49 results on '"Gayvert, Kaitlyn"'
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2. Evolutionary trajectory of SARS-CoV-2 genome shifts during widespread vaccination and emergence of Omicron variant
3. Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning
4. Author response: Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning
5. Broad Targeting Specificity during Bacterial Type III CRISPR-Cas Immunity Constrains Viral Escape
6. Differential modulation of allergic rhinitis nasal transcriptome by dupilumab and allergy immunotherapy.
7. FIGURE 1 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
8. Supplementary Figure 1 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
9. Supplementary Data Legends from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
10. Supplementary Table 1 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
11. FIGURE 5 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
12. FIGURE 3 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
13. Supplementary Figure 3 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
14. FIGURE 4 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
15. Supplementary Figure 2 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
16. FIGURE 2 from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
17. Data from The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
18. The Identification of CELSR3 and Other Potential Cell Surface Targets in Neuroendocrine Prostate Cancer
19. N-Myc Induces an EZH2-Mediated Transcriptional Program Driving Neuroendocrine Prostate Cancer
20. Drug-Induced Expression-Based Computational Repurposing of Small Molecules Affecting Transcription Factor Activity
21. A Bayesian machine learning approach for drug target identification using diverse data types
22. A Single Dose Of Fel d 1 Monoclonal Antibodies Regulates Molecular Signatures of Asthma In Nasal Mucosa Upon Cat Allergen Challenge In A Phase 2 Study
23. Blocking common γ chain cytokine signaling ameliorates T cell–mediated pathogenesis in disease models
24. Evaluation of Common Gamma Chain Cytokine Signaling Blockade with REGN7257, an Interleukin 2 Receptor Gamma (IL2RG) Monoclonal Antibody, on Immune Cell Populations in Monkey and Human
25. Machine learning analysis of a digital insole versus clinical standard gait assessments for digital endpoint development
26. Viral population genomics reveals host and infectivity impact on SARS-CoV-2 adaptive landscape
27. Highly Multiplexed Immunohistochemistry Can Predict Steroid Refractory Gastrointestinal (GI) Acute Gvhd at the Time of Endoscopy
28. A machine learning approach predicts essential genes and pharmacological targets in cancer
29. A Computational Drug Repositioning Approach for Targeting Oncogenic Transcription Factors
30. A Machine Learning Approach Predicts Tissue-Specific Drug Adverse Events
31. Abstract 5039: A data driven approach to predicting tissue-specific adverse events
32. Abstract 1563: A machine learning approach to predict platform specific gene essentiality in cancer
33. Rovalpituzumab tesirine (Rova-T) as a therapeutic agent for Neuroendocrine Prostate Cancer (NEPC).
34. A New Big-Data Paradigm for Target Identification and Drug Discovery
35. A Computational Approach for Identifying Synergistic Drug Combinations
36. A Data-Driven Approach to Predicting Successes and Failures of Clinical Trials
37. Abstract 887: N-Myc drives neuroendocrine prostate cancer
38. Abstract 3916: A “moneyball” approach to predicting clinical trial toxicity events
39. Abstract LB-106: Using a data-driven Bayesian approach to predict the targets of orphan small molecules and ways to overcome drug resistance
40. Abstract B142: A “moneyball” approach to predicting clinical trial failures and successes
41. Abstract LB-072: The N-Myc transcriptional program driving the neuroendocrine prostate cancer phenotype
42. Abstract 3688: Target identification for anticancer molecules using a Big Data approach
43. ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancers
44. Abstract 362: Computational drug repositioning identifies dexamethasone as potential ERG inhibitor
45. Predicting Cancer Prognosis Using Functional Genomics Data Sets
46. ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancers.
47. A COMPARISON OF COMPUTATIONAL EFFICIENCIES OF STOCHASTIC ALGORITHMS IN TERMS OF TWO INFECTION MODELS.
48. The IL‐4–IL‐4Rα axis modulates olfactory neuroimmune signaling to induce loss of smell.
49. Drug-Induced Expression-Based Computational Repurposing of Small Molecules Affecting Transcription Factor Activity.
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