首页|Machine learning enables high-throughput, low-replicate screening for novel anti -seizure targets and compounds using combined movement and calcium fluorescence in larval zebrafish
Machine learning enables high-throughput, low-replicate screening for novel anti -seizure targets and compounds using combined movement and calcium fluorescence in larval zebrafish
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from bi orxiv.org:“Identifying new, more efficacious anti-seizure medications (ASMs) is challengin g, partly due to limitationsin animal-based assays. Zebrafish (Danio rerio) can serve as a model of chemical and geneticseizures, but methods for detecting se izure-like activity in zebrafish, though powerful, have been hamperedby low sen sitivity (locomotor/behavioral assays) or low-throughput (tectal electrophysiolo gy orcalcium fluorescence microscopy).
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