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Subgraph Matching for High-Throughput DNA-Aptamer Secondary Structure Classification and Machine Learning Interpretability (Case No. 2025-104)
Intro Sentence: UCLA researchers in the Department of Mathematics have developed machine learning methods to rapidly identify novel aptamer sequences for target binding to accelerate highly-accurate diagnostic and therapeutic development. Background: Aptamers are single-stranded nucleotide polymers that bind with high affinity to targets such as...
Published: 7/22/2025   |   Inventor(s): Andrea Bertozzi, Anne Andrews, Matthew Tyler, Paolo Climaco, Noelle Mitchell
Keywords(s): Advanced Computing / AI, advanced computing methods, Aptamers, Artifical Intelligence (Machine Learning, Data Mining), artificial intelligence/machine learning models, bioinformatics pipeline, cancer target, clustering, computational efficiency, computational efficiency and analysis, design software, DNA clustering, DNA oligomer, DNA Sequencing, Drug, Drug Delivery, Drug Development, Drug Discovery, drug screening, high throughput, high throughput assays, high throughput testing, high-throughput analysis, High-Throughput Screening, interpretability, pipeline, large-scale parallelization, Machine Learning, machine learning modeling, motif structures, open source, open source code, OpenAI, Pharmaceutical Drug, protein classification, secondary structure, SELEX, sequences of interest, single strand DNA sequences, Software, Software & Algorithms, Software Development Tools, Software-enabled learning, subgraph matching, target binding, target detection, Targeted Therapy, Targets And Assays, tissue targeting accuracy
Category(s): Software & Algorithms, Software & Algorithms > AI Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Data Analytics, Life Science Research Tools, Life Science Research Tools > Research Methods, Life Science Research Tools > Screening Libraries, Platforms, Platforms > Drug Delivery, Diagnostic Markers > Targets And Assays, Diagnostic Markers, Software & Algorithms > Bioinformatics