Lin Dai
About
Lin Dai is a scholar working on Molecular Biology, Physiology and Statistics and Probability.
According to data from OpenAlex, Lin Dai has authored 47 papers receiving a total of 648 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 5 papers in Physiology and 5 papers in Statistics and Probability. Recurrent topics in Lin Dai’s work include Gut microbiota and health (7 papers), Endometriosis Research and Treatment (3 papers) and Bayesian Methods and Mixture Models (3 papers). Lin Dai is often cited by papers focused on Gut microbiota and health (7 papers), Endometriosis Research and Treatment (3 papers) and Bayesian Methods and Mixture Models (3 papers). Lin Dai collaborates with scholars based in China, United Kingdom and United States. Lin Dai's co-authors include Fang Huang, Zhanshan Ma, Xiang Wang, Guanzhen Gao and Mulugeta Gebregziabher and has published in prestigious journals such as PLoS ONE, Food Chemistry and Journal of Nutrition.
In The Last Decade
Fields of papers citing papers by Lin Dai
Since SpecializationEngineeringComputer SciencePhysics and AstronomyMathematicsEarth and Planetary SciencesEnergyEnvironmental ScienceMaterials ScienceChemical EngineeringChemistryAgricultural and Biological SciencesVeterinaryDecision SciencesArts and HumanitiesBusiness, Management and AccountingSocial SciencesPsychologyEconomics, Econometrics and FinanceHealth ProfessionsDentistryMedicineBiochemistry, Genetics and Molecular BiologyNeuroscienceNursingImmunology and MicrobiologyPharmacology, Toxicology and Pharmaceutics
This network shows the specialization of papers citing the papers produced by Lin Dai. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where Lin Dai may publish in the future.
Countries citing papers authored by Lin Dai
Since SpecializationCitations
This map shows the geographic impact of Lin Dai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lin Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Dai more than expected).
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