Profile Cell Biology Biochemistry

This course builds on the Structural Biochemistry course in S5. Students will learn the basic concepts of the different approaches used for multi-scale structural characterization and the analysis of macromolecular interactions. The advantages and limitations of all the tools will be highlighted so that students can understand how they complement each other and know how to use them in an integrated way to answer a given biological question. 

The tutorials will be a mix of structural analysis using visualization tools (such as Pymol) and analysis of articles using a combination of the approaches studied in CM. Students will then be required to conceptualize their own experimental project to address a given problem.

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The course provides a comprehensive overview of the concepts required for mathematical modeling in biology. The focus is on linear and nonlinear dynamic systems in one and two dimensions. The course begins with essential concepts in linear algebra: matrices, systems of linear equations, geometric interpretation of the solutions to these systems as vectors and subspaces (line, plane, etc.). The theory of vectors and eigenvalues of matrices is introduced in relation to linear dynamic systems. For nonlinear dynamical systems, we present the qualitative theory of differential equations (attractors, phase portraits, zero-level isoclines) as an alternative to the often complicated calculation of solutions. The tutorial covers a large number of biological models used in ecology, epidemiology, oncology, and systems biology.

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This course unit allows students to consolidate and deepen their practical management of the large amount of experimental data obtained during a week of practical work in a block period (5 consecutive days). This data is obtained following the development of numerous different protocols, with a view to ensuring the best possible reproducibility of the preparations carried out and the fastest possible execution in the preparation, implementation, and analysis of the various experiments. A high degree of autonomy in the implementation of protocols will be encouraged, ultimately leading to experimental mastery and autonomy. These practical sessions also allow for group work (in pairs or threes, depending on capacity and numbers) and the writing of a report detailing the protocols carried out, all the experimental data obtained, and their analysis in order to determine a wide range of biochemical parameters. A significant part of the assessment will be based on the students' ability to generate, manage, exploit, and analyze raw experimental data with the utmost rigor.

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As part of this course, students will learn experimental principles based on the manipulation of nucleic acids. Lectures will focus on two main areas:

1. Implementation of molecular tools (cloning, nucleic acid analysis, vectorology) ii. Their applications (recombinant protein expression, genomic banking, transgenesis, CRISPR/CAS9 system, etc.) and reflection on the concept of ethics in biology.

The tutorials will consist of:

- Analysis of articles presenting issues to be resolved using the knowledge acquired in the course. The topics chosen will, as far as possible, refer to parallel L3 teaching units. These articles will be presented by students in the form of oral presentations by groups of 3 to 4 students to the whole class.

- Sessions reserved for the use of basic bioinformatics tools in the computer lab.

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Systems biology offers the possibility of understanding how living organisms function at different levels of their organization. This course will focus primarily on the subcellular level. At this level, systems biology models integrate several levels of interaction from the transcriptome, proteome, and metabolome. Predictions from in silico models can be used in biomedical research to understand multifactorial diseases and optimize drug treatments, in bioengineering to synthesize genomes with optimized properties and functions (synthetic biology), and to guide fundamental research on the principles of how living organisms function. The course includes a theoretical component (lectures and tutorials on gene, signaling, and metabolic network modeling) and a practical component (computer labs using Matlab software).

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