BMEG3102 Bioinformatics (2021-2022 Term 2)

Course information

The goal of this course is to introduce the basic concepts in bioinformatics. Topics to be covered include introduction to bioinformatics, reviews of molecular biology and genetics, biomedical data types and databases, sequence alignment and searching methods, mutation models and molecular phylogenetics, molecular structures, clinical bioinformatics for genetic diseases diagnosis. On the theoretical side, students are expected to learn the relevant knowledge in computer science, biology and mathematics from lectures and tutorials. On the practical side, students are given assignments and tutorials to get hands-on experience in locating, studying and using developed tools to apply the learned concepts in performing standard analytical tasks on biomedical data.

Class time and venue

Lectures:

Wednesdays      10:30AM - 11:15AM (SC L3)
Thursdays          11:30AM - 01:15PM (MMW 710)

Tutorials:

Wednesdays      11:30AM - 12:15PM (SC L3)

All lectures and tutorials now use online teaching.

Piazza

For discussions, questions and sharings:
link: https://piazza.com/cuhk.edu.hk/spring2022/bmeg3102

Assessments:

Assignments:                              45%
Topic presentation & report:        15%
Final examination:                       35%
Class participation:                       5%

Tentative class schedule

Presentation topics

1. Protein folding prediction with AI
Highly accurate protein structure prediction with AlphaFold
2. COVID and bioinformatics
AIs that read sentences are now catching coronavirus mutations
3. Functional genomics data privacy
Functional genomics data: privacy risk assessment and technological mitigation
4. Protein function prediction
Structure-based protein function prediction using graph convolutional networks
5. Cancer diagnosis
The evolutionary history of 2,658 cancers
6. Discover the genetic patterns of complex diseases
Repeat DNA expands our understanding of autism spectrum disorder
7. The next wave after single-cell analysis: spatial single-cell transcriptomics
Method of the Year, spatially resolved transcriptomics
8. Genome-Based drug repurposing
Opportunities for drug repositioning from phenome-wide association studies
9. Transcription factor binding sites prediction
Deep neural networks identify sequence context features predictive of transcription factor binding
10. Methods to assess off-target CRISPR edits
Inactivation of porcine endogenous retrovirus in pigs using CRISPR-Cas9
11. Sequence assembly
Chromosome-scale, haplotype-resolved assembly of human genomes
12. Multimodal Single-Cell Data Integration
Computational principles and challenges in single-cell data integration

Reference materials

- Bioinformatics Micro-modules, YouTube channel, by Prof. Kevin Yip.
- Fundamental Concepts of Bioinformatics, by Dan E. Krane, Michael L. Raymer and Benjamin Cummings, Pearson Education, 2003.
- Algorithms in Bioinformatics: A Practical Introduction, by Wing-Kin Sung, Chapman & Hall, 2009. [with free online materials]