Li Chuin Chong

Doctoral researcher (TWINCORE GmbH) & Ph.D. candidate (MHH BIOMEDAS) under COVIPA consortium | Financial Comm of ISCBSC

Hannover, Lower Saxony, Germany

About

An enthusiastic virologist who started out as a classically trained wet-lab scientist, then soon transited to the field of bioinformatics and data science in biology after realizing the importance of translating the data in biology/biomedical fields into an informative insight. Generally, my research interest lies in the study of pathogen-associated diseases, in particular that of viral origin, which contributes to the global disease burden. I am interested in better understanding how vaccines/drugs work towards a more effective prevention/clearance of viral diseases, and how to overcome diseases with no or lack of an effective prophylactic or therapeutic intervention. High throughput technology-enabled omics disciplines, such as genomics and proteomics, are playing an important role in the new phase of preventive medicine research. As such, the integration of biomedical knowledge with bioinformatics/data science skills is the general approach of my intended research direction. More about my research projects:- ResearchGate: https://www.researchgate.net/profile/Li_Chong25 Google Scholar: http://bit.ly/lichuinchong GitHub Profile: https://github.com/ChongLC Personal Portfolio: https://chonglc.github.io/

Experience

  • Doctoral Researcher at TWINCORE GmbH
    Apr 2022 - Present · 4 yrs 3 mos

    Research Theme: viral diversity, computational virology

  • Visiting Trainee at DKFZ German Cancer Research Center
    Oct 2023 - Nov 2023 · 2 mos

  • Research Intern at Mahidol University
    May 2020 - Dec 2021 · 1 yr 8 mos

    Research Theme: machine learning, chemical space analysis, SARS-CoV-2 Being introduced to machine learning through a project, entitled “Exploring the chemical space of SARS-CoV-2 drugs via machine learning” - Curated structural proteome data from ChEMBL and others - Performed exploratory data analysis on the curated data using python (pandas/numpy) - Learned machine learning, such as random forest (mainly) and others, to predict the class of the structure data potency

  • International Visiting Researcher at Bezmialem Vakif University Life Sciences & Biotechnology Institute
    Mar 2021 - Sep 2021 · 7 mos

    Research Theme: sequence diversity, viral dynamics, epitope prediction, vaccine target discovery Mentored a few students who involved in two projects: (i) a large-scale viral project, involving multiple viruses (e.g. LASV, CHIKV, ZIKV, IAV H7N9, DENV), with the goal of understanding the dynamics of viral sequence change. (ii) an immunoinformatics project on SARS-CoV-2

  • Assistant Executive Officer at Perdana University
    Dec 2020 - Mar 2021 · 4 mos