January 13, 2020


Program start, and optional review of Intro to Bioinformatics

January 16, 2020

Introduction to the Program

Program overview, goals and structure

January 30, 2020

Processing NGS data

Raw data pre-processing, mapping, quantification

February 06, 2020

Statistical Analysis 1

Statistical tests, Differential Gene Expression

February 20, 2020

Statistical Analysis 2

Correlation, Analysis of Variance and Factor Regression Analysis

February 27, 2020

Data Science for High Throughput Data

Principles of data-driven thinking

March 05, 2020

Exploratory Analysis and Visualization

Dimensionality Reduction

March 12, 2020

Data Mining for Transcriptomics Data

Clustering and DImensionality Reduction techniques for transcriptomic data

March 19, 2020

Classification and Feature Selection

Gene sets for biomarker discovery

March 26, 2020

Biological Interpretation

Gene Ontologies, functional annotation and pathways

April 02, 2020

Gene Set Enrichment Analysis

Differential Pathway enrichment

April 16, 2020

Basic Programming for Bioinformatics

Working with files and tables in bash and R

April 29, 2020

Final Exam

Optional: Transcriptomics 4, single-cell transcriptomics

Transcriptomics 4

Transcrptomics 4

Optional, single-cell transcriptomics
More Information About the LBRN Transcriptomics 2020 Program Curriculum:

To learn more or get help on the curriculum, time requirements, and other questions, please contact us: info@t-bio.info

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Program License

Change level
LBRN Transcriptomics
61 Days

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Spring Session Graduate Course on Transcriptomic Data Analysis: Applied Bioinformatics Concepts for Life Science Research led by Dr. Gus Kousoulas, Dr. Ramesh Subramania, Dr. Lyndon Coghill, Chris Taylor, and Urska Svek. In this course, we will explore how gene expression can be studied using high throughput sequencing data, leveraging principles of bioinformatics. The course will cover essential steps of processing, analysis and interpretation of such data using commercial solutions for high performance computing (T-BioInfo) and open source applications (R). This program is a collaborative effort between LBRN, BioMMED and Pine Biotech.
Transcriptomics 2
Transcriptomics 1
Introduction to Bioinformatics
Transcriptomics 3
Transcriptomics 4
PCA: biomedical data visualization in R

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