26 citations · 55 across the 10 of their papers we have counts for
12 papers
Extrinsic Principal Component Analysis
Ka Chun Wong, Vic Patrangenaru, Robert L. Paige +1
One develops a fast computational methodology for principal component analysis on manifolds. Instead of estimating intrinsic principal components on an object space with a Riemanni…
DiffDTM: A conditional structure-free framework for bioactive molecules generation targeted for dual proteins
Lei Huang, Zheng Yuan, Huihui Yan +9
Advances in deep generative models shed light on de novo molecule generation with desired properties. However, molecule generation targeted for dual protein targets still faces for…
MDM: Molecular Diffusion Model for 3D Molecule Generation
Lei Huang, Hengtong Zhang, Tingyang Xu +1
Molecule generation, especially generating 3D molecular geometries from scratch (i.e., 3D \textit{de novo} generation), has become a fundamental task in drug designs. Existing diff…
A Self-adaptive Weighted Differential Evolution Approach for Large-scale Feature Selection
Xubin Wang, Yunhe Wang, Ka-Chun Wong +1
Recently, many evolutionary computation methods have been developed to solve the feature selection problem. However, the studies focused mainly on small-scale issues, resulting in…
EGFI: Drug-Drug Interaction Extraction and Generation with Fusion of Enriched Entity and Sentence Information
Lei Huang, Jiecong Lin, Xiangtao Li +2
The rapid growth in literature accumulates diverse and yet comprehensive biomedical knowledge hidden to be mined such as drug interactions. However, it is difficult to extract the…
Review of Single-cell RNA-seq Data Clustering for Cell Type Identification and Characterization
Shixiong Zhang, Xiangtao Li, Qiuzhen Lin +1
In recent years, the advances in single-cell RNA-seq techniques have enabled us to perform large-scale transcriptomic profiling at single-cell resolution in a high-throughput manne…
Context awareness and embedding for biomedical event extraction
Shankai Yan, Ka-Chun Wong
Motivation: Biomedical event detection is fundamental for information extraction in molecular biology and biomedical research. The detected events form the central basis for compre…
Big Data Challenges in Genome Informatics
Ka-Chun Wong
In recent years, we have witnessed a dramatic data explosion in genomics, thanks to the improvement in sequencing technologies and the drastically decreasing costs. We are entering…
A Short Survey on Data Clustering Algorithms
Ka-Chun Wong
With rapidly increasing data, clustering algorithms are important tools for data analytics in modern research. They have been successfully applied to a wide range of domains; for i…
Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics: Evolutionary Algorithms for Bioinformatics
Ka-Chun Wong
Since genetic algorithm was proposed by John Holland (Holland J. H., 1975) in the early 1970s, the study of evolutionary algorithm has emerged as a popular research field (Civiciog…
Unsupervised Learning in Genome Informatics
Ka-Chun Wong, Yue Li, Zhaolei Zhang
With different genomes available, unsupervised learning algorithms are essential in learning genome-wide biological insights. Especially, the functional characterization of differe…
Evolutionary Multimodal Optimization: A Short Survey
Ka-Chun Wong
Real world problems always have different multiple solutions. For instance, optical engineers need to tune the recording parameters to get as many optimal solutions as possible for…