Beth Bioinformatics

Innovating Bioinformatics Solutions to Empower Novel Vaccine Development

Solving Design & Decision-making Problems

Bioinformatics and computational biology provides unique strategic advantages to vaccine development in ways conventional approaches could not.

Whether it is designing effective antigens for mutating viruses or personalized vaccines, informing product planning and clinical trial to mitigate risks and costs, or directly enhancing vaccine performance such as immunogenicity and expression through our new codon optimization technology, BethBio can be your reliable partner at every stage of vaccine development.

Learn more about our solutions

BETH Solutions

Virus Evolution Prediction

Vaccine Effectiveness Estimation

PCO Codon Optimization

Epitope Screening & Antigen Design

Human Omics-data Analytics

Our Team

Beth Bioinformatics is founded and led by current professors at the Chinese University of Hong Kong.

Young researchers and experienced scientists from multi-disciplinary backgrounds such as biostatistics, computer science, and virology all work together to develop new methods and generate insights for innovative ways to solve complex problems, before rigorously examining and verifying our technologies.

This is how BethBio delivers reliable, versatile and effective solutions to fulfill our clients' different needs in vaccine development.

Latest News

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Publications

Interaction-based feature selection and classification for high-dimensional biological data

Wang MH, Lo SH, Zheng T, Hu I. Bioinformatics. 2012 Nov 1;28(21):2834-42.

Predictive evolutionary modelling for influenza virus by site-based dynamics of mutation

Lou J, Liang W, Cao L, Hu I, Zhao S, Chen Z, Chan RW, Cheung PPH, Zheng H, Liu C, Li Q, Chong MKC, Zhang Y, Yeoh EK, Chan PKY, Zee BCY, Mok CKP, Wang MH. Nature Communications. 2024 Mar 21;15(1):2546.

A Prism Vote Method for Individualized Risk Prediction of Traits in Genotype Data of Multi-population

Xia X, Zhang Y, Sun R, Wei Y, Li Q, Chong MKC, Wu WKK, Zee BCY, Tang H, Wang MH. PLoS Genetics. 2022 Oct 27;18(10):e1010443.

Rapid evaluation of COVID-19 vaccine effectiveness against symptomatic infection with SARS-CoV-2 variants by analysis of genetic distance

Cao L, Lou J, Chan SY, Zheng H, Liu C, Zhao S, Li Q, Mok KP, Chan SY, Chan RWY, Chong MKC, Wu WKK, Chen Z, Wong ELY, Chan PKY, Zee BCY, Yeoh EK, Wang MH. Nature Medicine. 2022 Jun 16:1-8.

Characterization of key amino acid substitutions and dynamics of the influenza virus H3N2 hemagglutinin

Wang MH, Lou J, Cao L, Zhao S, Chan RW, Chan PK, Chan MC, Chong MK, Wu WK, Wei Y, Zhang H, Zee BC, Yeoh EK. Journal of Infection. 2021 Dec;83(6):671-677.

In silico prediction of influenza vaccine effectiveness by sequence analysis

Cao L, Lou J, Zhao S, Chan RW, Chan M, Wu WK, Chong MK, Zee BC, Yeoh EK, Wong SY, Chan PK, Wang MH. Vaccine. 2021 Feb 12;39(7):1030-4.

A Zoom-Focus algorithm (ZFA) to locate the optimal testing region for rare variant association tests

Wang MH, Weng H, Sun R, Lee J, Wu WK, Chong KC, Zee BC. Bioinformatics. 2017 Aug 1;33(15):2330-6.

A fast and powerful W-test for pairwise epistasis testing

Wang MH, Sun R, Guo J, Weng H, Lee J, Hu I, Sham PC, Zee BC. Nucleic acids research. 2016 Jul 8;44(12):e115-.

Interaction-based feature selection and classification for high-dimensional biological data

Wang MH, Lo SH, Zheng T, Hu I. Bioinformatics. 2012 Nov 1;28(21):2834-42.

Predictive evolutionary modelling for influenza virus by site-based dynamics of mutation

Lou J, Liang W, Cao L, Hu I, Zhao S, Chen Z, Chan RW, Cheung PPH, Zheng H, Liu C, Li Q, Chong MKC, Zhang Y, Yeoh EK, Chan PKY, Zee BCY, Mok CKP, Wang MH. Nature Communications. 2024 Mar 21;15(1):2546.