Advanced course on modeling and inferring gene regulatory networks from transcriptomic data, combining machine learning, systems biology, and data-driven approaches.
Focus: Systems Biology · Machine Learning · Network Inference · Transcriptomics
Level: Advanced / Graduate / Research
Introduction to gene regulation mechanisms and biological network structures.
Access materialsOverview of computational approaches to infer gene regulatory networks from expression data.
Access materialsApplication of classification-based models for reconstructing gene regulatory interactions.
Access materialsHands-on project exploring gene regulatory interactions in developmental biology using real datasets.
Access materialsComputational methods for genomic sequence analysis, including string matching, alignment algorithms, suffix structures, and probabilistic models for biological sequences.
Focus: Genomics · String Algorithms · Sequence Alignment · Computational Biology
Level: Advanced Undergraduate / Graduate
Overview of computational genomics and sequence-based biological data analysis.
Access materialsAlgorithms for comparing biological sequences and identifying similarities.
Access materialsComputational methods for measuring similarity between biological sequences.
NotebookEdit distance metrics for sequence comparison and mutation modeling.
Access materialsEfficient data structures for fast substring search in genomic sequences.
Access materialsCompression and indexing technique widely used in genomic alignment tools.
Access materialsHands-on implementation of the Burrows–Wheeler transform and applications.
NotebookComputational prediction of RNA folding and structural stability.
NotebookBasic probabilistic and heuristic models for genomic sequence analysis.
Access materialsExploration of evolutionary landscapes using sequence-based neutral models.
NotebookStatistical approaches for identifying patterns and associations in genomic data.
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