biodatascience

This is the web resource for NTU's Bio-Data Science and Education Laboratory

View the Project on GitHub gohwils/biodatascience

Welcome to the BioData Science and Education Laboratory

We are a research group comprised of biodata scientists, computational biologists and education technologists in the School of Biological Sciences, Nanyang Technological University.

Current projects

Our research activities may be broadly divided into two areas: biodata science and education technology.

Biodata science is an exciting new area where the associative technologies associated with data science and relevant thinking skills are applied onto biological and health-related problems.

These may include how to resolve batch effect problems when effecting large-scale data mergers, improving study reproducibility, and understanding how choice of normalization method impacts downstream data modeling. We are also very interested in understanding how heterogeneity and data holes impacts outcome of analysis, especially in how it affects our interpretation of the underlying biological system.

Our interest in Education technology (EdTech) pertains to the use of data analytics for analyzing student performance and also the development of software for facilitating learning. In particular, we are interested in how we may leverage on big data and machine learning to unravel indicators of human-based deep learning. Instead of fielding our work on typical classroom-type settings, our interest is in combining EdTech with high-impact practices in teaching and learning, where deep learning is more likely to take place. Currently, we focus our research on NTU’s unique Deeper Experiential Engagement Project (DEEP), a large-scale pilot experiential learning project spread across different colleges.

Link out below to find out more about each area and our work/contributions.

BioData Science and Computational Biology

  1. Dealing with confounders in omics analysis
  2. Enabling more sophisticated proteomic profile analysis
  3. Resolving the missing protein problem using meaningful context
  4. Understanding the cost of batch effects in biological big data analysis
  5. Developing graph literacy skills
  6. How to improve upon weak validation practices in current machine learning

Education Technology

  1. Not feeling it — How does sentiment and motivation affect academic performance?
  2. Using machine-based deep learning to uncover the signs of human-based deep learning
  3. High-impact pedagogical practices

Publications

Check out our latest works here.

Our people (Meet the team)

Research staff

  1. Wilson Wen Bin Goh (PI)
  2. Anna Chew (Project Officer)

Research students

  1. Samuel Tan (PhD)
  2. Zhou Longjian (PhD)
  3. Kong Weijia (PhD)
  4. Joan Jong (BSc)
  5. Wee Yuhui (BSc)
  6. Jordan Kho (BSc)
  7. Lejia Lin (BSc)
  8. Lirong Wang (BSc)
  9. Bertrand Wang Jernhan (BSc)
  10. Wenxuan Kong (BSc)
  11. Priscila Sun Yunqian (BSc)
  12. Tng Jia Wei Teddy (BSc)
  13. Lee Yue Xin (BSc)

Alumni

  1. Felicia Ngan, BSc
  2. Chon Hui Min, BSc
  3. Lu Tianyi, BSc
  4. Wei Wang, MSc
  5. Ho Sung Yang (Research Assistant; Data Scientist)
  6. Justin Ng (Research Fellow)
  7. Zhao Yaxing (MSc)
  8. Kimberly Phua (BSc)
  9. Nicole Kan (BSc)
  10. Bernard Koh
  11. Kaijin Soh
  12. Fu Ting Ting
  13. Toh Shergi
  14. Leon Yao Jinchi
  15. Zenghao Lim (Research Assistant)
  16. Damien Chua (BSc)

Courses and training programmes (Taught by us)

Undergraduate courses

Graduate courses

Workshops and hackathons

Masters of Science in Biomedical Data Science

Collaborations

We are highly collaborative, and work with a multitude of experts in and out of Singapore. These include:

  1. Limsoon Wong
  2. Jimmy Lee
  3. Andrew Tan
  4. Guillaume Thibault
  5. Tan Suet Mien
  6. Tiannan Guo
  7. Nikola Kasabov
  8. Lim Kah Leong

Contact or join us

We are located at level 3 north wing of the School of Biological Sciences (60 Nanyang Drive, Singapore 637551).

We are open to consultative and development work with industrial, educational and business partners. Do drop us an email at biodatascienceandeducation@e.ntu.edu.sg.

We are always on the lookout for exciting new talent to join the team: For full-time staff, we have vacancies for research fellows, associates and assistants. Do check out the NTU jobs portal for ads or check with us directly.

For undergraduate students, we do post available projects on the relevant project portals (e.g. URECA, FYP or CN Yang). You may also approach us directly to discuss customized projects (preferred). Do note that you are required to have certain proficiency in programming skills, mathematics, statistics and algorithms.

For prospective graduate students (MSc or PhD), please write in directly to myself or to Limsoon.