Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

    címtáras azonosítással

    vissza a tantárgylistához   nyomtatható verzió    

    Algorithm and Software Development in Pharma Research

    A tantárgy neve magyarul / Name of the subject in Hungarian: Algoritmus- és szoftverfejlesztés a gyógyszerkutatásban

    Last updated: 2010. november 9.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

    Mérnök informatikus szak

    BSc képzés

    Course ID Semester Assessment Credit Tantárgyfélév
    VISZA078   0/0/2/f 2  
    3. Course coordinator and department Dr. Csima Judit,
    Web page of the course
    4. Instructors






    András ASZÓDI 



    Institut für Molekulare Pathologie (Wien)


    Judit CSIMA 


    Assoc. professor

    Department of Computer Science and Information Theory 


    5. Required knowledge

    Mathematics and Computer Science: linear algebra, differential equations, Boolean algebra, probability theory. Web programming experience and basic understanding of database technologies is required for the practical part.

    Biology: no previous knowledge is required beyond standard high-school biology. Knowledge of basic concepts such as cell structure, genome organisation, DNA and protein structure is desirable. 

    7. Objectives, learning outcomes and obtained knowledge

    Two main parts are foreseen: the scientific/theoretical part will focus on the topic “Information Processing in Living Systems”, whereas the technological and cross-cultural issues will be explored in the practical exercise “Scientific Software in Pharmaceutical Research”. 

    Part 1 “Information Processing in Living Systems” 

    Living organisms exchange not only matter and energy with their environment, they also process information. The molecular mechanisms of biological regulation will be discussed, in particular gene expression regulation, qualitative and quantitative description of complex kinetic phenomena, metabolic control, signal processing in biochemical reactions, homeostasis and robustness. 

    Part 2 “Scientific Software in Pharmaceutical Research” 

    A well-balanced scientific software portfolio should have three components: commercial software, academic open-source packages, and applications developed in-house. The latter is essential to achieve competitive advantage (“if I use exactly the same tools as my competitors, my results will be very similar to theirs”). The students will work on a fictitious in-house development project “Software at your fingertips” that should present a complex scientific calculation through an intuitive Web interface. Interactions with “non-expert users” and “upper management” will be learned through role-playing exercises

    8. Synopsis

    Week 1: Systems biology: a gentle introduction. Definition of systems. Comparison of natural and artificial systems. Applicability of systems theory and engineering in biology. Basic principles of regulation: positive and negative feedback. Mechanism elucidation: experimental and theoretical methodologies.


    Week 2: The theory of evolution. Fundamental concepts. Evolution of macromolecular sequences, molecular phylogeny. The "Tree of Life": Perception or reality?


    Week 3: Regulation of gene expression. Basic principles of genetic regulation. Nuclear receptors and their pharmacological importance. Epigenetics: was Lamarck right after all? High-throughput methodologies for transcriptome analysis (microarrays, next-generation sequencing).


    Week 4: Complex kinetics. Qualitative description of dynamic processes: equilibria, steady states, periodic processes, deterministic chaos, and their relevance to biology. Quantitative description with differential equations, kinetic simulations. Examples: glycolytic oscillations, "predator-prey models".


    Week 5: Metabolic control. Metabolic networks. Enzyme regulation. The concept of "metabolic flow". Signal processing in biochemical reactions. Self-optimisation in microbial metabolism.


    Week 6: Pattern formation in biological systems. The chemical basis of morphogenesis. Spatiotemporal information processing.


    Week 7: Evolution of networks. Ligand-receptor coevolution. The chemoton theory. System-theoretical description of evolutionary dynamics.


    Week 8: Biology meets Computer Science: DNA computing, evolutionary programming, artificial life.


    Week 9: Homeostasis and Robustness. The purpose of biological regulation: self-preservation in a constantly changing environment. Adaptation via Robustness.


    Weeks 10-14: „Software At Your Fingertips” project: role-playing exercise to simulate an in-house software development project in pharma research. The primary objective here is not to come up with a usable application but rather to learn how to manage a scientific software development project in a tightly controlled environment.

    The project will go through the following stages:-

    - „Preparation”: introduction to the project, discussion of roles.

    - „Kickoff meeting”: the ’programming team’ will be formed.

    - „User requests”: how to manage expectations, how to formulate use cases.

    - „Development meetings”: architectural planning, tools, testing procedures.

    - „Convincing management”: how to present the project successfully to skeptical leaders.

    - „Rollout and Maintenance”: how to manage a mature project.

    The students will assume the following roles:-

    - „Project Leader”: this person will manage the project and interfaces with the users and management;

    - „Architect”: this person will design the application;

    - „Developer”: this person will write code;

    - „Tester/Maintainer”: this person will test the code and will interact with the users after product rollout;

    - „User”: provides use cases, feature requirements, will complain about bugs;

    - „Manager”: requests progress reports, must be convinced that the project is worthwhile, otherwise s/he fires the whole team!

    Depending on the number of students, more than one project team could be formed. The lecturer will act as moderator and neutral observer.

    9. Method of instruction

    Lectures and project-based computer assignments.

    10. Assessment The grading of students is based on the following criteria:



    -  class participation and activity:             30 %


    -  homeworks:                                           10 %


    -  mid-term test:                                         10 %


    -  role-playing exercise:                            25 %


    -  final exam:                                             25 %



    The mid-term test will be written in Week 9.



    The project work is the result of the role-playing exercise (see  Weeks 10-14 above). The final exam consists of a written essay (15..20 pages) on a topic related to the course, plus a 30-minute presentation of the essay. Students who propose a topic on their own will be rewarded by bonus points. The students will be required to challenge each other (asking questions, debating etc) during their presentations and may evaluate their colleagues’ essays anonymously.


    12. Consultations You can reach the instructor at the following e-mail address for consultation:


    András ASZÓDI:


    13. References, textbooks and resources Strogatz, S.H.: Sync: How Order Emerges From Chaos In the Universe, Nature, and Daily Life. Hyperion, 2004.


    Nowak, M.A.: Evolutionary Dynamics: Exploring the Equations of Life. Belknap Press (Harvard University Press), 2006.


    Ashby, W.R.: An Introduction to Cybernetics. Chapman and Hall, 1957 (available electronically from


    Friedrich, P.: Supramolecular Enzyme Organization. Quaternary Structure and Beyond. Pergamon Press, Oxford/Akadémiai Kiadó, Budapest, 1984.

    Lecture notes by András Aszódi.

    14. Required learning hours and assignment
    Number of contact hour 28
    Preparation to the classes 
    Preparation to the tests4
    Assigned reading 
    Preparation to he exam8
    15. Syllabus prepared by
     András ASZÓDI 



    Institut für Molekulare Pathologie (Wien)