Into to Big Data Bioinfo

On this page, you will find information on the program training topics, syllabus and ways to register. Introduction to Bioinformatics - this training program is designed for everyone, including students who don't have a background in bioinformatics, as well as life science researchers. The objective is to introduce topics and examples to help participants understand Omics data, and the use of bioinformatics in life science research. As a result of this training, you will learn about Next Generation Sequencing (NGS) data analysis. This includes processing and preparing data for analysis in application to Genomics, Transcriptomics, and Metagenomics. You will also get an overview of downstream analysis and interpretation of various types of -omics data using bioinformatics, including commonly used annotation databases, statistical analysis and machine learning techniques.

Key Topics Covered:

Big Data in Biology
Introduction to Omics Data in Life Science Research, including various types: Genomics, Transcriptomics and Metagenomics. Learn how Next Generation Sequencing can be used to study biological variation and understand genes, mutations and microorganisms responsible for experimental conditions or clinical factors in disease.
  Statistical Analysis of Omics Data
Learn about statistical analysis for Big Data, including how to use apxpropriate analysis techniques to measure differences between groups of samples. See examples of advanced data analysis methods and ways to perform visualization, annotation and interpretation of analysis results.
  Machine Learning for Biomedical Data Science
Overview of analytical methods for processing, visualization and analysis of complex biomedical data.  Terminology and use-cases for machine learning and artificial intelligence in biomedical discovery, clinical research and experimentation.
  Bioinformatics Project Examples
Case Study to learn about: Modelling Cancer Precision Medicine: Learn to analyze various omics data types, integrate them and associate them with a phenotype (response to treatment) using sophisticated machine learning algorithms.

Why Next Generation Sequencing? With the decreasing cost of Next Generation Sequencing (NGS) and the increasingly broad range of applications, this technology has transformed biomedical research, the biotechnology industry, and now is becoming increasingly becoming popular in clinical use. Analysis of NGS data can help identify pathogenic, germline, and somatic DNA variants; measure gene expression; detect methylation patterns, and even study microbial communities on human skin, in the gut, lungs, and other organs. That is why this program can help anyone who is getting started with life science research and bioinformatics to understand these techniques, their applications and a broad overview of various methods to know getting started with bioinformatics. To get started, you can join this program and gain access to the following modules:

Program Syllabus : Introduction to Big Data Bioinformatics




Introduction & Orientation 
  • Program overview and Introduction
  • Omics Logic Learn: courses, projects, and profile demonstration
  • T-BioInfo Analytics Platform - how to access and learn from demo pipelines
  • Q&A discussion 
  • Schedule review for the training program
  • description of the program structure and important deadlines
Associated online course/resource:

Introduction to NGS Genomics 


Introduction to NGS Genomics 
  • Genome variation: A detailed overview
  • Targeted Sequencing, Whole Exome Sequencing, and Whole Genome Sequencing
  • Logical steps for Genomic Data Analysis and associated Algorithms
  • Analysis with Integrative Genomics Viewer
Associated online course/resource:

Introduction to Gene Expression NGS Data Analysis 



Introduction to Gene Expression NGS Data Analysis 
  • Analysis logic: from raw reads to a table of expression (RNA-seq example)
  • Common sources of unwanted technical variation 
  • pre-processing steps, filtering and cleaning the table of expression
  • Loading processed data for analysis
Associated online course/resource:

Transcriptomics in Research: DEGs & Pathway annotation 


Transcriptomics in Research: DEGs & Pathway annotation  
  • Introduction to Differential gene expression
  • DESEQ and EDGER,
  • Volcano plots, MA Plots, Heatmaps 
  • Regression and Factor Regression Analysis
  • Application of transcriptomics in research
Associated online course/resource:

Biomedical Data Science: Introduction to Machine Learning for NGS Data


Biomedical Data Science: Introduction to Machine Learning for NGS Data
  • Introduction to Machine Learning
  • Types of Machine Learning methods 
  • Overview of unsupervised machine learning methods
  • Finding patterns and similarities in data
  • Principal Component Analysis (PCA) Hierarchical and K-means clustering
Associated online course/resource:

Bioinformatics NGS Machine Learning Projects


Bioinformatics NGS Machine Learning Projects

    • Overview of supervised machine learning methods
    • Preparing Training and test datasets
    • Classification: Decision Trees, Random Forest (RF), Support Vector Machine (SVM)
    • Bioinformatics Project examples & OmicsLogic Research Fellowship
       Associated online course/resource:


If you need help finalizing registration, contact Farhana Musarrat (email: You have to register for the orientation using the form below. For LSU or LBRN members, you can complete your registration via BIOMMED iLab link below - 

Register for the Online Mentor Guided Training Program

The program will include the following asynchronous resources:

OL Introduction to Bioinformatics OL Bytes and Molecules Omics Logic T-BioInfo User-friendly-1 OL BioInfo in R Omics Logic Project Case Studies
An overview of bioinformatics and it's key applications.  Omics Technologies and Key terminology to know. User-friendly bioinformatics analysis solutions. Introduction to coding and analysis in R Curated datasets and Project Case Studies


LBRN certificate

Training Certificate from the Louisiana Biomedical Research Network or LSU BioMMED:

  • Certification of Training Requirement Completion
  • Recognition within the Network and Other IDeA States
  • Advancement for Research, Faculty and Student participants within the LBRN Network
  • Training certification for LSU through the Center for Biotechnology and Biomolecular Medicine at the Louisiana State University

A few examples from the program:

Previous participants share their feedback on the training:

"This lesson gave a good explanation and example for how normal citizens can participate in complex biomedical work without the extensive background many scientists have".
- Lane Yutzy, PhD Fellow
LSU student
"I enjoyed the lessons and look forward to learning more.It is a great documentation for beginners. For anyone starting afresh, I’d highly recommend these courses. Examples and resources are really useful".
- Wellesley Dittmar, Graduate Student
Clay Brassuel-1
"The course outlined the basics of molecular biology that is needed for understanding the sequencing results. Complex concepts are explained in simple words".
- Clay Brasuell, Graduate Student