementation assays provide limited informationon functional features of K+ channels.
Kurkovetz K, Cartolano M, Gebhardt M, Schumann LE, Kast SM, Moroni A, Thiel G, Rauh O. Kurkovetz K, et al. Biophys Rep (N Y). 2025 Mar 12:100206. doi: 10.1016/j.bpr.2025.100206. Online ahead of print. Biophys Rep (N Y). 2025. PMID: 40086750 Free article.
We investigate to what extent yeast complementation assays, which in principle can provide large amounts of training data for machine learning models, yield quantitative correlations between growth rescue and single channel recordings. If this were the case, yeast c …
We investigate to what extent yeast complementation assays, which in principle can provide large amounts of training data for machine …
BERT-AmPEP60: A BERT-Based Transfer Learning Approach to Predict the Minimum Inhibitory Concentrations of Antimicrobial Peptides for Escherichia coli and Staphylococcus aureus.
Cai J, Yan J, Un C, Wang Y, Campbell-Valois FX, Siu SWI. Cai J, et al. J Chem Inf Model. 2025 Mar 14. doi: 10.1021/acs.jcim.4c01749. Online ahead of print. J Chem Inf Model. 2025. PMID: 40086449
In five independent experiments with 10% leave-out sequences as the test sets, the optimal EC and SA models outperformed the state-of-the-art regression method and traditional machine learning methods, achieving an average mean squared error of 0.2664 and 0.3032 (lo …
In five independent experiments with 10% leave-out sequences as the test sets, the optimal EC and SA models outperformed the state-of-the-ar …
22,074 results
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