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Numerical spiking neural P systems with production functions on synapses.

, , , , and . Theor. Comput. Sci., 940 (Part): 80-89 (2023)

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Numerical P systems with production thresholds., , , and . Theor. Comput. Sci., (2017)Numerical P systems with migrating variables., , , and . Theor. Comput. Sci., (2016)Numerical spiking neural P systems with production functions on synapses., , , , and . Theor. Comput. Sci., 940 (Part): 80-89 (2023)Spiking neural P systems with mute rules., , , and . Inf. Comput., (2024)Improved Multi-step Iterative Algorithms for the Fixed Points of Strongly Pseudo-Contractive Mappings., , , , , and . BIC-TA (2), volume 682 of Communications in Computer and Information Science, page 489-496. Springer, (2016)Spiking neural P systems with rules on synapses and anti-spikes., , , , and . Theor. Comput. Sci., (2018)Spiking Neural P Systems: Theoretical Results and Applications., , , and . Enjoying Natural Computing, volume 11270 of Lecture Notes in Computer Science, page 256-268. Springer, (2018)CAPLA: improved prediction of protein-ligand binding affinity by a deep learning approach based on a cross-attention mechanism., , , , , , , and . Bioinform., (February 2023)TransRNAm: Identifying Twelve Types of RNA Modifications by an Interpretable Multi-Label Deep Learning Model Based on Transformer., , , , , , , and . IEEE ACM Trans. Comput. Biol. Bioinform., 20 (6): 3623-3634 (November 2023)MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction., , , , , , , , , and 1 other author(s). IEEE J. Biomed. Health Informatics, 28 (8): 4995-5006 (August 2024)