2025
Connectome-driven neural inventory of a complete visual system
Nern A, Loesche F, Takemura S, Burnett L, Dreher M, Gruntman E, Hoeller J, Huang G, Januszewski M, Klapoetke N, Koskela S, Longden K, Lu Z, Preibisch S, Qiu W, Rogers E, Seenivasan P, Zhao A, Bogovic J, Canino B, Clements J, Cook M, Finley-May S, Flynn M, Hameed I, Fragniere A, Hayworth K, Hopkins G, Hubbard P, Katz W, Kovalyak J, Lauchie S, Leonard M, Lohff A, Maldonado C, Mooney C, Okeoma N, Olbris D, Ordish C, Paterson T, Phillips E, Pietzsch T, Salinas J, Rivlin P, Schlegel P, Scott A, Scuderi L, Takemura S, Talebi I, Thomson A, Trautman E, Umayam L, Walsh C, Walsh J, Xu C, Yakal E, Yang T, Zhao T, Funke J, George R, Hess H, Jefferis G, Knecht C, Korff W, Plaza S, Romani S, Saalfeld S, Scheffer L, Berg S, Rubin G, Reiser M. Connectome-driven neural inventory of a complete visual system. Nature 2025, 641: 1225-1237. PMID: 40140576, PMCID: PMC12119369, DOI: 10.1038/s41586-025-08746-0.Peer-Reviewed Original ResearchConceptsVisual systemNetwork of neuronsVisual neuronsNeural architectureConnectivity informationFocused ion beam millingSplit-GAL4 linesIon beam millingSpatial featuresVisual sceneVisualization capabilitiesComputational frameworkDiverse featuresExpert curationVisual regionsDiverse networksBeam millingStructure-function relationshipsCapability of flyingRight optic lobesNeurotransmitter identityVisionOptic lobeCell typesComprehensive set
2024
PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge
Wei C, Allot A, Lai P, Leaman R, Tian S, Luo L, Jin Q, Wang Z, Chen Q, Lu Z. PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge. Nucleic Acids Research 2024, 52: w540-w546. PMID: 38572754, PMCID: PMC11223843, DOI: 10.1093/nar/gkae235.Peer-Reviewed Original ResearchState-of-the-art AI techniquesState-of-the-artComplex information needsAdvanced search capabilitiesPairs queriesEntity relationsRetrieval qualitySearch capabilityAI techniquesLiterature resourcesPubTatorInformation needsPubMed abstractsBiomedical literatureOnline interfaceLarge-scale analysisGenetic variantsBiomedical knowledgeAPIScientific discoveryComprehensive setChatGPTQueryVerifiabilityRetrieval
2018
Multivariate Pattern Analysis of Genotype–Phenotype Relationships in Schizophrenia
Zheutlin AB, Chekroud AM, Polimanti R, Gelernter J, Sabb FW, Bilder RM, Freimer N, London ED, Hultman CM, Cannon TD. Multivariate Pattern Analysis of Genotype–Phenotype Relationships in Schizophrenia. Schizophrenia Bulletin 2018, 44: 1045-1052. PMID: 29534239, PMCID: PMC6101611, DOI: 10.1093/schbul/sby005.Peer-Reviewed Original ResearchConceptsMultivariate pattern analysisIndependent samplesVisual memoryCognitive endophenotypesPredictive strengthSchizophreniaMemoryIndividual variationPattern analysisSingle predictorCertain domainsDiscovery samplePsychiatric patientsPolygenic risk scoresPredictive powerScoresEndophenotypesPotential relationshipRelationshipRandom forestGenetic risk variantsLimited setPredictorsComprehensive setSamples
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