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Event - In-person training
UK
This two-day training event will discuss strategies to engineer sufficiently pure, homogenous and high-quality recombinant proteins that are critical for subsequent structural and functional studies.
Designed and delivered by experts from industry and academia, this training event will provide a comprehensive overview of the pre-clinical drug discovery process
Event - Online training
Online
R for Biochemists 201 builds on the content of R101, focussing on proteomic data analysis and uses modern data analysis concepts, packages and visualisations.
Unlock the power of data in the life sciences with our comprehensive online course. This course covers fundamental statistical concepts and techniques essential for biochemistry and related fields. Learn how to analyse and interpret data, apply statistical methods, and enhance your research skills.
Practical Python for beginners aims to teach the core skills which underlie the application of Python to complex, real-world research problems.
R for Biochemists 101 is the Biochemical Society’s original R course, aimed to equip researchers with the information, tools and techniques to use R. It is suited to beginners who want to use this programming software but have little or no experience.
Protein purification and biophysical characterisation of the resulting protein are two major disciplines in modern biochemistry. This training course aims to expose participants to the latest hardware required for protein purification and biophysical measurements.
R for Biochemists 201 builds on the content of R101, focussing on proteomic data analysis and using modern data analysis concepts, packages and visualisations.
This training event aims to provide a framework for designing, evaluating, and publishing new research projects in education.
This training event will focus on the function of biological membranes and the biophysical techniques available to study their components in the context of biology and biotechnology.
The course will focus on getting data into R, and manipulating and visualising this using various methods. Each module will use a biochemical experiment and data as a starting point.
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