479 results on '"Davis, Melissa J."'
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2. vissE: a versatile tool to identify and visualise higher-order molecular phenotypes from functional enrichment analysis
3. IKAROS and AIOLOS directly regulate AP-1 transcriptional complexes and are essential for NK cell development
4. Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT
5. Spatial omics techniques and data analysis for cancer immunotherapy applications
6. Spatial transcriptomic analysis of Sonic hedgehog medulloblastoma identifies that the loss of heterogeneity and promotion of differentiation underlies the response to CDK4/6 inhibition
7. Discovery of a highly potent, selective, orally bioavailable inhibitor of KAT6A/B histone acetyltransferases with efficacy against KAT6A-high ER+ breast cancer
8. MsImpute: Estimation of Missing Peptide Intensity Data in Label-Free Quantitative Mass Spectrometry
9. Implementation of DNA Methylation Array Profiling in Pediatric Central Nervous System Tumors: The AIM BRAIN Project: An Australian and New Zealand Children's Hematology and Oncology Group Study
10. Loss of TAF8 causes TFIID dysfunction and p53-mediated apoptotic neuronal cell death
11. SFPQ-ABL1 and BCR-ABL1 use different signaling networks to drive B-cell acute lymphoblastic leukemia
12. hoodscanR: profiling single-cell neighborhoods in spatial transcriptomics data
13. ERG and c-MYC regulate a critical gene network in BCR::ABL1-driven B cell acute lymphoblastic leukemia
14. In situ single-cell profiling sheds light on IFI27 localisation during SARS-CoV-2 infection
15. Blockade of the co-inhibitory molecule PD-1 unleashes ILC2-dependent antitumor immunity in melanoma
16. Harnessing Natural Killer Immunity in Metastatic SCLC
17. standR: spatial transcriptomic analysis for GeoMx DSP data
18. Dissection of the bone marrow microenvironment in hairy cell leukaemia identifies prognostic tumour and immune related biomarkers
19. Systems pharmacogenomics identifies novel targets and clinically actionable therapeutics for medulloblastoma
20. Elp2 mutations perturb the epitranscriptome and lead to a complex neurodevelopmental phenotype
21. PRMT1-mediated H4R3me2a recruits SMARCA4 to promote colorectal cancer progression by enhancing EGFR signaling
22. Correction to: PRMT1-mediated H4R3me2a recruits SMARCA4 to promote colorectal cancer progression by enhancing EGFR signaling
23. Supervised, semi-supervised and unsupervised inference of gene regulatory networks
24. Spatial proteomics identifies a spectrum of immune dysregulation in acquired bone marrow failure syndromes
25. Identification of cell types, states and programs by learning gene set representations
26. Single‐cell RNA sequencing captures patient‐level heterogeneity and associated molecular phenotypes in breast cancer pleural effusions
27. Basonuclin-2 regulates extracellular matrix production and degradation
28. vissE.cloud: a webserver to visualise higher order molecular phenotypes from enrichment analysis
29. An Erg-driven transcriptional program controls B cell lymphopoiesis
30. Differential co-expression-based detection of conditional relationships in transcriptional data: comparative analysis and application to breast cancer
31. standR: a Bioconductor package for analysing transcriptomic Nanostring GeoMx DSP data
32. Data from A Gene Signature Predicting Natural Killer Cell Infiltration and Improved Survival in Melanoma Patients
33. Supplementary Figures 1-9 and Table 2 from A Gene Signature Predicting Natural Killer Cell Infiltration and Improved Survival in Melanoma Patients
34. Supplementary Figure from TGFβ and CIS Inhibition Overcomes NK-cell Suppression to Restore Antitumor Immunity
35. Supplementary Table 1 from A Gene Signature Predicting Natural Killer Cell Infiltration and Improved Survival in Melanoma Patients
36. Data from TGFβ and CIS Inhibition Overcomes NK-cell Suppression to Restore Antitumor Immunity
37. Supplementary Methods from A Transcriptional Program for Detecting TGFβ-Induced EMT in Cancer
38. Data from SOX9 Defines Distinct Populations of Cells in SHH Medulloblastoma but Is Not Required for Math1-Driven Tumor Formation
39. Supplementary Figure 1 from SOX9 Defines Distinct Populations of Cells in SHH Medulloblastoma but Is Not Required for Math1-Driven Tumor Formation
40. Data from A Transcriptional Program for Detecting TGFβ-Induced EMT in Cancer
41. Supplementary Table 2 from SOX9 Defines Distinct Populations of Cells in SHH Medulloblastoma but Is Not Required for Math1-Driven Tumor Formation
42. Supplementary Table 1 from SOX9 Defines Distinct Populations of Cells in SHH Medulloblastoma but Is Not Required for Math1-Driven Tumor Formation
43. Supplementary Table 3 from SOX9 Defines Distinct Populations of Cells in SHH Medulloblastoma but Is Not Required for Math1-Driven Tumor Formation
44. Supplementary Results from A Transcriptional Program for Detecting TGFβ-Induced EMT in Cancer
45. Supplementary Tables from A Transcriptional Program for Detecting TGFβ-Induced EMT in Cancer
46. Supplementary Figure 3 from SOX9 Defines Distinct Populations of Cells in SHH Medulloblastoma but Is Not Required for Math1-Driven Tumor Formation
47. Supplementary Figure 2 from SOX9 Defines Distinct Populations of Cells in SHH Medulloblastoma but Is Not Required for Math1-Driven Tumor Formation
48. Supplementary Figure 4 from SOX9 Defines Distinct Populations of Cells in SHH Medulloblastoma but Is Not Required for Math1-Driven Tumor Formation
49. Supplementary Figure legends from Inhibition of CDK4/6 by Palbociclib Significantly Extends Survival in Medulloblastoma Patient-Derived Xenograft Mouse Models
50. Data from Tight Junction Protein Claudin-2 Promotes Self-Renewal of Human Colorectal Cancer Stem-like Cells
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