Bioinformatics Course

Transition to a Tech Career with Bioinformatics


Bioinformatics is a blend of biology, computer science, and mathematics.

Bioinformatics is an integrated field, which combines computational, mathematical, and statistical methods to manage and analyze biological information using computers especially as applied to molecular genetics and genomics.

One of the reasons why Bioinformatics exists is due to the increasing amount of biological datasets. These are huge scientific research outputs that need to be managed. Bioinformatics is all about managing data and providing scientific knowledge

bioinformatics course - Heels and Tech

This course is designed to help prepare you for high-demand work in bioinformatics science in a corporate, government, and/or academic environment.

Course Value

  • Acquire skills at the interface of life science, computer science and mathematics
  • Use this skills to boost your profile when applying for: Scholarships; Graduate School Funding and Opportunities; Jobs (If you have a MSc in any core life sciences discipline)
  • Expand your Current skill set/flexibility at your current workplace

Learn to Start your Career in Bioinformatics

NGN 250,000/USD 650

NGN 150,000/USD 300

What You’ll Learn

  • Apply the theoretical and computational methodologies relevant to the mining of information from large datasets of biological origin.
  • Combine theory and practice to solve research problems in bioinformatics, genomics, and proteomics.
  • Manipulate data on a computer and understand the algorithms that underlie the analysis tools that are used for essential research tasks.
  • Explore databases and align sequences (Pairwise and Multiple)
  • Construction of phylogenetic tree
  • 3D structure prediction using Thread algorithm
  • Secondary structure Prediction of Globular and Transmembrane protein.
  • Integrate biological concepts with information technologies to study the biological system.
  • Good understanding of homology for 3D structure prediction.

Course Requirement

  • Background in biology, biology, mathematics, computer science, and statistics.
  • An interest in learning Bioinformatics and maintaining the same interest constantly throughout the course.
  • Knowledge in molecular biology, basic genetics, and other life science-related courses would be an advantage but not necessary.
  • You need to have at least a personal laptop or a desktop with a minimum of 4GiB RAM and enough storage capacity for data storing.
  • Good qualitative (semantic) and quantitative (mathematics/statistics) reasoning.
  • No programming skill

Course Outline

  • Introduction to Linux and Bash (Bourne-again shell) on Linux
  • Code version control and documentation (Git/GitHub)
  • Introduction to R, RStudio and R Syntax
  • Statistical analysis and Visualization with R
  • Basic descriptive statistics
  • Dimensionality: Reduction strategies and Clustering
  • Bioconductor on R
  • Sequence Data generation
  • Sequence analysis and Visualization
  • Transcriptome Data Analysis
  • Basic Multi-Omics Strategies (Genomics + Transcriptomics)
  • Final Projects

Who Is This Course For?    

  • Beginners from Biological sciences
  • Data Science beginners who are interested in biological data
  • Statisticians or computer scientists wishing to work in biology for studies in modern bioinformatics.
  • Biologists and clinicians are interested in data analysis


“The Bioinformatics Class has been so helpful in my PhD journey. Currently using one of the resources he gave us to get materials for my PhD. We were given an essay to write as a requirement for one of the courses I take. And it has to do with proteins and peptides, so with that NCBI site and the bookshelf resources Bolu taught, I was able to get some materials for the essay. Made life easy for me??”

Chinelo Nnenna Uju – Bioinformatics Student

The Titles You Can Apply To As A Bioinformatician    

  • Pharmacogenomics
  • Bioinformatics Analyst
  • Bioinformatics Engineer
  • Bioinformatics Specialist
  • Bioinformatics Scientist
  • Bioinformatics Developer
  • Bioinformatics Analyst Programmer
  • Bioinformatics Software Developer
  • Network Administration
  • Database Programmer
  • Science Technician
  • Structural Analyst
  • Biostatistician
  • Computational Biologist
  • Clinical Bioinformatics Expert
  • Gene Analyst

Here Is What You Should Know    

There are limited slots available for us to have practical hands-on training with our students and so we are imploring you to have a spot by registering right now before you lose the opportunity.

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