625 results on '"de Ridder, Jeroen"'
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2. Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes
3. The genome-wide mutational consequences of DNA hypomethylation
4. Predicting response to enzalutamide and abiraterone in metastatic prostate cancer using whole-omics machine learning
5. Comprehensive benchmark and architectural analysis of deep learning models for nanopore sequencing basecalling
6. WEE1 inhibitor adavosertib in combination with carboplatin in advanced TP53 mutated ovarian cancer: A biomarker-enriched phase II study
7. A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns
8. Multi-country metabolic signature discovery for chicken health classification
9. Direct detection of 8-oxo-dG using nanopore sequencing
10. How to trust a scientist
11. Author Correction: A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns
12. Integration of multiple lineage measurements from the same cell reconstructs parallel tumor evolution
13. A multi-stage approach of simulating turbulence-induced vibrations in a wire-wrapped tube bundle for fretting wear prediction
14. What's so bad about misinformation?
15. Evidence of survival bias in the association between APOE-Є4 and age at ischemic stroke onset.
16. The Online Battlefield: How Conflict Frames in Political Advertisements Affect Political Participation in a Multiparty Context.
17. Mutational synergy with CREBBP loss in lymphomagenesis identified through forward insertional mutagenesis in a new DLBCL mouse model
18. Nanopore-based consensus sequencing enables accurate multimodal tumor cell-free DNA profiling
19. Online and Offline Battles : Usage of Different Political Conflict Frames
20. Group belief reconceived
21. Is Fake News Old News?
22. Evidence of survival bias in the association betweenAPOE-Є4and age of ischemic stroke onset
23. INNV-36. ULTRA-FAST DEEP-LEARNED CNS TUMOR CLASSIFICATION USING NANOPORE-SEQUENCING DURING SURGERY
24. Editorial
25. Accurate detection of circulating tumor DNA using nanopore consensus sequencing
26. Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning
27. Introduction to the Philosophy of Creation Order, with Special Emphasis on the Philosophy of Herman Dooyeweerd
28. Alternate approach to stroke phenotyping identifies a genetic risk locus for small vessel stroke
29. Multi-contact 4C: long-molecule sequencing of complex proximity ligation products to uncover local cooperative and competitive chromatin topologies
30. Common Sense and Ontological Commitment
31. Kunnen goed geïnformeerde burgers wel betrokken burgers zijn?
32. Editors’ Note
33. Introduction
34. Numerical investigation of large-scale vortices in an array of cylinders in axial flow
35. Molecular heterogeneity and early metastatic clone selection in testicular germ cell cancer development
36. Intestinal LKB1 loss drives a pre-malignant program along the serrated cancer pathway
37. Author Correction: Accurate detection of circulating tumor DNA using nanopore consensus sequencing
38. The epistemology of groups. By JenniferLackey, New York: Oxford University Press. 2021. pp. x + 200. £61.00 (hbk). ISBN: 9780199656608
39. Predicting modal characteristics of a cluster of cylinders in axial flow: From potential flow solutions to coupled CFD–CSM calculations
40. MetaboShiny: interactive analysis and metabolite annotation of mass spectrometry-based metabolomics data
41. How Many Scientists Does It Take to Have Knowledge?
42. Enhancer hubs and loop collisions identified from single-allele topologies
43. Supplementary Data from Gene Networks Constructed Through Simulated Treatment Learning can Predict Proteasome Inhibitor Benefit in Multiple Myeloma
44. Fold Assignment from Gene Networks Constructed Through Simulated Treatment Learning can Predict Proteasome Inhibitor Benefit in Multiple Myeloma
45. Supplementary Table 8 from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes
46. Data from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes
47. Supplementary Table 10 from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes
48. Supplementary Figure 1B from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes
49. Supplementary Table 6 from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes
50. Supplementary Table 4 from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes
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