CPES SV S6 profile Cell biology biochemistry

This course is a continuation of the Structural Biochemistry course in S5. Students will learn the basic concepts of the different approaches used for multi-scale structural characterization and macromolecular interaction analysis. The advantages and limitations of all the tools will be highlighted, so that students can understand the complementarity of these tools and know how to use them in an integrative way to answer a given biological question. 

TDs will be a mix of structural analysis applications using visualization tools (such as Pymol) and article analysis using a combination of the approaches studied in CM. Students will then be asked to conceptualize their own experimental project in response to a given problem.

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

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This course enables students to consolidate and deepen their practical management of numerous experimental data obtained over a week of practical work during a blocked period (5 consecutive days). These data are obtained following the elaboration of many different protocols, keeping in mind to ensure the best reproducibility of the preparations carried out and to have the best speed of execution in the preparation, realization and analysis of the different experiments. A high degree of autonomy in setting up protocols will be encouraged, leading ultimately to experimental mastery and autonomy. This practical work will also enable students to work in groups (in pairs or trios, depending on capacity and number of students), and to write a report recording 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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In this course, students will learn experimental principles based on the manipulation of nucleic acids. The lectures will be structured around two major themes:

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

The TDs will consist of :

- Analysis of articles presenting problems to be solved with the knowledge acquired in the course. As far as possible, the themes chosen will refer to the parallel UEs of L3. These articles will be presented by students in the form of oral presentations in groups of 3 or 4 to the whole class.

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

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Systems biology offers the possibility of understanding how living organisms function at different scales of organization. This course will focus on the sub-cellular scale. At this scale, systems biology models integrate several levels of interaction from the transcriptome, proteome and metabolome. The predictions of in silico models can be used in biomedical research to understand multi-factorial diseases and optimize drug treatments, in bioengineering to synthesize genomes with optimized properties and functions (synthetic biology), as well as to guide fundamental research into the principles of how living organisms function. The course comprises a theoretical component (lectures and practical sessions on modeling gene, signaling and metabolic networks) and a practical component (computer-based practical exercises using Matlab software).

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