PickAClass · AI Applications (Interdisciplinary) · AI for Medicine & Diagnostics

AI for Genomics & Proteomics

Apply AI and machine learning techniques to analyze large-scale genomic and proteomic data for disease research, variant calling, and understanding biological pathways.

AI for Genomics & Proteomics

Computational Genomics: Analyzing Personal Genome Sequences

Computational Functional Genomics: Analyzing Genomic Data

Computational Biology and Genomics: A Practical Introduction

High-Performance Computing and Reproducible Genomics with Bioconductor

Data Analysis for Life Sciences: Functional Genomics in R

Palindromic DNA Sequence Analysis: Algorithms for Bioinformatics

Introduction to DNA Sequencing Technologies and Genome Assembly

DNA Mutation Analysis Using Graph Mapping in Computational Biology

Bioinformatics Foundations: Graphs and Genome Assembly

Genomic String Reconstruction with Paired De Bruijn Graphs

Bioinformatics Foundations: Sequence Alignment and Edit Distance

Genome Assembly Fundamentals: String Reconstruction and De Bruijn Graphs

Topological Ordering and DAGs for Bioinformatics

Genome Assembly with de Bruijn Graphs and Paired Composition

Bioinformatics Algorithms: Generating Eulerian Cycles in Directed Graphs

Bioinformatics Algorithms: Solving the Coin Change Problem with Recursion

Graph Theory for Genome Assembly: Gluing and Adjacency Matrices

Graph Algorithms for Bioinformatics: The Manhattan Tourist Problem

Big-O Notation for Algorithm Efficiency in Bioinformatics

De Bruijn Graphs for Genome Assembly

Bioinformatics Algorithms: Solving the DNA Clump Finding Problem

Graph Theory for Genome Assembly: Euler, Hamilton, and de Bruijn

Bioinformatics and Computational Biology Interview Prep

Sequence Alignment with Affine Gap Penalties