EdX

Graph Algorithms in Genome Sequencing (edX)

Graph Algorithms in Genome Sequencing (edX)

Learn how graphs are used to assemble millions of pieces of DNA into a contiguous genome and use these genomes to construct a Tree of Life.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

In this course, part of the Algorithms and Data Structures MicroMasters program, you will learn how graph algorithms are used in two fundamental problems in modern biology:

  • How do we sequence a genome?
  • How do we construct an evolutionary “Tree of Life?"

In the first part of the course, you will learn how genome sequencing relies on using a graph to assemble millions of tiny DNA fragments into a contiguous genome. We will then shift gears and learn how to construct an evolutionary tree of life from genome data.

What you'll learn

  • Graph algorithms
  • Algorithms for genome assembly
  • Phylogenetics

Course Syllabus

Week 1: Introduction to Genome Sequencing and Graphs
Introduction to the basics of genome sequencing, and first attempts to model this problem using graphs.
Weeks 2 and 3: Assembling Genomes from Tiny Fragments
Applying an Eulerian path approach to assemble a genome from small pieces of DNA, and adapting this theoretical solution to practical considerations.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Aplicaciones de la Teoría de Grafos a la vida real II (edX) EdX
Universitat Politècnica de València,UPValenciaX

Aplicaciones de la Teoría de Grafos a la vida real II (edX)

Aprenderemos a modelizar problemas del mundo real mediante su representación con grafos y a resolverlos mediante sus algoritmos asociados. Este curso trata la Teoría de Grafos desde el punto de vista de la modelización, lo que nos permitirá con posterioridad resolver muchos problemas de diversa índole. Presentaremos ejemplos de los distintos problemas en un contexto real, analizaremos la representación de éstos mediante grafos y veremos los algoritmos necesarios para resolverlos.

Self Paced
Self-Paced
Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps (edX) EdX
Georgia Institute of Technology,GTx

Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps (edX)

Become familiar with nonlinear and hierarchical data structures. Study various tree structures: Binary Trees, BSTs and Heaps. Understand tree operations and algorithms. Learn and implement HashMaps that utilize key-value pairs to store data. Explore probabilistic data structures like SkipLists. Course tools help visualize the structures and performance.

Self Paced
Self-Paced
Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms (edX) EdX
Georgia Institute of Technology,GTx

Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms (edX)

Delve into Pattern Matching algorithms from KMP to Rabin-Karp. Tackle essential algorithms that traverse the graph data structure like Dijkstra’s Shortest Path. Study algorithms that construct a Minimum Spanning Tree (MST) from a graph. Explore Dynamic Programming algorithms. Use the course visualization tool to understand the algorithms and their performance.

Self Paced
Self-Paced
Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms (edX) EdX
Georgia Institute of Technology,GTx

Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms (edX)

Learn more complex tree data structures, AVL and (2-4) trees. Investigate the balancing techniques found in both tree types. Implement these techniques in AVL operations. Explore sorting algorithms with simple iterative sorts, followed by Divide and Conquer algorithms. Use the course visualizations to understand the performance.

Self Paced
Self-Paced
Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues (edX) EdX
Georgia Institute of Technology,GTx

Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues (edX)

Work with the principles of data storage in Arrays, ArrayLists & LinkedList nodes. Understand their operations and performance with visualizations. Implement low-level linear, linked data structures with recursive methods, and explore their edge cases. Extend these structures to the Abstract Data Types, Stacks, Queues and Deques.

Self Paced
Self-Paced
Introduction to Object-Oriented Programming with Java II: Object-Oriented Programming and Algorithms (edX) EdX
Georgia Institute of Technology,GTx

Introduction to Object-Oriented Programming with Java II: Object-Oriented Programming and Algorithms (edX)

Learn the basics of object-oriented programming and algorithms. Students will build on the skills learned from “Introduction to Object-Oriented Programming with Java I: Foundations and Syntax Basics” and learn the basics of writing classes that serve as blueprints of concepts or objects that are represented in a programming problem. Students will leverage the concepts of inheritance, interfaces, and polymorphism to program reusability and flexibility in classes. Finally, students will gain experience walking through and analyzing algorithms that are applied on data (including objects) in many object-oriented programs.

Self Paced
Self-Paced
Fundamentals of Python (edX) EdX
SDA_Bocconi,SDA Bocconi School of Management

Fundamentals of Python (edX)

We will equip you with everything you need to properly start using Python in your daily work activities. You will learn how to install Python and work with it through different graphical front-ends. You will then learn how to define objects and how to recognize different characteristics and functionalities. Finally, you will learn how to make Python execute a series of instructions in a sequential order through loops, as well as how to write your own functions.

Self Paced
Self-Paced
Advanced Linear Algebra: Foundations to Frontiers (edX) EdX
University of Texas at Austin,UTAustinX

Advanced Linear Algebra: Foundations to Frontiers (edX)

Learn advanced linear algebra for computing. Linear algebra is one of the fundamental tools for computational and data scientists. In Advanced Linear Algebra: Foundations to Frontiers (ALAFF), you will build your knowledge, understanding, and skills in linear algebra, practical algorithms for matrix computations, and the analysis of the effects of floating-point arithmetic as performed by computers.

Self Paced
Self-Paced