A5101509302- Software Engineering Research
- Advanced Malware Detection Techniques
- Monoclonal and Polyclonal Antibodies Research
- Topic Modeling
- Software Engineering Techniques and Practices
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Advanced Measurement and Detection Methods
- Traumatic Brain Injury and Neurovascular Disturbances
- Software Testing and Debugging Techniques
- Optical Systems and Laser Technology
- Inflammatory mediators and NSAID effects
- Gut microbiota and health
- Sensor Technology and Measurement Systems
- Blockchain Technology Applications and Security
- Neural Networks and Applications
- Viral Infectious Diseases and Gene Expression in Insects
- Advanced Glycation End Products research
- Genetics, Bioinformatics, and Biomedical Research
- S100 Proteins and Annexins
- Cervical Cancer and HPV Research
- Web Data Mining and Analysis
- AI in cancer detection
- Security and Verification in Computing
- Cancer Genomics and Diagnostics
Macau University of Science and Technology
2022-2025
Sutro Biopharma (United States)
2023-2024
University of Macau
2024
Cipher Gene (China)
2018-2021
North University of China
2010
Background: Evaluating the risk of metastasis and recurrence a cervical cancer patient is critical for appropriate adjuvant therapy. However, current assessment models usually involve testing tens to thousands genes from patients’ tissue samples, which expensive timeconsuming. Therefore, computer-aided diagnosis prognosis prediction based on Hematoxylin Eosin (H&E) pathological images have received much attention recently. Objective: The whether patients will can support accurate...
A growing number of clinical observations have indicated that microbes are involved in a variety important human diseases. It is obvious in-depth investigation correlations between and diseases will benefit the prevention, early diagnosis prognosis greatly. Hence, this paper, based on known microbe-disease associations, prediction model called NBLPIHMDA was proposed to infer potential associations. Specifically, two kinds networks including disease similarity network microbe were first...
With the emergence of smartphones, Android has become a widely used mobile operating system. However, it is vulnerable when encountering various types attacks. Every day, new malware threatens security users’ devices and private data. Many methods have been proposed to classify malicious applications, utilizing static or dynamic analysis for classification. previous still suffer from unsatisfactory performance due two challenges. First, they are unable address imbalanced data distribution...
Artificial intelligence (AI) for software engineering (SE) tasks has recently achieved promising performance. In this article, we investigate to what extent the pre-trained language model truly understands those SE such as code search, summarization, etc. We conduct a comprehensive empirical study on board set of AI (AI4SE) by feeding them with variant inputs: 1) various masking rates and 2) sufficient input subset method. Then, trained models are evaluated different tasks, including...
Code clone detection plays a critical role in the field of software engineering. To achieve this goal, developers are required to have rich development experience for finding "functional" code. However, is unfriendly novice developers. Although many approaches were proposed automatically detect code clones, results not satisfactory. A major reason that it difficult extract syntax and semantic information from source resolve problem, article, we develop novel graph representation approach...
Several studies have reported a significant role of high mobility group box protein 1 (HMGB1) in lung cancer. Nevertheless, there is lack knowledge regarding the expression HMGB1 and its correlation with clinicopathological features In addition, potential molecular mechanisms underlying cancer are still unknown. We therefore investigated prognostic significance as well development progression tumor tissues cohort correlated features. Moreover, cell migration invasion were significantly...
The XpressCF+® cell-free protein synthesis system is a robust platform for the production of non-natural amino acids containing antibodies, which enable site-specific conjugation homogeneous antibody drug conjugates (ADCs) via click chemistry. Here, we present and scalable means achieving 50-100% increase in IgG titers by combining high productivity cell-based with unique ability reactions to produce correctly folded assembled IgGs multiple at defined positions. This hybrid technology...
Background: Identification of genomic markers using NGS (next-generation sequencing) technology would be valuable for guiding precision medicine treatments pancreatic cancers. Traditional somatic mutation methods require both tumor and matched non-tumor samples. However, only samples are available mostly, especially in retrospective studies. In this study, we tried to analyze the associations between clinical features oncogenic mutations genome-wide tumor-only Methods: Fifty-four derived...
With the development and application of next-generation sequencing (NGS) target capture technology, demand for an effective analysis method to accurately detect gene fusion from high-throughput data is growing. Hence, we developed a novel analyzing called single-end (SEGF) by starting with DNA-seq data. This approach takes raw as input, integrates commonly used alignment basic local search tool (BLAST) short oligonucleotide package (SOAP) stringent passing filters achieve successful...
Therapeutic bioconjugates are emerging as an essential tool to combat human disease. Site-specific conjugation technologies widely recognized the optimal approach for producing homogeneous drug products. Non-natural amino acid (nnAA) incorporation allows introduction of bioconjugation handles at genetically defined locations. Escherichia coli (E. coli) is a facile host therapeutic nnAA protein synthesis because it can stably replicate plasmids encoding genes product and incorporation. Here,...
Artificial intelligence (AI) for software engineering (SE) tasks has recently achieved promising performance. In this paper, we investigate to what extent the pre-trained language model truly understands those SE such as code search, summarization, etc. We conduct a comprehensive empirical study on board set of AI (AI4SE) by feeding them with variant inputs: 1) various masking rates and 2) sufficient input subset method. Then, trained models are evaluated different tasks, including duplicate...