Bio Training in Tashkent

This instructor-led, live training in Tashkent (online or onsite) is aimed at scientists and anyone interested to learn about the basics of Nanoscience and its applications.

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

• Understand the field of nanosciences and nanotechnologies.
• Differentiate those in the nano range from those in the micro range.
• Know the fundamental theory of electron and energy transfer.

This instructor-led, live training in Tashkent (online or onsite) is aimed at healthcare professionals and workers who wish to learn intermediate to advanced-level knowledge of the different genetic sequencing and testing operations.

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

• Acquire and comprehend the fundamental concepts of genetics.
• Grasp the mechanisms behind genetic sequencing and testing operations.

This practical workshop introduces the basics of bioinformatics. It targets individuals with a foundational background in biology and molecular biology who want to learn how to process biological data using computational tools. It has been specifically designed for:

• Researchers working in experimental laboratories on biological macromolecules: proteins, RNA, and DNA
• Scientists whose primary expertise lies outside 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 develop programs for biological molecules

The course is divided into theoretical and practical components. Lectures are interwoven with simple practical exercises, quizzes, and concept checks to ensure comprehension. During the training, participants will follow a guided tour 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) is a comprehensive set of guidelines governing clinical research involving human subjects. It establishes the international standard for the design, execution, monitoring, documentation, analysis, and reporting of clinical trials.

In this instructor-led live training, participants will explore the essential guidelines and core principles of Good Clinical Practice (GCP) as applied to clinical trials and research involving human subjects. While the course covers various GCP domains, it places particular emphasis on ICH-centric GCP standards for investigational drugs and biologics.

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

• Grasp the fundamental principles of GCP for investigational drugs and biologics, as defined by the International Conference on Harmonization (ICH)
• Apply GCP guidelines effectively to their own clinical research and trials

Target Audience

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

Course Format

• A blend 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 such as antimicrobial resistance.

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

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

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

Format of the Course

• Lectures introducing concepts and tools (20%).
• Hands-on practical sessions using 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 hands-on course highlights the significance of programming as a vital tool for addressing biological challenges. Participants will learn Python, a programming language renowned for its power and user-friendly nature. The course serves as an illustration of how bioinformatics can enhance the work of biologists.

Designed for individuals without a computer science background, this course is ideal for those eager to learn programming.

This course is perfect for:

• Researchers handling biological data.
• Scientists aiming to automate routine tasks and analyze data.
• Managers interested in understanding how programming can optimize workflows and project execution.

By the end of the course, participants will be capable of writing short programs to manipulate, analyze, and manage biological data, as well as present results graphically.

This course aims to provide researchers with a solid understanding of the principles of statistical design and analysis, as well as their relevance to research across a wide range of scientific disciplines.

The training covers key probability and statistical methods, primarily illustrated through practical examples. Approximately 30% of the course consists of lectures, while 70% is dedicated to guided quizzes and hands-on lab sessions.

For closed courses, examples and materials can be customised to fit a specific field, such as psychology, public sector research, biology, genetics, and more.

In public courses, a mix of examples from various disciplines is used.

Although the course utilises a range of software tools—from Microsoft Excel to SPSS and Statgraphics—its primary focus remains on developing a clear understanding of the principles and processes that guide research, reasoning, and conclusion-drawing.

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