A5089477818- Computational Drug Discovery Methods
- Advanced Sensor and Control Systems
- Advanced Algorithms and Applications
- Bioinformatics and Genomic Networks
- Receptor Mechanisms and Signaling
- Cell Image Analysis Techniques
- Industrial Technology and Control Systems
- COVID-19 and Mental Health
- Natural Products and Biological Research
- Microplastics and Plastic Pollution
- Acne and Rosacea Treatments and Effects
- Atherosclerosis and Cardiovascular Diseases
- Pharmacogenetics and Drug Metabolism
- Tribology and Lubrication Engineering
- Wireless Sensor Networks and IoT
- Cooperative Communication and Network Coding
- Iterative Learning Control Systems
- Adhesion, Friction, and Surface Interactions
- Recycling and Waste Management Techniques
- Gut microbiota and health
- Robotic Path Planning Algorithms
- Protein Degradation and Inhibitors
- Industrial Automation and Control Systems
- Pharmacological Effects of Natural Compounds
- Second Language Learning and Teaching
Hunter College
2020-2021
City University of New York
2020-2021
Peking University
2021
Jiangsu University
2016-2017
Xidian University
2016
Guizhou University
2003-2007
Yan'an University
2007
Shihezi University
2007
Changsha University of Science and Technology
2006
Yangon University of Economics
2003
Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the experimental investigation all to become costly time-consuming. Computational techniques can efficiency combination screening. Despite recent advances applying machine learning synergistic prediction, several challenges remain. First, performance existing methods is suboptimal. There still much...
Abstract Octacosanol, as the major active policosanol, has attracted much attention due to potential beneficial effects for human health. However, free octacosanol a high melting point, poor oil solubility and low bioavailability, which greatly restricts its practical application. In this study, we report highly efficient method an ionic liquids (IL)‐catalyzed synthesis of ester by direct esterification with linoleic acid. The synthesized product was purified, subsequently characterized...
In order to avoid obstacles efficiently and reach the goal quickly under multi-obstacle environment, we studied path planning question of autonomous mobile robot (AMR) based on ultrasonic sensor information by combining genetic algorithm with fuzzy logic control. Firstly, principles configuration sensors were introduced. Secondly, dynamic model kinetic equations AMR constructed. Then, according number obstacles, avoiding behavior rules presented, moreover, obstacle-selecting avoidance flow...
The present work investigates the properties of self-made magnetic filler from plastic waste bottle and explores a new technology approach resource utilization. was prepared by air plasma modification loading ferrite on strip bottle. surface were characterized Atomic Force Microscope (AFM), contact angle system Fourier Transform Infrared (FTIR). AFM images original modified showed that low-temperature treatment markedly increased roughness strip. mean (Ra) rose 1.116 to 5.024 nm. FTIR...
Abstract Motivation Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. With the fast-growing number of anti-cancer drugs, experimental investigation all is costly time-consuming. Computational techniques can efficiency combination screening. Despite recent advances applying machine learning to synergistic prediction, several challenges remain. First, performance existing methods suboptimal. There still...
Abstract Accurate and robust prediction of patient-specific responses to drug treatments is critical for development personalized medicine. However, patient data are often too scarce train a generalized machine learning model. Although many methods have been developed utilize cell line data, few them can reliably predict individual clinical new drugs due distribution shift confounding factors. We develop novel Context-aware Deconfounding Autoencoder (CODE-AE) that extract common biological...
Objective To indentify the cognitive status of Chinese patients to acne and influencing factors theirs＇ status, so as provide solid evidences for prevention treatment acne. Methods A self-designed questionnaire was made conduct this survey 16, 156 patients, who seeked in dermatological departments from 112 hospitals China. The consisted several parts, including general patients＇ cognition occurrence, development risk acne, whether first choice seeking at hospital when had condition...
Abstract An increasing body of evidence suggests that microbes are not only strongly associated with many human diseases but also responsible for the efficacy, resistance, and toxicity drugs. Small-molecule drugs which can precisely fine-tune microbial ecosystem on basis individual patients may revolutionize biomedicine. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional “one-drug-one-target-one-disease” process. It is often insufficient...
Abstract Accurate and robust prediction of patient-specific responses to drug treatments is critical for development personalized medicine. However, patient data are often too scarce train a generalized machine learning model. Although many methods have been developed utilize cell line data, few them can reliably predict individual clinical new drugs due distribution shift confounding factors. We novel Context-aware Deconfounding Autoencoder (CODE-AE) that extract intrinsic biological...