2025
Resolution in super-resolution microscopy – facts, artifacts, technological advancements and biological applications
Prakash K, Baddeley D, Eggeling C, Fiolka R, Heintzmann R, Manley S, Radenovic A, Shroff H, Smith C, Schermelleh L. Resolution in super-resolution microscopy – facts, artifacts, technological advancements and biological applications. Journal Of Cell Science 2025, 138: jcs263567. PMID: 40421932, PMCID: PMC12148039, DOI: 10.1242/jcs.263567.Peer-Reviewed Original Research
2024
Large language models surpass human experts in predicting neuroscience results
Luo X, Rechardt A, Sun G, Nejad K, Yáñez F, Yilmaz B, Lee K, Cohen A, Borghesani V, Pashkov A, Marinazzo D, Nicholas J, Salatiello A, Sucholutsky I, Minervini P, Razavi S, Rocca R, Yusifov E, Okalova T, Gu N, Ferianc M, Khona M, Patil K, Lee P, Mata R, Myers N, Bizley J, Musslick S, Bilgin I, Niso G, Ales J, Gaebler M, Ratan Murty N, Loued-Khenissi L, Behler A, Hall C, Dafflon J, Bao S, Love B. Large language models surpass human experts in predicting neuroscience results. Nature Human Behaviour 2024, 9: 305-315. PMID: 39604572, PMCID: PMC11860209, DOI: 10.1038/s41562-024-02046-9.Peer-Reviewed Original ResearchConceptsHuman expertsLanguage modelHuman information processing capacityNeuroscience resultsKnowledge-intensive endeavourInformation processing capacityProcessing capacityNeuroscience literatureExperimental outcomesExpertsHigh confidenceScientific discoveryDecades of researchLanguageNeuroscienceLLMTaskPubTator 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
2022
Applications and Techniques for Fast Machine Learning in Science
Deiana A, Tran N, Agar J, Blott M, Di Guglielmo G, Duarte J, Harris P, Hauck S, Liu M, Neubauer M, Ngadiuba J, Ogrenci-Memik S, Pierini M, Aarrestad T, Bähr S, Becker J, Berthold A, Bonventre R, Bravo T, Diefenthaler M, Dong Z, Fritzsche N, Gholami A, Govorkova E, Guo D, Hazelwood K, Herwig C, Khan B, Kim S, Klijnsma T, Liu Y, Lo K, Nguyen T, Pezzullo G, Rasoulinezhad S, Rivera R, Scholberg K, Selig J, Sen S, Strukov D, Tang W, Thais S, Unger K, Vilalta R, von Krosigk B, Wang S, Warburton T. Applications and Techniques for Fast Machine Learning in Science. Frontiers In Big Data 2022, 5: 787421. PMID: 35496379, PMCID: PMC9041419, DOI: 10.3389/fdata.2022.787421.Peer-Reviewed Original ResearchScientific domainsPowerful ML methodsMultiple scientific domainsHigh-level overviewComputing architectureML algorithmsFast machineScientific discoveryML methodsML solutionProcessing loopCommon solutionMachineAlgorithmScience communityApplicationsArchitectureCommunity reportsPerformantPlatformPointersTechniqueDomainMain areasTechnology
2021
Chickens as a simple system for scientific discovery: The example of the MHC
Tregaskes C, Kaufman J. Chickens as a simple system for scientific discovery: The example of the MHC. Molecular Immunology 2021, 135: 12-20. PMID: 33845329, PMCID: PMC7611830, DOI: 10.1016/j.molimm.2021.03.019.Peer-Reviewed Original Research
2020
Impact of Diverse Data Sources on Computational Phenotyping
Wang L, Olson J, Bielinski S, St. Sauver J, Fu S, He H, Cicek M, Hathcock M, Cerhan J, Liu H. Impact of Diverse Data Sources on Computational Phenotyping. Frontiers In Genetics 2020, 11: 556. PMID: 32582289, PMCID: PMC7283539, DOI: 10.3389/fgene.2020.00556.Peer-Reviewed Original ResearchDiverse data sourcesElectronic health recordsComputational phenotypingData fragmentationPhenotyping algorithmData sourcesRochester Epidemiology ProjectPositive predictive valueSingle data sourceFalse negative rateRheumatoid arthritisEHR dataMultiple health care systemsHealth recordsMayo dataIncomplete dataType 2 diabetes mellitusAlgorithmPhenotype informationIntegrated sourceHealth care systemScientific discoveryT2DM controlDiabetes mellitusMedical recordsCausal Relational Learning
Salimi B, Parikh H, Kayali M, Getoor L, Roy S, Suciu D. Causal Relational Learning. 2020, 241-256. DOI: 10.1145/3318464.3389759.Peer-Reviewed Original ResearchRelational dataDatalog-like rulesMultiple relational tablesComplex relational structuresDeclarative languageRelational tablesExperimental evaluationReal-world settingsCost constraintsRelational domainsInferenceRelational structureCausal inferenceDecision makingScientific discoverySocial sciencesHeterogeneous elementsDomainInformed decision makingHomogeneous elementsFrameworkRulesConstraintsLanguageData
2016
Being open minded about neuromodulation trials: Finding success in our “failures”
Fins J, Kubu C, Mayberg H, Merkel R, Nuttin B, Schlaepfer T. Being open minded about neuromodulation trials: Finding success in our “failures”. Brain Stimulation 2016, 10: 181-186. PMID: 28159536, DOI: 10.1016/j.brs.2016.12.012.Peer-Reviewed Original Research
2015
Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature
Nagarajan M, Wilkins A, Bachman B, Novikov I, Bao S, Haas P, Terrón-Díaz M, Bhatia S, Adikesavan A, Labrie J, Regenbogen S, Buchovecky C, Pickering C, Kato L, Lisewski A, Lelescu A, Zhang H, Boyer S, Weber G, Chen Y, Donehower L, Spangler S, Lichtarge O. Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature. 2015, 2019-2028. DOI: 10.1145/2783258.2788609.Peer-Reviewed Original ResearchPreserving Genome Privacy in Research Studies
Wang S, Jiang X, Fox D, Ohno-Machado L. Preserving Genome Privacy in Research Studies. 2015, 425-441. DOI: 10.1007/978-3-319-23633-9_16.Peer-Reviewed Original ResearchGenome privacyPrivacy researchBetter privacy protectionObfuscation of dataSecure data repositoryLoss of privacyData use agreementsPrivacy challengesPrivacy problemsPrivacy protectionAttack modelIndividual privacyData sharingMassive collectionPrivacyData repositoryTraditional clinical informationScientific discoveryGenomic dataData analysis methodsBig challengeUse agreementsBiomedical communityTechnical aspects
2014
Choosing blindly but wisely: differentially private solicitation of DNA datasets for disease marker discovery
Zhao Y, Wang X, Jiang X, Ohno-Machado L, Tang H. Choosing blindly but wisely: differentially private solicitation of DNA datasets for disease marker discovery. Journal Of The American Medical Informatics Association 2014, 22: 100-108. PMID: 25352565, PMCID: PMC4433380, DOI: 10.1136/amiajnl-2014-003043.Peer-Reviewed Original ResearchConceptsData ownersData usersHuman genomic datasetsHuman genomic dataPatient privacyPrivacyGeneration approachUsersData selectionReal dataDatasetGenomic datasetsPrivate solicitationDNA datasetsScientific discoveryNew approachGenomic dataHigh confidencePilot versionEvaluation methodRight choiceOwnersAlgorithmNew techniqueDisease marker discovery
2011
The Emerging Role of Electronic Medical Records in Pharmacogenomics
Wilke R, Xu H, Denny J, Roden D, Krauss R, McCarty C, Davis R, Skaar T, Lamba J, Savova G. The Emerging Role of Electronic Medical Records in Pharmacogenomics. Clinical Pharmacology & Therapeutics 2011, 89: 379-386. PMID: 21248726, PMCID: PMC3204342, DOI: 10.1038/clpt.2010.260.Peer-Reviewed Original Research
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