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28 results on '"Le, Thuc D"'

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4. Listening to young lives at work in Vietnam: second call

5. Identifying preeclampsia-associated genes using a control theory method.

6. pDriver: a novel method for unravelling personalized coding and miRNA cancer drivers.

7. NIBNA: a network-based node importance approach for identifying breast cancer drivers.

8. Large expert-curated database for benchmarking document similarity detection in biomedical literature search

9. The winning methods for predicting cellular position in the DREAM single-cell transcriptomics challenge.

10. DriverGroup: a novel method for identifying driver gene groups.

11. A novel single-cell based method for breast cancer prognosis.

13. CBNA: A control theory based method for identifying coding and non-coding cancer drivers.

15. Use of Haploid Model of Candida albicans to Uncover Mechanism of Action of a Novel Antifungal Agent.

16. Identifying miRNA sponge modules using biclustering and regulatory scores.

17. Inferring microRNA and transcription factor regulatory networks in heterogeneous data.

18. Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives

19. Identifying miRNA-mRNA regulatory relationships in breast cancer with invariant causal prediction

20. Uncovering the roles of microRNAs/lncRNAs in characterising breast cancer subtypes and prognosis

21. pDriver: a novel method for unravelling personalized coding and miRNA cancer drivers

22. Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data

23. Extensive transcriptional responses are co-ordinated by microRNAs as revealed by Exon-Intron Split Analysis (EISA)

24. Large expert-curated database for benchmarking document similarity detection in biomedical literature search

25. Preface

26. Use of Haploid Model of Candida albicans to Uncover Mechanism of Action of a Novel Antifungal Agent

27. Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data.

28. Identifying miRNA sponge modules using biclustering and regulatory scores.

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