Programming for Biologists Training Course

This is a hands-on workshop designed to introduce the core principles of bioinformatics. It is tailored for individuals with a foundational background in biology and molecular biology who wish to learn how to process and manipulate biological data using computational tools. The course has been specifically crafted for:

• Researchers working in experimental laboratories on biological macromolecules such as proteins, RNA, and DNA.
• Scientists whose primary expertise lies outside biology but who need to handle biological data effectively.
• Managers involved in introducing new products (e.g., pharmaceuticals) who want to expand their understanding of contemporary bioinformatics.
• Computer programmers planning to develop software related to biological molecules.

The course comprises two main sections: theoretical instruction and practical application. Lectures are interspersed with straightforward practical exercises, quizzes, and tests to ensure participants fully grasp the concepts.

During the training, you will embark on a guided tour covering all fundamental aspects of biological data analysis. This workshop offers an ideal opportunity to become familiar with the diverse facets of bioinformatics. By the end, you will be equipped to address basic bioinformatics challenges: you will know where to source the necessary data, how to extract relevant information, and how basic software and algorithms function. Our goal is to facilitate your comprehension of biological data.

Upon completion of the course, you will be able to work with biological data using bioinformatics tools.

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

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

• Grasp and comprehend fundamental concepts in genetics.
• Understand the mechanics of genetic sequencing and testing operations.

Good Clinical Practice (GCP) constitutes a framework of guidelines for clinical research involving human subjects. It establishes the international standard for the design, conduct, monitoring, documentation, analysis, and reporting of clinical trials.

Through this instructor-led live training, participants will master the critical guidelines and core principles underlying Good Clinical Practice (GCP) as applied to clinical trials and research on human subjects. While the course offers a broad overview of various GCP domains, it places particular emphasis on ICH-centric GCP requirements for investigational drugs and biologics.

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

• Comprehend the fundamental principles of GCP for investigational drugs and biologics, grounded in the International Conference on Harmonization (ICH) standards
• Apply GCP guidelines effectively to their clinical research and trial activities

Audience

• Clinical investigators
• Clinical research professionals
• Healthcare and medical professionals
• Clinical trials support staff
• Research and development staff

Course Format

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

Microbial genomics and metagenomics integrate sequencing technologies with computational analysis to profile microbial communities, characterize genomes, and identify functional traits like antimicrobial resistance.

This instructor-led live training, available online or onsite, targets beginner to intermediate researchers and bioinformaticians seeking hands-on experience in analyzing microbial genomics and metagenomic sequencing data.

Upon completion, participants will be able to:

• Explain standard sequencing workflows and essential file formats in microbial genomics.
• Conduct quality control and preprocessing of raw NGS reads.
• Execute 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.
• Implement reproducible workflows using Conda, Docker, and notebook-based reporting.

Course Format

• Lectures covering 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%).

Customization Options

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

This instructor-led, live training session Norway (available online or onsite) targets scientists and any individuals wishing to learn the basics of Nanoscience and its applications.

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

• Gain insight into the domains of nanosciences and nanotechnologies.
• Distinguish between phenomena in the nano range and those in the micro range.
• Comprehend the core theories regarding electron and energy transfer.

This programme provides researchers with a comprehensive grasp of statistical design and analysis principles, highlighting their significance across diverse scientific fields.

The curriculum explores key 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 private courses, we can customize examples and materials to align with specific disciplines, such as psychology assessments, public administration, biology, or genetics.

Public courses utilize a broad range of mixed examples to ensure versatility.

While the course incorporates various software tools (ranging from Microsoft Excel to SPSS and Statgraphics), the primary emphasis remains on comprehending the fundamental principles and processes that underpin research, critical reasoning, and valid conclusions.

This course is also available in a blended format, incorporating homework and assignments.