The program is designed for biologists, clinicians and researchers or students that are interested in advancing their understanding of big data in life sciences. The program will not require any background in coding, bioinformatics or biostatistics, however we will speak about topics related to cell and molecular biology and utilize terminology coming from biostatistics and data science domains. Anyone with a good handle on biological sciences at an undergraduate university level is welcome to join. The program is conducted by experienced biologists and bioinformaticians versed in applications of bioinformatics in biomedicine, agrobiology and biotechnology.
In the program, you will learn about the impact of the genomic revolution, next-generation sequencing and computational technologies in every area of life sciences: research, biomedical, biotechnology, and agrobiology. You will also learn to find, understand and analyze data using high-performance computing and user-friendly tools for biologists.
Session Topics: Biostatistical tools and exploratory data analysis concepts for working with NGS data Outcome: Learn about commonly used statistical tests and associated terminology. Learn...
Session Topics: History of Omics Data and its significance, Overview of the entire course, Overview of the tools and resources for this program (edu.t-bio.info...
Session Topics: What is Bioinformatics, Knowledge-Driven vs. Data-Driven Discovery, Examples of Data-Driven Discoveries, Applications of Bioinformatics in Agriculture, Neuroscience, Cancer Biology, Immunology, Defense, and...
Session Topics: Overview of Processing NGS Data (from raw data to structured data), Standard tools and concepts for genomics, transcriptomics, metagenomics Outcome: Learn data...
Session Topics: Data Mining, Machine learning and their application to high throughput data Outcome: learn to differentiate between various clustering and classification techniques, understand how...
Session Topics: Gene annotation using databases, pathway analysis, linking phenotype and genotype Outcome: Learn to infer biological insight from data and learn about project examples...