Nanoscience Fundamentals Training Course

This hands-on workshop provides an introduction to the core principles of bioinformatics. It is designed for individuals with a foundational background in biology and molecular biology who wish to learn how to process and analyze biological data using computational methods. The course is particularly suitable for:

• Researchers in experimental laboratories focusing on biological macromolecules such as proteins, RNA, and DNA.
• Professionals whose primary expertise lies outside biology but who regularly encounter biological data.
• Managers developing new products (e.g., pharmaceuticals) who wish to expand their understanding of modern bioinformatics.
• Software developers preparing to create applications that handle biological molecules.

The program consists of two main components: theoretical instruction and practical application. Lectures are integrated with practical exercises, quizzes, and assessments to ensure participants fully grasp the underlying concepts.

Through this guided journey, you will explore all essential aspects of biological data analysis. This workshop serves as an excellent opportunity to become familiar with the diverse applications of bioinformatics. By the conclusion, you will be equipped to address fundamental bioinformatics challenges: you will understand where to source necessary data, how to extract relevant information, and how basic software tools and algorithms function. Our goal is to enhance your comprehension of biological data.

Upon completion of the course, you will possess the skills to utilize bioinformatics tools effectively for working with biological data.

This instructor-led, live training in Slovakia (online or onsite) is designed for healthcare professionals and workers seeking to gain intermediate to advanced knowledge of various genetic sequencing and testing procedures.

By the end of this training, participants will be able to:

• Learn and understand core genetics concepts.
• Comprehend how genetic sequencing and testing operations function.

Good Clinical Practice (GCP) constitutes a comprehensive set of guidelines governing clinical research involving human participants. It establishes the international benchmark for the design, execution, monitoring, documentation, analysis, and reporting of clinical trials.

This instructor-led live training guides participants through the critical guidelines and core principles underpinning Good Clinical Practice (GCP) for clinical trials and studies involving human subjects. The course offers a broad overview of GCP domains, with a particular emphasis on ICH-centric GCP standards for investigational drugs and biologics.

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

• Comprehend the fundamental principles of GCP for investigational drugs and biologics, as defined by the International Conference on Harmonization (ICH)
• Effectively apply GCP guidelines to their respective clinical research and trials

Audience

• Clinical investigators
• Clinical research professionals
• Healthcare and medical practitioners
• Support staff for clinical trials
• Research and development personnel

Course Format

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

By integrating sequencing technologies with computational analysis, microbial genomics and metagenomics enable the profiling of microbial communities, genome characterization, and the identification of functional traits such as antimicrobial resistance.

This instructor-led live training, available both online and onsite, is designed for beginner to intermediate researchers and bioinformaticians seeking to conduct hands-on analysis of microbial genomics and metagenomic sequencing data.

Upon completing this training, participants will be capable of:

• Explaining standard sequencing workflows and the primary file formats utilized in microbial genomics.
• Executing quality control and preprocessing steps for raw NGS reads.
• Conducting taxonomic profiling through marker-based and k-mer methodologies.
• Assembling and annotating microbial genomes and plasmids.
• Identifying SNPs, constructing phylogenies, and interpreting population structures.
• Predicting antimicrobial resistance genes and summarizing functional profiles.
• Implementing reproducible workflows using Conda, Docker, and notebook-based reporting tools.

Course Format

• Conceptual lectures and tool introductions (20%).
• Practical, hands-on sessions utilizing example datasets (60%).
• Open discussions and guided analysis, allowing participants to apply methods to their own data (20%).

Customization Options

• For customized workshops focused on clinical, environmental, or industrial metagenomics, please contact us to arrange specific requirements.

This hands-on course demonstrates why programming is an invaluable asset for addressing biological challenges. Participants will learn the Python programming language, which is widely regarded for its power and ease of use. The course serves as a practical illustration of how bioinformatics can enhance the daily work of biologists.

Designed specifically for individuals without a computer science background who wish to acquire programming skills.

This course is ideal for:

• Researchers working with biological data.
• Scientists seeking to automate routine tasks and analyze data.
• Managers aiming to understand how programming can streamline workflows and project execution.

Upon completion, participants will be capable of writing concise programs to manipulate, analyze, and manage biological data, as well as present findings through graphical representations.

This program is designed to equip researchers with a solid grasp of statistical design and analysis principles, highlighting their importance across various scientific fields.

The curriculum explores fundamental probability and statistical techniques, primarily illustrated through practical examples. The training structure comprises approximately 30% lecture content and 70% guided quizzes and laboratory exercises.

For closed-group sessions, we can customize examples and materials to align with specific sectors, such as psychology, public administration, biology, or genetics.

Public course participants will engage with a diverse range of mixed examples.

While the course utilizes various software tools (ranging from Microsoft Excel to SPSS and Statgraphics), the primary emphasis remains on comprehending the core principles and processes that underpin research reasoning and conclusion formulation.

This training can also be offered as a blended learning experience, incorporating homework and assignments.