45SESSION 3 : Imaging of Cell Population Dynamics and AI PredictionSESSION 4 : AI for Brain Imaging1.EverythingasCodeDavid Van ValenCaliforniaInstituteofTechnology2.AnInteractiveDeepLearning-basedApproachRevealsMitochondrialCristaeTopologiesYusuke HirabayashiTheUniversityofTokyo3.EstablishmentofCellular‘Dynalogy’–anAI-basedNovelResearchTrendforUnderstandingtheLifeActivityBasedonTheirDynamicNatureMasaru IshiiOsakaUniversity4.NetworkCellMeasurementsviaMultimodalBarcodedDropletsSadao OtaTheUniversityofTokyo5.Super-resolutionImagingofTranscriptioninLivingCellsIbrahim CisséMPIofImmunobiologyandEpigenetics1.ChallengesandResourcesforMakingBigNeuroscienceDataOpen,FAIRandAIReadyMaryann E. MartoneUCSD2.iPSCDataScience:CellularDissectionofPolygenicityUncoveringthePolygenicArchitectureofAlzheimer’sDiseaseHaruhisa InoueKyotoUniversity3.NeuronalSignalsRegulatingEmotionandMemoryKozo KaibuchiFujitaHealthUniversity4.Label-freeImagingofIntracellularDynamicsCombinedwithMulti-omicsApproachforInducedPluripotentStemCellsYohei HayashiRIKEN
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