Bio Training in JiangSu

This instructor-led, live training in JiangSu (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 JiangSu (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:

• Learn and understand key concepts of genetics.
• Understand how genetic sequencing and testing operations work.

This is a practical workshop, which will introduce basics of bioinformatics. It is aimed at people with basic biological background and knowledge in molecular biology, who want to learn how to process and work with biological data using computational tools. It has been designed especially for:

• Researchers working in experimental laboratories on biological macromolecules: proteins, RNA, and DNA
• Scientists whose main area of expertise is not biology, but who need to cope with biological data
• Managers introducing new products (e.g., drugs), who want to broaden their knowledge about contemporary bioinformatics
• Computer programmers who are going to write programs dealing with 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 set of guidelines for clinical research done on human subjects. GCP serves as the international standard for designing, conducting, monitoring, documenting, analyzing, and reporting clinical trials.

In this instructor-led, live training, participants will learn the most important guidelines and fundamental principles applied in Good Clinical Practice (GCP) for clinical trials and researches involving human subjects. This course provides an overview of the different GCP areas, but provides slightly more focus on the ICH-centric GCP for Investigational Drugs and Biologics.

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

• Understand the fundamental principles of GCP for investigational drugs and biologics as based on the International Conference on Harmonization (ICH)
• Apply the guidelines stipulated by the GCP to their clinical researches and trials

Audience

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

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Microbial genomics and metagenomics combine sequencing technologies and computational analysis to profile microbial communities, characterize genomes, and detect functional traits such as antimicrobial resistance.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level researchers and bioinformaticians who wish to perform hands-on analysis of microbial genomics and metagenomic sequencing data.

By the end 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.
• Carry out 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.
• Use 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 so participants can apply methods to their data (20%).

Course Customization Options

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

This is a practical course, which shows why programming is a powerful tool in the context of solving biological problems. During the course participants will be taught the Python programming language, a language widely considered both powerful as well as easy to use. This course might be considered as a demonstration how bioinformatics improves biologists lives.

The course is designed and aimed for people without computer science background who want to learn to program.

This course is suited for:

• Researchers dealing with biological data.
• Scientists who would like to learn how to automate everyday tasks and analyse data.
• Managers who want to learn how programming improves workflows and conducting projects.

By the end of the course, participants will be able to write short programs, which will allow them to manipulate, analyse and deal with biological data and present results in a graphical format.

This course aims to give researchers an understanding of the principles of statistical design and analysis and their relevance to research in a range of scientific disciplines.

It covers some probability and statistical methods, mainly through examples. This training contains around 30% of lectures, 70% of guided quizzes and labs.

In the case of closed course we can tailor the examples and materials to a specific branch (like psychology tests, public sector, biology, genetics, etc...)

In the case of public courses, mixed examples are used.

Though various software is used during this course (Microsoft Excel to SPSS, Statgraphics, etc...) its main focus is on understanding principles and processes guiding research, reasoning and conclusion.

This course can be delivered as a blended course i.e. with homework and assignments.