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Improved Multi-step Iterative Algorithms for the Fixed Points of Strongly Pseudo-Contractive Mappings., , , , , и . BIC-TA (2), том 682 из Communications in Computer and Information Science, стр. 489-496. Springer, (2016)Numerical P systems with production thresholds., , , и . Theor. Comput. Sci., (2017)Numerical spiking neural P systems with production functions on synapses., , , , и . Theor. Comput. Sci., 940 (Part): 80-89 (2023)Numerical P systems with migrating variables., , , и . Theor. Comput. Sci., (2016)Spiking neural P systems with mute rules., , , и . Inf. Comput., (2024)Small Universal Spiking Neural P Systems with Homogenous Neurons and Synapses., , , и . Fundam. Informaticae, 149 (4): 451-470 (2016)Cell-like Spiking Neural P Systems with Anti-spikes and Membrane Division/Dissolution., , , , , и . BIC-TA (2), том 1160 из Communications in Computer and Information Science, стр. 393-408. Springer, (2019)Computation power of asynchronous spiking neural P systems with polarizations., , и . Theor. Comput. Sci., (2019)TransRNAm: Identifying Twelve Types of RNA Modifications by an Interpretable Multi-Label Deep Learning Model Based on Transformer., , , , , , , и . IEEE ACM Trans. Comput. Biol. Bioinform., 20 (6): 3623-3634 (ноября 2023)CAPLA: improved prediction of protein-ligand binding affinity by a deep learning approach based on a cross-attention mechanism., , , , , , , и . Bioinform., (февраля 2023)