A5018737487- Protein Degradation and Inhibitors
- Ubiquitin and proteasome pathways
- Monoclonal and Polyclonal Antibodies Research
- Click Chemistry and Applications
- Biotin and Related Studies
- Computational Drug Discovery Methods
- Protein purification and stability
- HIV Research and Treatment
- Genetics, Bioinformatics, and Biomedical Research
- Artificial Intelligence in Healthcare
- Sentiment Analysis and Opinion Mining
- Viral Infectious Diseases and Gene Expression in Insects
- Machine Learning in Healthcare
- Anomaly Detection Techniques and Applications
- Crime Patterns and Interventions
- Enzyme Structure and Function
- Misinformation and Its Impacts
- CAR-T cell therapy research
- AI in cancer detection
- Peptidase Inhibition and Analysis
- Cellular transport and secretion
- Protein Structure and Dynamics
University of California, San Diego
2020-2024
University of California, Berkeley
2023
Palo Alto University
2021
Abstract Understanding how small molecules bind to specific protein complexes in living cells is critical understanding their mechanism-of-action. Unbiased chemical biology strategies for direct readout of interactome remodelling by would provide advantages over target-focused approaches, including the ability detect previously unknown ligand targets and complexes. However, there are few current methods unbiased profiling molecule interactomes. To address this, we envisioned a technology...
Abstract Bifunctional molecules such as targeted protein degraders induce proximity to promote gain-of-function pharmacology. These powerful approaches have gained broad traction across academia and the pharmaceutical industry, leading an intensive focus on strategies that can accelerate their identification optimization. We others previously used chemical proteomics map degradable target space, these datasets been develop train multiparameter models extend degradability predictions...
Bifunctional molecules such as targeted protein degraders induce proximity to promote gain‐of‐function pharmacology. These powerful approaches have gained broad traction across academia and the pharmaceutical industry, leading an intensive focus on strategies that can accelerate their identification optimization. We others previously used chemical proteomics map degradable target space, these datasets been develop train multiparameter models extend degradability predictions proteome. In this...
Bifunctional molecules such as targeted protein degraders induce proximity to promote gain‐of‐function pharmacology. These powerful approaches have gained broad traction across academia and the pharmaceutical industry, leading an intensive focus on strategies that can accelerate their identification optimization. We others previously used chemical proteomics map degradable target space, these datasets been develop train multiparameter models extend degradability predictions proteome. In this...
Unbiased chemical biology strategies for direct readout of protein interactome remodelling by small molecules provide advantages over target-focused approaches, including the ability to detect previously unknown targets, and inclusion off-compete controls leading high-confidence identifications. We describe BioTAC system, a small-molecule guided proximity labelling platform, rapidly identify both complexed molecule binding proteins. The system overcomes limitation current supports...
Machine learning can be utilized to enhance proper police response Property Crime. However, many current predictive policing strategies unfairly target underprivileged racial demographics by training models with biased data. This is due in part the bias patterns prevalent policing, which are ultimately replicated machine models. In our study, we focus on city of Boston and investigate their publicly available Census Crime Incident datasets identify possibility create less racially for...
Nek9 is a member of the understudied Nek family dark kinases. Aberrant activation kinase signaling has been linked to poor keratinocyte differentiation phenotypes, and key driver nevus comedonicus, rare, localized form acne. also essential scaffolding roles; during mitosis non-catalytic C-terminal domain binds Nek6 Nek7, releasing them from an auto-inhibitory conformation, enabling proper mitotic progression. Finally, expression cancer proliferation. SiRNA mediated knock-down in panel cell...
There is literature on Machine Learning Sentiment Analysis (MLSA) during the COVID-19 pandemic, however, to best of our knowledge, there has been little no research investigating effectiveness different internet media sources for prediction population-level sentiment; Twitter currently most often used in MLSA research. This study conducts related various determine relative each mining public sentiment. The natural language processing achieved through a long short-term memory (LSTM) neural...
There has been previous work on predicting diabetes using machine learning models; however, the accuracies and recalls of prediction methods can be further improved. This study investigates a more accurate model that successfully predicts patient's stage based typical hospital data. Three online datasets (PIDD, UCIMLR, LMCH) are obtained preprocessed, five models (Random Forest, Logistic Regression, Decision Tree, XGBoost, Ensemble Soft Voting Classifiers) developed each dataset. Next,...
ADVERTISEMENT RETURN TO ISSUEViewpointNEXTAssembling a Robust Workflow for Characterizing Endogenous E3 Ligase SubstratesAndrew J. TaoAndrew TaoDepartment of Chemistry and Biochemistry, University California, San Diego, La Jolla, California 92093-0657, United StatesMore by Andrew Tao Fleur M. Ferguson*Fleur FergusonDepartment StatesSkaggs School Pharmacy Pharmaceutical Sciences, States*Email: [email protected]More Fergusonhttps://orcid.org/0000-0003-4091-7617Cite this: Biochemistry 2021, 60,...