L
Lei Chen
Researcher at Shanghai Maritime University
Publications - 318
Citations - 7134
Lei Chen is an academic researcher from Shanghai Maritime University. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 38, co-authored 253 publications receiving 4965 citations. Previous affiliations of Lei Chen include Shanghai Normal University & Qilu University of Technology.
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Journal ArticleDOI
Shorter durations and lower doses of peginterferon alfa-2a are associated with inferior hepatitis B e antigen seroconversion rates in hepatitis B virus genotypes B or C.
Yun-Fan Liaw,Jidong Jia,Hoi-Yun Chan,Kwang Hyub Han,Tawesak Tanwandee,Wan-Long Chuang,Deming Tan,Xinyue Chen,Edward Gane,Teerha Piratvisuth,Lei Chen,Qing Xie,Joseph J.Y. Sung,Cynthia Wat,Coen Bernaards,Y. Cui,Patrick Marcellin +16 more
TL;DR: Compared with lower doses and shorter durations, the licensed PEG‐IFNα‐2a treatment regimen (180μg/48 weeks) was the most efficacious and beneficial for HBeAg‐positive patients predominantly infected with hepatitis B virus genotypes B or C.
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Predicting Anatomical Therapeutic Chemical (ATC) Classification of Drugs by Integrating Chemical-Chemical Interactions and Similarities
TL;DR: It was observed by the jackknife test on a benchmark dataset of 3,883 drug compounds that the overall success rate achieved by the prediction method was about 73% in identifying the drugs among the following 14 main ATC-classes.
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Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways
TL;DR: This study investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes, and suggests that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.
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A similarity-based method for prediction of drug side effects with heterogeneous information.
TL;DR: Results indicated that drug similarity in fingerprint was most related to the prediction of drug side effects and all drug properties gave less or more contributions.
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Analysis of cancer-related lncRNAs using gene ontology and KEGG pathways
TL;DR: Novel insight is provided of how lncRNAs may affect tumorigenesis and which pathways may play important roles during it by extracting important GO terms and KEGG pathways that can help identify cancer-related lnc RNAs.