BMEG3102 Bioinformatics (2024-2025 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 (MMW 702)
Thursdays          11:30AM - 01:15PM (MMW 702)

Tutorials:

Wednesdays      11:30AM - 12:15PM (MMW 702)

Piazza

For discussions, questions and sharings:
link: https://piazza.com/cuhk.edu.hk/spring2025/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
Improved protein structure prediction using potentials from deep learning
After AlphaFold: protein-folding contest seeks next big breakthrough
Accurate structure prediction of biomolecular interactions with AlphaFold 3
2. Drug Design
Leveraging molecular structure and bioactivity with chemical language models for de novo drug design
Accurate prediction of molecular properties and drug targets using a self-supervised image representation learning framework
Comprehensive assessment of deep generative architectures for de novo drug design
3. Functional genomics data privacy
Data Sanitization to Reduce Private Information Leakage from Functional Genomics
Functional genomics data: privacy risk assessment and technological mitigation
Sociotechnical safeguards for genomic data privacy
4. Protein function prediction
Structure-based protein function prediction using graph convolutional networks
DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction
DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks
5. Cancer diagnosis
The evolutionary history of 2,658 cancers
Toward best practice in cancer mutation detection with whole genome and whole-exome sequencing
Tumor fractions deciphered from circulating cell-free DNA methylation for cancer early diagnosis
6. Discover the genetic patterns of complex diseases
Repeat DNA expands our understanding of autism spectrum disorder
Patterns of de novo tandem repeat mutations and their role in autism
Molecular mechanisms underlying nucleotide repeat expansion disorders
7. Spatially resolved transcriptomics
Method of the Year: spatially resolved transcriptomics
Spatially resolved transcriptomics adds a new dimension to genomics
Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention autoencoder
8. Genome-Based drug repurposing
Opportunities for drug repositioning from phenome-wide association studies
Single-cell-led drug repurposing for Alzheimer’s disease
Integrating 3D genomic and epigenomic data to enhance target gene discovery and drug repurposing in transcriptome-wide association studies
9. Transcription factor binding sites prediction
Deep neural networks identify sequence context features predictive of transcription factor binding
Recurrent neural network for predicting transcription factor binding sites
Enhancing the interpretability of transcription factor binding site prediction using attention mechanism
10. Methods to assess off-target CRISPR edits
Inactivation of porcine endogenous retrovirus in pigs using CRISPR-Cas9
CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets
Mapping the genomic landscape of CRISPR–Cas9 cleavage
11. Sequence assembly
Chromosome-scale, haplotype-resolved assembly of human genomes
Sequence assembly demystified
New advances in sequence assembly
12. Multimodal Single-Cell Data Integration
Computational principles and challenges in single-cell data integration
BABEL enables cross-modality translation between multiomic profiles at single-cell resolution
Integrated analysis of multimodal single-cell data

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]