CMB is an international Master of science dedicated to the analysis and the modelling of complex biological systems, created as a part of the graduate school of the Turing Center of living systems (CENTURI). It is shared by the departments of mathematics and biology, and aims at gathering students with a high potential coming from different backgrounds and at benefiting from the interdisciplinary synergies between training experts in that scientific area on the rise.
CMB offers a program by and for scientific research, with many opportunities for pursuing studies towards a PhD or obtaining a job in numerous companies having a research department.
The bioinformatics option of the CMB master will focus on the analysis of interaction networks involved in different types of biological processes (embryonic developmental, nervous system, immune response) in order to understand the relationship between network structure and the behaviour of complex biological systems.
This Master of science relies on the activities and skills of the laboratories that compose the Turing center of living systems (CENTURI).
As this Master is a research-focused study path, a BSc in Life sciences (or related domains) obtained with Honors is required.
Group projects and internships in research laboratories will lead students to apply interdisciplinary approaches and interact directly with researchers from the institutes of the Turing Center for Living Systems (CENTURI).
The Master Computational and Mathematical Biology, entirely taught in English, combines theoretical and practical courses of mathematics, computer sciences and biology. It provides an interdisciplinary training oriented towards modelling of complex biological systems.
This course Fundamentals in biology is divided in 2 parts taught during the 1st and 2nd semester of CMB. In the first semester, we will give a presentation of the evolutionary theories that have founded modern biology (from Lamarck to Darwin), and a synthesis of the discoveries that have led to current concepts of molecular and cellular biology : the role of macromolecules in cell function (information transfer between DNA, RNA, proteins, regulation, etc.), heredity and cellular adaptation.
Below are some topics covered during the lectures :
The teaching unit consists of a presentation of the main professions involved in biological modelling. It will be carried out in two ways. First of all, some seminars will be offered with speakers from outside Aix-Marseille University in the academic and industrial field. Secondly, students will benefit from an immersion in Centuri laboratories where they will discover multidisciplinary research topics. To conclude this unit, students will be asked to present a specific problem related to data processing and modelling. The scientific aspect will also have to be integrated into a reflection on the underlying professional issues, whether in the academic or private sector.
Genomics is an interdisciplinary field of modern biology studying the full genetic complement (the genome) of an organism. With nearly 3,500 genomes now sequenced, the post-genomic era has considerably improved our knowledge of the origin of diversity and evolution of genomes, cellular pathways, organismal phenotypes and human diseases. The course will be split into three main topics of a teaching course followed by a practical informatics-oriented course designed to cover the methods of genome analysis, the evolution of eukaryotic genomes, the power of comparative genomics to understand gene regulation and will finish by exploring how genomics gives rise to epigenomics and how both allow our understanding of gene regulation and its dysfunction in the development of human diseases.
This course is an introduction to the basics of finite dynamic systems and PLC networks (definitions of local functions, global function/relationship, automata, interaction graph, transition graph) as well as the main static and dynamic properties. A part of the lecture will also focus on the parallel update mode.
The lectures should provide students the skills to implement modelling approaches (differential, logical, stochastic or deterministic equations) to develop mathematical models of a biological system, analyze mathematical models and biological data to understand complex systems, evaluate the adequacy between a biological question, available data, and mathematical formalisms and interpret and validate a study.
3 parts : 1) Unix : - file system and basic shell commands - text utilities - redirections, pipe 2) Programming language (Python) : - basic principles of imperative programming : variable, type, assignment, operators - control flow (conditional, iterations, loops) - basic data structures : tuple, list, dict - files (text, input/output) - local and external modules : math, random, numpy, scipy, matplotlib, pandas - functions 3) Algorithms : arrays, sorting, lists, stacks, queues
Computational biology will introduce the biological concepts necessary to model complex systems, implement modelling approaches (differential, logical, stochastic or deterministic equations) to develop mathematical models of a biological system, analyze mathematical models and biological data to understand complex systems and assess the adequacy between a biological question.
The course is divided in 2 sections :
This course is a quick revision of the basics of probability and statistics. The concepts will be taught in relation to concrete biology exemples (genome analysis, complex systems). The following concepts will be taught :
Some biological examples of applications could concern the probability of patterns in genomic sequences, the detection of differentially expressed genes.
The purpose of this course is to introduce some of the simplest differential equations and systems of differential equations which underlie the main continuous models used in biology (dynamics of populations or cells, biochemical processes, etc.). We will address both qualitative (long-time behavior) and quantitative (positivity, parameter dependency) properties of the considered models. In parallel to this theoretical study, numerical simulations will be performed during the computer sessions. Practicals will consist in using Python specialised libraries as scipy.integrate in order to visualise trajectories and systems behaviours.
This course will give a review of some basic notions of algebra and analysis. Illustrations in Python will be given. We will focus on the matrix tools necessary for regression :
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The course is in conitnuity with the course Fundamentals of biology 1. This module will show how these molecular mechanisms underlie the development and functioning of tissues and organisms. It will be structured around four areas :
Some examples topics covered during the lectures :
This introductory course focuses on graphs as mathematical objects and some of its uses to solve applications to biological networks. After intruducing different classes of graphs and their properties, the following points will be developped :
This course aims at providing students with a practical approach of the analysis of biological data with R, based on the concepts acquired in the course “Probabilities and statistics for modelling 1”. The associated mathematical foundations will be developed in the course “Advanced statistics”. The following notions will be investigated :
This course will tackle advanced notions in statistics such as :
This course is addressed to students with a background in biology, and aims at enforcing the theoretical grounds in order to allow them to apprehend advanced statistics. The following concepts will be investigated :
At the end of the courses Professional perspectives for biological systems modelling , and Fundamentals of biology 1,, students will choose a scientific article at the interface of several disciplines on which they will work in groups. They will have to present in a memory and an oral presentation, to explain the biological context and the related basic concepts, to explain the methods used to interpret the biological data, to synthesize the results obtained in the article.
Scientific seminars constitute a good way to broaden your scientific horizon. In this regard, MSc students will frequently attend CENTURI seminars. At the end of the semester, students will be asked to write a summary of two seminars they have attended.
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This course is an introduction to inferential statistics. It will be illustrated with biogical examples. The course will be composed by three parts
This course will propose some illustrations of the concepts and results of mathematical modelling to biological systems, with a specific focus on the domains of interest to CenTuri (immunology, developmental biology, neurology).
Practicals will consist in a personal project that may consist in extending one of the examples seen in the courses.
Following the module Research project and scientific communication, the students will do a short internship in laboratory. They will have to propose a modelling or data processing problem at the math-info-bio interface. They will be asked to synthesize their results in a dissertation and an oral presentation.
Following the module Centuri seminars 2, the students will attend all the Centuri seminars of this semester. For two of them, they will be asked to broaden their knowledges on the subject and present an oral and written synthese. The work will be done in collaboration.
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