Genomics for Biomedical Drug Discovery is an online bioinformatics training program that will provide an in-depth overview of concepts and analytical tools used to study genomic variation. The program is designed to introduce students, clinicians and researchers to the role and the applications of Genomic Data Analysis to study genomic variation and apply genomics in translational sciences to improve diagnostic accuracy, predict which drugs are likely to be effective in patients, and contribute to the monitoring, treatment and diseases in individuals and populations.

Each week, participants will meet online to discuss various aspects of NGS data processing, genomic data analysis, and interpretation. After the first introductory lectures, participants will have the opportunity to get guidance and work on curated datasets or develop independent projects that leverage the tools and concepts covered in this program.

Key Topics Covered:

Big data, HPC and cloud computing

Many types of omics data require step-by-step preparation, exploration, annotation, and visualization to understand. The T-BioInfo platform was designed for big multi-omics data analysis hiding the complexities of data with a user-friendly and intuitive interface that eliminates the need for coding and advanced machine learning algorithms for data integration and mining.

NGS: omics data types and use cases

A program that embeds data-driven concepts into biological projects, spanning the student learning journey from observer to participant in research. Project-based learning for big data bioinformatics is to go beyond the theory with real datasets, projects, and expert mentors. Work with curated datasets from publicly available repositories with easy-to-follow tutorials.

Computational pipelines for data processing

Data processing for Next Generation Sequencing, Mass-Spectroscopy, Structural and phenotypic data. Build and adapt pipelines using similar approaches to data mapping, quantification, and annotation that are used to prepare data for downstream statistical analysis, train machine learning models and annotate features.

Introduction to Programming: R and Python
Online bioinformatics coding exercises to learn and explore R and Python scripting and understand how to analyze and visualize -omics data to extract meaningful insights from large biological datasets. Learn, practice, and achieve bioinformatics greatness with concise exercises and interesting challenges right in the comfort of your browser!

Program Syllabus : OmicsLogic Genomics

SESSIONS TITLE

TOPICS TO BE COVERED

FEBRUARY 02, 2022

Course Overview

Course structure, expectations, and intended outcomes.
Applications of bioinformatics (Introduction to Bioinformatics Course),
Examples in Biomedical Research
Pharma R & D and Agriculture

Associated online resources:

Introduction to Bioinformatics Course
DNA Structure & Variants
Access to the educational portal (https://learn.omicslogic.com) & analytical server (server.t-bio.info)

FEBRUARY 09, 2022

Bioinformatics in R and Python

Working with sequences DNA
RNA and Protein sequences

Associated online resource:

Working with DNA Sequences in R

Next Generation Sequencing history and applications

FEBRUARY 16, 2022

NGS history & applications

History of NGS
Overview of DNA structure
DNA variations: Point mutations
Deletions, Duplication, Frame Shift
Types of Genomics sequencing: Targeted, Whole Genome, Whole Exome
Advancements & Challenges
Current application of NGS in Biomedical Drug designing and Discovery

Associated online resources:

FEBRUARY 21, 2022 at 1 PM CST

LIVE QnA Session

FEBRUARY 23, 2022

Introduction to Genomics

Technologies for DNA and RNA sequencing: Microarray, High Throughput Sequencing, qPCR (Introduction to Genomics Course)
Advantages and applications of NGS: Illumina, Nanopore and PacBio
Computational challenges with short-read sequencing (Big Data)

Associated online resources: