Publications by authors named "Cheng-Bing Huang"
Article Synopsis
- * The authors aimed to create a prediction model for essential genes in humans by analyzing data from human cancer cell lines and using multiple feature encoding methods to characterize gene sequences.
- * Their results demonstrated that fusing and optimizing features enhanced model performance, with the deep learning model achieving the best AUC of 0.860, indicating a more effective approach for identifying essential genes.
In biological organisms, metal ion-binding proteins participate in numerous metabolic activities and are closely associated with various diseases. To accurately predict whether a protein binds to metal ions and the type of metal ion-binding protein, this study proposed a classifier named MIBPred. The classifier incorporated advanced Word2Vec technology from the field of natural language processing to extract semantic features of the protein sequence language and combined them with position-specific score matrix (PSSM) features.
View Article and Find Full Text PDFRecently, attention mechanism and derived models have gained significant traction in drug development due to their outstanding performance and interpretability in handling complex data structures. This review offers an in-depth exploration of the principles underlying attention-based models and their advantages in drug discovery. We further elaborate on their applications in various aspects of drug development, from molecular screening and target binding to property prediction and molecule generation.
View Article and Find Full Text PDFHeparin-binding protein (HBP) is a cationic antibacterial protein derived from multinuclear neutrophils and an important biomarker of infectious diseases. The correct identification of HBP is of great significance to the study of infectious diseases. This work provides the first HBP recognition framework based on machine learning to accurately identify HBP.
View Article and Find Full Text PDFAlcohol dependence is an overall health-related challenge; however, the specific mechanisms underlying alcohol dependence remain unclear. Serine proteinase inhibitor A3 () plays crucial roles in multiple human diseases; however, its role in alcohol dependence clinical practice has not been confirmed. We screened Gene Expression Omnibus (GEO) expression profiles, and identified differentially expressed genes (DEGs).
View Article and Find Full Text PDFArticle Synopsis
- - The cause of Bipolar Disorder (BPD) is still not well understood, but studies indicate that certain signaling pathways may be involved in its development.
- - Research has shown that specific genetic variations in the adenylate cyclase gene could influence how patients respond to mood stabilizers and antidepressants.
- - This study focuses on the potential connection between polymorphisms in the ADCY-2 gene and BPD among the Chinese Han population.
[Ecological executive function profiles in depression patients before and after treatment].
Zhonghua Yi Xue Za Zhi
March 2013
Objective: To explore the ecological executive function profile in depression patients before and after antidepressants treatment and analyze the relationship of ecological executive function and depression symptoms and effect.
Methods: A total of 33 inpatients diagnosed as depression disorder according to ICD-10 completed the Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) and Hamilton Depression Scale (HAMD) before and after a 6-week antidepressant treatment.
Results: (1) After treatment, they yielded lower scores significantly on most subscales of BRIEF-A (t = 2.