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Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides.

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第一作者： Phasit,Charoenkwan

第一单位： Modern Management and Information Technology, College of Arts, Media and Technology, Chiang Mai University, 50200, Chiang Mai, Thailand.

作者： Phasit,Charoenkwan ^[1] ; Pramote,Chumnanpuen ^[2] ; Nalini,Schaduangrat ^[3] ; Pietro,Lio' ^[4] ; Mohammad Ali,Moni ^[5] ; Watshara,Shoombuatong ^[6]

作者单位： Modern Management and Information Technology, College of Arts, Media and Technology, Chiang Mai University, 50200, Chiang Mai, Thailand. ^[1] Department of Zoology, Faculty of Science, Kasetsart University, 10900, Bangkok, Thailand.;Omics Center for Agriculture, Bioresources, Food, and Health, Kasetsart University (OmiKU), 10900, Bangkok, Thailand. ^[2] Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, 10700, Bangkok, Thailand. ^[3] Department of Computer Science and Technology, University of Cambridge, CB3 0FD, Cambridge, UK. ^[4] Artificial Intelligence & Digital Health Data Science, School of Health and Rehabilitation Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, 4072, St Lucia, QLD, Australia. ^[5] Center of Data Mining and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, 10700, Bangkok, Thailand. watshara.sho@mahidol.ac.th. ^[6]

关键词 Bioinformatics Blood-brain barrier Machine learning Penetrating peptides Propensity score Scoring card method Sequence analysis

医学主题词血脑屏障(Blood-Brain Barrier);二肽类(Dipeptides);倾向性评分(Propensity Score);内皮细胞(Endothelial Cells);肽类(Peptides);氨基酸类(Amino Acids)

DOI 10.1007/s10822-022-00476-z

PMID 36284036

发布时间 2022-11-21

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准确一般字义偏差语意偏离译文作用小提交