Genetic Sequencing and Testing Training Course

This is a practical workshop designed to introduce the fundamentals of bioinformatics. It is aimed at individuals with a basic background in biology and molecular biology who wish to learn how to process and work with biological data using computational tools. The course is specially designed for:

• Researchers working in experimental laboratories on biological macromolecules: proteins, RNA, and DNA.
• Scientists whose primary expertise is not biology but who need to manage biological data.
• Managers introducing new products (e.g., drugs) who wish to broaden their knowledge of contemporary bioinformatics.
• Computer programmers preparing to write programs that deal with biological molecules.

The course consists of theoretical and practical components. Lectures are interwoven with simple practical exercises, quizzes, and concept checks to ensure comprehension. Throughout the training, participants will follow a guided path covering all foundational aspects of biological data analysis. This workshop serves as an ideal entry point into bioinformatics, equipping learners to tackle basic bioinformatics problems: identifying authoritative data sources, extracting relevant information, understanding core algorithms, and confidently using bioinformatics tools.

By the end of the course, participants will be able to work with biological data using bioinformatics tools.

Good Clinical Practice (GCP) constitutes a framework of guidelines for clinical research involving human participants. It serves as the global standard for the design, execution, monitoring, documentation, analysis, and reporting of clinical trials.

In this instructor-led live training, attendees will explore the core guidelines and fundamental principles underpinning Good Clinical Practice (GCP) for trials and research involving human subjects. While the course provides a broad overview of various GCP areas, it places particular emphasis on ICH-centric GCP standards for Investigational Drugs and Biologics.

Upon completion of this training, participants will be able to:

• Comprehend the fundamental GCP principles for investigational drugs and biologics, as established by the International Conference on Harmonization (ICH)
• Apply GCP guidelines to their clinical research and trials

Audience

• Clinical investigators
• Clinical research professionals
• Healthcare and medical professionals
• Staff supporting clinical trials
• Research and development personnel

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Microbial genomics and metagenomics merge advanced sequencing technologies with computational analysis to profile microbial communities, characterize genomes, and identify functional traits such as antimicrobial resistance.

This instructor-led, live training (available online or onsite) is designed for beginner to intermediate researchers and bioinformaticians who wish to gain hands-on experience analyzing microbial genomics and metagenomic sequencing data.

Upon completion of this training, participants will be able to:

• Describe common sequencing workflows and the key file formats used in microbial genomics.
• Conduct quality control and preprocessing of raw NGS reads.
• Perform taxonomic profiling using marker-based and k-mer approaches.
• Assemble and annotate microbial genomes and plasmids.
• Detect SNPs, construct phylogenies, and interpret population structure.
• Predict antimicrobial resistance genes and summarize functional profiles.
• Utilize reproducible workflows incorporating Conda, Docker, and notebook-based reports.

Course Format

• Lectures introducing concepts and tools (20%).
• Hands-on practical sessions utilizing example datasets (60%).
• Open discussions and guided analysis to allow participants to apply methods to their own data (20%).

Course Customization Options

• To request a customized workshop focusing on clinical, environmental, or industrial metagenomics, please contact us to arrange.

This instructor-led, live training in Greece (online or onsite) is designed for scientists and anyone eager to grasp the fundamentals of Nanoscience and its practical applications.

Upon completing this training, participants will be able to:

• Comprehend the fields of nanosciences and nanotechnologies.
• Distinguish between phenomena in the nano range and those in the micro range.
• Master the fundamental theories of electron and energy transfer.

This hands-on course demonstrates why programming serves as a powerful asset in addressing biological challenges. Participants will be introduced to Python, a programming language renowned for its versatility and user-friendliness. The curriculum effectively illustrates how bioinformatics can enhance the daily work of biologists.

Designed specifically for individuals without a computer science background who wish to learn coding, this course bridges the gap between biology and technology.

This course is ideal for:

• Researchers managing biological datasets.
• Scientists seeking to automate routine tasks and perform data analysis.
• Managers interested in understanding how programming can streamline workflows and project execution.

Upon completion, participants will be equipped to write concise programs that enable them to manipulate, analyze, and interpret biological data, while presenting findings in clear graphical formats.

This course is designed to help researchers grasp the fundamental principles of statistical design and analysis, highlighting their importance across various scientific fields.

The curriculum covers key probability and statistical methods, primarily illustrated through practical examples. The training structure consists of approximately 30% lectures and 70% guided quizzes and laboratory exercises.

For closed group courses, we can customize the examples and materials to suit a specific discipline, such as psychology testing, public sector work, biology, genetics, and more.

For public courses, a diverse mix of examples from various fields is utilized.

While the course employs various software tools (ranging from Microsoft Excel to SPSS and Statgraphics), the primary emphasis remains on comprehending the underlying principles and processes that guide research, reasoning, and conclusions.

This course can also be offered in a blended format, incorporating homework and assignments.