Bioinformatics

• Gesamtes Lehrangebot der Bioinformatik

  E61aA1.1
  • 19000546 Mentoring
    Mentoring (Ulrike Seyferth)
    Schedule: -
    Location: keine Angabe
    

    Comments

    The mentoring program offers events and counseling services primarily (but not only!) for first-year students. All offers are voluntary and are based on your needs and wishes!

    If you have questions or wishes, please contact us!

    Your mentors in mathematics, computer science and bioinformatics

  • 19200501 Lecture
    Computerorientated Mathematics I (5 LP) (Ralf Kornhuber, Claudia Schillings)
    Schedule: Fr 12:00-14:00 (Class starts on: 2024-10-18)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Comments

    Contents:
    Computers play an important role in (almost) all situations in life today. Computer-oriented mathematics provides basic knowledge in dealing with computers for solving mathematical problems and an introduction to algorithmic thinking. At the same time, typical mathematical software such as Matlab and Mathematica will be introduced. The motivation for the questions under consideration is provided by simple application examples from the aforementioned areas. The content of the first part includes fundamental terms of numerical calculation: number representation and rounding errors, condition, efficiency and stability.

    Homepage: All current information on lectures and lectures

    Suggested reading

    Literatur: R. Kornhuber, C. Schuette, A. Fest: Mit Zahlen Rechnen (Skript zur Vorlesung)

  • 19200502 Practice seminar
    Practice seminar for Computerorientated Mathematics I (5 LP) (André-Alexander Zepernick)
    Schedule: Mo 08:00-16:00 (Class starts on: 2024-10-14)
    Location: A3/SR 119 (Arnimallee 3-5)
    
  • 19200541 Zentralübung
    Large tutorial for Computerorientated Mathematics I (5 LP) (André-Alexander Zepernick)
    Schedule: Fr 14:00-16:00 (Class starts on: 2024-10-18)
    Location: A6/SR 031 Seminarraum (Arnimallee 6)
    
  • 19234810 Proseminar
    Women in the History of Mathematics and Computer Science (N.N.)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    For mathematicians and computer scientists in a monobachelor's degree, creditable as ABV!

    Comments

    The seminar focuses on the development and rediscovery of the life stories and the work of some important mathematicians and computer scientists in the 19th and 20th centuries. The life and work of Sophie Germaine (1776-1831), Ada Lovelace (1815-1852), Sonja Kovalevskaya (1850-1891), Emmy Noether (1882-1935), Ruth Moufang (1905-1977), Grace Murray Hopper (1906-1992) and other female scientists are examined.

    The seminar is not about highlighting these women as an exception, because it would only set them on their exotic status. Rather, it is about a historical contextualization of their life and work. This not only enables an exemplary examination of social and cultural inclusion and exclusion processes along the gender category, but also the development of new perspectives on the traditional cultural history of both disciplines. The seminar is based on the approach of researching or discovering learning, i.e. the students will independently prepare and present individual seminar topics in group work. These presentations will then be discussed in the seminar. Through the use of observation sheets, a feedback culture is also to be tested that will be helpful in dealing with pupils and/or colleagues in later professional life.

  • 19300001 Lecture
    Fundamentals of Programming (Wolfgang Mulzer)
    Schedule: Mo 14:00-16:00, Mi 12:00-14:00 (Class starts on: 2024-10-14)
    Location: , Gr. Hörsaal (Raum B.001), Hs Anorganik
    

    Comments

    Qualification goals 

    The students can explain and compare different programming paradigms. They are able to interpret descriptions and source code related to fundamental data structures, to characterize how they work, and to implement basic algorithms and data structures in different programming paradigms, adapting them to given requirements. They can discuss the advantages and disadvantages of different solutions for algorithmic problems.

    Contents

    Students acquire the fundamentals of programming. We will discuss basic programming paradigms, such as imperative, functional, and object oriented. Students will learn about expressions and data types, as well as fundamental aspects of imperative programming (e.g., state, statements, control structures, input-output), and practice their application. Students will also gain an understanding of fundamental aspects of functional programming (functions, recursion, higher-order functions, currying), object-oriented concepts such as encapsulation and inheritance, polymorphism, as well as basic algorithmic tasks (e.g., searching, sorting, selection, and simple array- and pointer-based data structures), and practice their implementation.

  • 19300002 Practice seminar
    Practice seminar for Fundamentals of Programming (N.N.)
    Schedule: Mo 08:00-10:00, Mo 10:00-12:00, Mo 12:00-14:00, Mo 16:00-18:00, Di 08:00-10:00, Di 10:00-12:00, Di 12:00-14:00, Di 16:00-18:00, Mi 10:00-12:00 (Class starts on: 2024-10-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    Tutorien finden erst ab der 2. Vorlesungswoche statt

  • 19300901 Lecture
    Discrete Structures for Computer Science (Katharina Klost)
    Schedule: Di 14:00-16:00, Do 14:00-16:00 (Class starts on: 2024-10-15)
    Location: Elisabeth-Schiemann-Hörsaal (R 014) (Königin-Luise-Str. 12 / 16)
    

    Comments

    Qualifikationsziele

    Die Studierenden formulieren³ Aussagen formal aussagenlogisch und prädikatenlogisch. Sie analysieren⁴ und vereinfachen³ die logische Struktur gegebener Aussagen und beschreiben⁴ die logische Struktur von Beweisen. Sie benennen Eigenschaften unterschiedlicher Mengen, Relationen und Funktionen und begründen⁴ diese mit Hilfe formaler Argumente. Sie können Beweise für elementare Aussagen unter Verwendung elementarer Beweistechniken entwickeln⁵ und die Mächtigkeit von Mengen mit Hilfe kombinatorischer Techniken sowie Wahrscheinlichkeiten von Zufallsereignissen bestimmen³. Sie sind in der Lage, Fragestellungen der (Bio-)Informatik mit Hilfe der Graphentheorie und der diskreten Wahrscheinlichkeitstheorie zu modellieren.^3. Die Studierenden benennen Eigenschaften unterschiedlicher Graphen und begründen⁴ diese mit Hilfe formaler Argumente.

    Inhalte

    Studierende erlernen grundlegende Konzepte der Mengenlehre, Logik, Booleschen Algebra, Kombinatorik und Graphentheorie und üben deren Anwendung. Sie erarbeiten sich in der Mengenlehre Mengen, Relationen, Äquivalenz- und Ordnungsrelationen und Funktionen. Im Bereich der Logik und Booleschen Algebra erarbeiten sie sich Aspekte der Aussagenlogik, Prädikatenlogik, Erfüllbarkeitstests, sowie Boolesche Funktionen und Normalformen. Im Themenfeld Kombinatorik erlernen und diskutieren sie das Schubfachprinzip, Rekursion, Abzählprinzipien, Fakultät und Binomialkoeffizienten. Im Themenfeld Graphentheorie erarbeiten sie Repräsentationsformen, Wege, Kreise und Bäume. Zuletzt erarbeiten sie sich verschiedene Beweistechniken und grundlegende Aspekte Diskreter Wahrscheinlichkeitstheorie. Die meisten dieser Konzepte werden an Rechen- oder Beweisaufgaben geübt.

  • 19300902 Practice seminar
    Practice seminar for Discrete Structures for CS (Katharina Klost)
    Schedule: Di 12:00-14:00, Mi 10:00-12:00, Mi 14:00-16:00, Do 16:00-18:00 (Class starts on: 2024-10-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    
  • 19301101 Lecture
    Analysis for Computer Science and Bioinformatics (Katinka Wolter)
    Schedule: Mi 10:00-12:00, Fr 10:00-12:00 (Class starts on: 2024-10-16)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Additional information / Pre-requisites

    The sign-up for the tutorial sessions will be announced in due time.

    Comments

    Contents:

    • number systems: from natural numbers to real numbers, completeness property of the reals
    • polynomials: roots of polynomials, polynomial interpolation, rational functions
    • special functions:  exponential function, logarithm, trigonometric functions
    • complex numbers: exponential function for complex numbers, complex roots
    • convergence of sequences and series, convergence of functions, continuous functions, O-notation
    • differential calculus: derivative of a function,  interpretations and applications of the derivative
    • intergral calculus: primitive functions, definite integrals,  fundamental theorem of calculus, applications
    • power series
    • basics of stochastics: probability spaces, discrete and continuous random variables, expected value and variance of random variables

    Suggested reading

    • Kurt Meyberg, Peter Vachenauer: Höhere Mathematik 1, Springer-Verlag, 6. Auflage 2001
    • Dirk Hachenberger: Mathematik für Informatiker, Pearson 2005
    • Peter Hartmann: Mathematik für Informatiker, Vieweg, 4. Auflage 2006
    • Thomas Westermann: Mathematik für Ingenieure mit Maple 1, Springer-Verlag, 4. Auflage 2005

  • 19301102 Practice seminar
    Practice seminar for Analysis for Computer Science (Katinka Wolter)
    Schedule: -
    Location: keine Angabe
    
  • 19301201 Lecture
    Foundations of Theoretical Computer Science (Katharina Klost, Wolfgang Mulzer)
    Schedule: Mo 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2024-10-14)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Comments

    Contents:

    • models of computation
      • automata
      • formal languates
      • grammars and the Chomsky-hierarchy
      • Turing-machines
      • computabilty
    • introduction to the complexity of computational problems

    Suggested reading

    • Uwe Schöning, Theoretische Informatik kurzgefasst, 5. Auflage, Spektrum Akademischer Verlag, 2008
    • John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman, Einführung in die Automatentheorie, Formale Sprachen und Komplexität, Pearson Studium, 3. Auflage, 2011
    • Ingo Wegener: Theoretische Informatik - Eine algorithmenorientierte Einführung, 2. Auflage, Teubner, 1999
    • Michael Sipser, Introduction to the Theory of Computation, 2nd ed., Thomson Course Technology, 2006
    • Wegener, Kompendium theoretische Informatik - Eine Ideensammlung, Teubner 1996

  • 19301202 Practice seminar
    Practice seminar for Foundations of Theoretical Computer Science (Wolfgang Mulzer)
    Schedule: Di 08:00-10:00, Mi 14:00-16:00, Mi 16:00-18:00 (Class starts on: 2024-10-15)
    Location: T9/049 Seminarraum (Takustr. 9)
    
  • 19303501 Lecture
    Advanced Algorithms (László Kozma)
    Schedule: Di 10:00-12:00, Fr 10:00-12:00 (Class starts on: 2024-10-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target audience

    All Master and Bachelor students who are interested in algorithms.

    Prerequisites

    Basic familiarity with the design and analysis of algorithms.

    Comments

    This course will focus on the design and analysis of algorithms, with topics including:

    • general principles of algorithm design,
    • randomized algorithms,
    • dynamic programming,
    • flow problems on graphs,
    • amortized analysis and advanced data structures,
    • theory of NP-completeness,
    • approximation methods for hard problems,
    • other topics.

    Prerequisites are basic knowledge of algorithms and relevant mathematics. All Bachelor and Master students interested in advanced algorithmic techniques are welcome. Lectures are in English.

    Suggested reading

    • Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms, 4th Ed. MIT Press 2022
    • Kleinberg, Tardos: Algorithm Design, Addison-Wesley 2005.
    • Sedgewick, Wayne: Algorithms, 4th Ed., Addison-Wesley 2016

  • 19303502 Practice seminar
    Practice seminar for Advanced Algorithms (László Kozma)
    Schedule: Fr 08:00-10:00, Fr 14:00-16:00 (Class starts on: 2024-10-18)
    Location: T9/046 Seminarraum (Takustr. 9)
    
  • 19304801 Lecture
    Geospatial Databases (Agnès Voisard)
    Schedule: Di 14:00-16:00 (Class starts on: 2024-10-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Zielgruppe:
    
    Studierende im Masterstudiengang Voraussetzungen: Vorlesung: Einf. in Datenbanksysteme

    Comments

    The goal of this course is to acquire the background of spatial databases, the kernel of Geographic Systems. The major aspects that will be handled are: modeling and querying geospatial information, spatial access methods (SAMs), data representation, basic operations (mostly from computational geometry), and optimization. Insights into current applications such as location-based services (e.g., navigation systems) will also be given. Knowledge in databases is necessary. This course encompasses: formal lectures, exercises, as well as a practical project with PostGIS.
     

    Suggested reading

    Handouts are enough to understand the course.
    
    The following book will be mostly used: P. Rigaux, M. Scholl, A. Voisard.Spatial Databases - With Application to GIS. Morgan Kaufmann, May 2001. 432 p. (copies in the main library)

  • 19304802 Practice seminar
    Practice seminar for Geospatial Databases (Agnès Voisard)
    Schedule: Do 14:00-16:00 (Class starts on: 2024-10-17)
    Location: T9/K 040 Multimediaraum (Takustr. 9)
    
  • 19328301 Lecture
    Data Visualization (Claudia Müller-Birn)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    https://www.mi.fu-berlin.de/en/inf/groups/hcc/teaching/winter_term_2021_22/course_data_visualization.html

    Comments

    The current rapid technological development requires the processing of large amounts of data of various kinds to make them usable by humans. This challenge affects many areas of life today, such as research, business, and politics. In these contexts, decision-makers use data visualizations to explain information and its relationships through graphical representations of data. This course aims to familiarize students with the principles, techniques, and methods in data visualization and provide practical skills for designing and implementing data visualizations.

    This course gives students a solid introduction to the fundamentals of data visualization with current insights from research and practice. By the end of the course, students will

    1. Be able to select and apply methods for designing visualizations based on a problem,
    2. know essential theoretical basics of visualization for graphical perception and cognition,
    3. know and be able to select visualization approaches and their advantages and disadvantages,
    4. be able to evaluate visualization solutions critically, and
    5. have acquired practical skills for implementing visualizations.

    This course is intended for students interested in using data visualization in their work and students who want to develop visualization software. Basic knowledge of programming (HTML, CSS, Javascript, Python) and data analysis (e.g., R) is helpful.

    In addition to participating in class discussions, students will complete several programming and data analysis assignments. In a mini-project, students work on a given problem. Finally, we expect students to document and present their assignments and mini-project in a reproducible manner.

    Please note that the course will focus on how data is visually coded and presented for analysis after the data structure and its content are known. We do not cover exploratory analysis methods for discovering insights in data are not the focus of the course.

    Suggested reading

    Textbuch

    Munzner, Tamara. Visualization analysis and design. AK Peters/CRC Press, 2014.

     

    Zusätzliche Literatur

    Kirk, Andy: Data visualisation: A handbook for data driven design. Sage. 2016.

    Yau, Nathan: Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Wiley Publishing, Inc. 2011.

    Spence, Robert: Information Visualization: Design for Interaction. Pearson. 2007.

  • 19328302 Practice seminar
    Data Visualization (Claudia Müller-Birn)
    Schedule: -
    Location: keine Angabe
    
  • 19333611 Seminar
    Seminar Deep Learning for biomedical applications (Vitaly Belik)
    Schedule: Mo 16:00-18:00 (Class starts on: 2024-10-14)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    Recent developments in the area of machine learning due to availability of data and computational power promise to revolutionize almost every area of science. The driving technology behind this advancement is deep learning – a machine learning technology based on artificial neural networks consisting of many layers. Deep learning is capable of processing huge amount of data of different nature and already outperforming humans in many decision-making tasks. Biomedical research became now a source of large heterogeneous data, i.e. images, video, activity sensors, omics and text data. Leveraging the opportunities of this deep learning technology in the biomedical field requires particular set of skills combining thorough knowledge of necessary algorithms, specifics of biomedical data and designated programming tools. In this course we aim to offer students with background in computer science an opportunity to acquire the above skills to be able to deploy deep learning technology with a focus on biomedical applications. The course is structured as a seminar, where students under extensive guidance of instructors read fundamental books and recent research articles on deep learning, learn necessary programming tools, and produce their own implementations of computational pipelines in case studies using already published or original data. Starting from fundamental aspects of deep learning we aim to cover its applications to e.g. image data, time series data, text data, complex networks.

    Suggested reading

    [1] Andresen N, Wöllhaf M, Hohlbaum K, Lewejohann L, Hellwich O, Thöne- Reineke C, Belik V, Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expres- sion analysis. Plos One, 15(4):e0228059, (2020) https://doi.org/10.1371/ journal.pone.0228059

    [2] Jarynowski A, Semenov A, Kamiński M, Belik V. Mild Adverse Events of Sputnik V Vaccine in Russia: Social Media Content Analysis of Telegram via Deep Learning. J Med Internet Res 2021;23(11):e30529 https://doi.org//10.2196/30529

  • 19335011 Seminar
    Seminar: Networks, dynamic models and ML for data integration in the life sciences (Katharina Baum, Pauline Hiort, Pascal Iversen)
    Schedule: Fr 12:00-13:30 (Class starts on: 2024-07-26)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Comments

    Research seminar of the group Data Integration in the Life Sciences (DILiS). Also open for seminar participation in the Master's program, online participation possible. Please refer to the current schedule on the whiteboard!

    The seminar offers space for the discussion of advanced and integrative data analysis techniques, in particular presentations and discussion of ongoing or planned research projects, news from conferences, review and discussion of current literature and discussion of possible future teaching formats and content, and presentations, as well as final presentations on theses or project seminars. The seminar language is mostly English. Interested students are welcome to attend and drop in without obligation or present a topic of their own choice of interest to the working group as in a usual seminar. Please note: Individual dates may be canceled or postponed. Please contact me in case of questions (katharina.baum@fu-berlin.de)!

  • 19336717 Seminar / Undergraduate Course
    Graph-neural networks in the life sciences and beyond (Katharina Baum, Pauline Hiort, Pascal Iversen)
    Schedule: Di 12:00-14:00 (Class starts on: 2024-10-15)
    Location: A6/SR 009 Seminarraum (Arnimallee 6)
    

    Comments

    Complex data can often be naturally modeled as a graph. Graphs or networks describe the interaction between objects and are an effective tool to represent systems in many applications. Graph neural networks are neural networks that directly input graphs and have recently emerged as a powerful tool to analyze networks and to predict properties of nodes and connections.

    This seminar offers an in-depth exploration of Graph Neural Networks (GNNs) and their applications across various domains, with a particular emphasis on the life sciences and biomedicine. We will begin by discussing the fundamental concepts and architectures of GNNs, including graph convolutional networks (GCNs) and graph attention networks (GATs). Applications that are discussed include protein-protein interaction networks, drug discovery and personalized medicine. Students will read and present research papers and participate in critical discussions.

    The language of this seminar is planned to be English. The students are encouraged to present and discuss in English, but contributions in German are also possible.

  • 19336801 Lecture
    Integrative analysis and including prior knowledge for data in the life sciences (Katharina Baum, Pauline Hiort, Pascal Iversen)
    Schedule: Mi 10:00-12:00 (Class starts on: 2024-10-16)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

    Comments

    Especially in the life sciences, data of different origins are often available for a question, and researchers already have prior knowledge, for example on dynamic aspects, or on spatial or regulatory relationships between entities. This course deals with analysis methods that can combine different data and prior knowledge. For example, we discuss how to link continuous and categorical data in mixed models, but also network integration, or multi-factorial matrix multiplication. A focus topic will deal with various approaches to informed machine learning such as graph-neural networks, transfer learning or current research methods such as simulation-based pre-training. The focus here is explicitly not on the processing of images, but on tabular or other data types. This course will be offered in English.

  • 19336802 Practice seminar
    Integrative analysis of biomedical data tutorials (Katharina Baum)
    Schedule: Fr 10:00-12:00 (Class starts on: 2024-10-18)
    Location: T9/046 Seminarraum (Takustr. 9)
    
  • 19400001 Lecture
    Algorithmic Bioinformatics I and Numerics (Knut Reinert)
    Schedule: Do 12:00-14:00 (Class starts on: 2024-10-17)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    The following topics are addressed in the lecture: methods for approximate and exact sequence search and comparison. Among those are index based methods, multiple searches, and heuristics for sequence search. In the numerics part we will address rounding errors, condition, stability as well as vector and matrix norms. Also we will address the Gauss elimination and LR decomposition.

    In the exercises, you will deepen the content and practice analysis and proof techniques.

    Please notice that the practical course "Praxis der Algorithmischen Bioinformatik I und Numerik" (19401330) is synchronized with this module. Please inform yourself on the corresponding page.

    Suggested reading

    Generelle Bücher/Basic reading:

    • Neil C. Jones, Pavel A. Pevzner: An Introduction to Bioinformatics Algorithms. MIT Press, Cambridge, MA, 2004. ISBN 0-262-10106-8
    • R. Durbin, S. Eddy, A. Krogh, G. Mitchison: Biological sequence analysis. Cambridge University Press, 1998. ISBN 0-521-62971-3
    • David B. Mount: Bioinformatics. Sequence and Genome Analysis. Cold Spring Harbor Laboratory Press, New York, 2001. ISBN 0-87969-608-7
    • Chao, Zhang: Sequence comparison, Theory and Methods: Springer, ISBN: 978-1-85800-319-4

  • 19400002 Practice seminar
    Practice seminar for Algorithmic Bioinformatics I and Numerics (Knut Reinert)
    Schedule: Di 10:00-12:00, Di 12:00-14:00, Do 14:00-16:00 (Class starts on: 2024-10-15)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    
  • 19400432 Research Internship
    Bioinformatics Research Internship (Priyanka Banerjee, Tim Conrad, Dorothee Günzel, Katharina Jahn, Camila Mazzoni, Irmtraud Meyer, Frank Noe, Robert Preissner, Knut Reinert, Bernhard Renard, Martin Vingron, Max von Kleist, Jana Wolf)
    Schedule: -
    Location: keine Angabe
    

    Comments

    Please contact your advisor.

    Further information on our homepage.

  • 19401201 Lecture
    Algorithmic Bioinformatics (Katharina Jahn, Knut Reinert, Martin Vingron)
    Schedule: Di 14:00-16:00, Do 14:00-16:00 (Class starts on: 2024-10-15)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    Please see German description.

  • 19401202 Practice seminar
    Ü: Algorithmic Bioinformatics (Katharina Jahn)
    Schedule: Di 12:00-14:00, Mi 10:00-12:00, Do 10:00-12:00 (Class starts on: 2024-10-15)
    Location: A3/SR 119 (Arnimallee 3-5)
    
  • 19401230 Internship
    Prak: Algorithmic Bioinformatics (Katharina Jahn, Svenja Mehringer)
    Schedule: -
    Location: keine Angabe
    
  • 19401330 Internship
    P: Algorithmic Bioinformatics I and Numerics (Chris Bielow)
    Schedule: Mo 10:00-12:00, Mo 12:00-14:00, Mo 14:00-16:00, Mo 16:00-18:00, Di 12:00-14:00, Di 14:00-16:00 (Class starts on: 2024-10-14)
    Location: A6/017 Frontalunterrichtsraum (Bioinf) (Arnimallee 6)
    

    Comments

    This practical course is associated with the lecture and exercise "Algorithmen und Datenstrukturen". It starts with an introduction to programming tools and the programming language applied in the lecture/exercise. After that, programming skills will be explained and taught using the algorithms discussed in the lecture.

  • 19402433 Professional Internship
    Bioinformatics Internship (N.N.)
    Schedule: -
    Location: keine Angabe
    

    Comments

    For further information see german text version.

     

  • 19402911 Seminar
    Journal Club Computational Biology (Knut Reinert)
    Schedule: Mo 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Open for:

    Master and PhD students

    Comments

    Content:

    In this seminar we will present original work in Computational biology as well as progress reports from PhD students. Master students will either be assigend a paper, or present their MSc thesis plans and results, or report about their research internship. Credits are only awarded for the presentation of papers.

    Please sign up on the Whiteboard (open "Site Browser" and look forJournal Club).

    Suggested reading

    aktuelle Publikationen aus der Forschung

  • 19403720 Course
    Introduction to C++ (Sandro Andreotti, Chris Bielow)
    Schedule: Termine siehe LV-Details (Class starts on: 2024-09-30)
    Location: T9/K 036 Rechnerpoolraum (Takustr. 9)
    

    Additional information / Pre-requisites

    This course is primarily aimed at students of bioinformatics (in preparation for the module "Algorithms and Data Structures" in the third semester). Students of computer science are also allowed to participate, provided that places are available.

    Comments

    The course is held as a two-part block course over a total of three weeks. One week takes place before the lecture period and two weeks after the lecture period. Every day there is a two-hour theoretical introduction. Afterwards, the theory is put into practice in a two-hour exercise (in the form of programming tasks). The course is aimed at students with little or no previous knowledge of C++. Previous knowledge of object-oriented programming is required.

    Contents (preliminary planning)
    1st week: Basics

        Basic language elements
        Creation of simple programs
        Compiler / Linker
        data types
        STL
         IO
        ...

    2nd week: Deepening

        object orientation
        templates

    Week 3: Mixed topics

        parallelization
        lambda expressions
        rValue References
        ....

  • 19404070 Begrüßungs- und Abschlussveranstaltung
    Welcome event for master students of bioinformatics (Ulrike Seyferth)
    Schedule: Mo 14.10. 14:00-16:00 (Class starts on: 2024-10-14)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    This information session is aimed at master students in their first semester, especially those who did their bachelor's degree at another university (in Germany or a different country). Attendants will be provided with information on the organization and the content of their studies. Afterwards there will be the opportunity to talk to experienced master's students and get to know fellow students.

  • 19404611 Seminar
    Open science, data handling and ethical aspects in bioinformatics (Thilo Muth)
    Schedule: Do 14:00-16:00 (Class starts on: 2024-10-17)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    The main objectives of this seminar are (1) to introduce fundamental methods of data handling in bioinformatics research with a particular focus on lab management systems, containerized frameworks and software workflow systems, (2) to provide a general overview of open science, sustainable software development, information security and data protection and (3) to discuss ethical issues, chances and risks with regard to fundamental research and personalized medicine.

    Planned topics are as follows:

    • Open vs. closed Science: chances and risks of open science. Open access and traditional publishing.
    • Sustainable software development and reproducible research: open data and open source, code repositories, maintainability of software and code in the sciences
    • Laboratory information management systems: sample management, integration of instruments and application, data exchange
    • Bioinformatic workflows: Galaxy, Snakemake and KNIME
    • Containerized frameworks: Advantages of using Docker, Bioconda etc.
    • Information security and data protection: securing personalized data, relevance for data analyses in research, efficient handling guidelines of data security, potential issues with open science
    • Ethical issues, chances and risks of omics research: immense opportunities when manipulating genome information, novel ethical questions need to be asked, „right not to know“, danger of discrimination against individuals or groups based on genetic differences

    Organisational note: During the first course at the beginning of the semester, the aforementioned topics will be briefly introduced and course material (e.g. relevant publications) will be provided. In the second course, topics will be assigned to the attendees of the seminar.

  • 19404901 Lecture
    Foundations in Computer Science (Knut Reinert)
    Schedule: Di 10:00-12:00 (Class starts on: 2024-10-15)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    

    Comments

    In this lecture we will introduce concepts and methods of advanced algorithmics relevant to current reseach in bioinformatics. We will discuss Methods for the development and analysis of deterministic and randomised algorithms and foundations of compact data structures. Finally, the lecture will encompass concepts for parallel and vectorized computing. In more detail we will cover:

    - Introduction into different kinds of algorithms and analysis methods
    - Foundations of compact data structures 
    - Graph theiry and graph algorithms 
    - Analysis of randomized algorithms and data structures
    - Introduction into parallel and vectorized computing
    - Concepts, paradigms and frameworks for distributed computing

  • 19404902 Practice seminar
    Practice seminar: Foundations in Computer Science (Knut Reinert)
    Schedule: Di 12:00-14:00 (Class starts on: 2024-10-15)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    
  • 19405001 Lecture
    Foundations in Mathematics and Statistics (Max von Kleist)
    Schedule: Do 10:00-12:00 (Class starts on: 2024-10-17)
    Location: A3/SR 120 (Arnimallee 3-5)
    

    Comments

    Goals: The students get a basic understanding of advanced mathematical concepts and methods in numerics, statistics, and optimization in the context of current research in bioinformatics and systems biology. They are able to choose problem-specific methods, to apply them in practice, and to evaluate the quality of the results.

    Contents: The course will address topics from the following areas:

    • Numerics
      • Modeling chemical reaction networks
      • Differential equation modeling
      • Parameter identification, sensitivity, identifiability
    • Optimization
      • Linear optimization (Simplex, polyhedra)
      • Integer linear optimization (branch-and-bound, branch-and-cut)
      • Local search and metaheuristics
    • Statistics
      • Testing and regression
      • Classification
      • Bootstrap and model evaluation

  • 19405002 Practice seminar
    Practice seminar for Foundations in Mathematics and Statistics (Max von Kleist)
    Schedule: Do 12:00-14:00 (Class starts on: 2024-10-17)
    Location: A3/SR 120 (Arnimallee 3-5)
    
  • 19405106 Seminar-style instruction
    SU: Introduction to Focus Areas (Katharina Jahn, Knut Reinert, Max von Kleist)
    Schedule: Mo 12:00-14:00 (Class starts on: 2024-10-21)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19405152 RV
    Introduction to Focus Areas (Katharina Jahn, Knut Reinert, Max von Kleist)
    Schedule: Mo 10:00-12:00 (Class starts on: 2024-10-21)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Comments

    The module presents interdisciplinary exemplary problems and approaches from the three focus areas "Data Science for Bioinformatics", "Complex Systems in Bioinformatics" and "Advanced Algorithms in Bioinformatics". During a project, teams work together on concrete tasks on selected topics from these focus areas. They develop concrete proposals for solutions to practice-oriented problems, implement them and present the results.

  • 19405911 Seminar
    Biochemical networks and disease (Jana Wolf)
    Schedule: Mi 12:00-14:00 (Class starts on: 2024-10-16)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    Molecular metabolic, signaling and gene-regulatory networks form complex networks that underly the normal physiological functioning of the cell. Various perturbations within these networks have been described in diseases. We will here use original papers to study and discuss how perturbations can be implemented in models and how they change the network characteristics. We will focus on dynamic models described by ordinary differential equations.

  • 19406411 Seminar
    Journal Club: Public Health Data Science (Max von Kleist)
    Schedule: -
    Location: keine Angabe
    

    Comments

    In this seminar, current research in the field of data-driven public health science, as well as the progress reports of PhD students and post-docs, will be presented. Master's students will present either an assigned journal article or their master's thesis, or they will report on their research internship. Credits will be awarded for article presentations only.

    Schedule: online, by arrangement

  • 19406570 Begrüßungs- und Abschlussveranstaltung
    Welcome event for Undergraduate Students of Bioinformatics (Knut Reinert)
    Schedule: Mo 14.10. 10:00-12:00 (Class starts on: 2024-10-14)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Comments

    Am Montag, den 16.10.2023 findet ab 10:15 Uhr eine Einführungsveranstaltung für Neuimmatrikulierte der Informatik statt. Nach der offiziellen Begrüßung des Fachbereichs übernehmen die Mentorinnen und Mentoren mit fach- und studiengangspezifische Informationen und diversen nützlichen Tipps und HInweisen. Außerdem werden das Mentoringprogramm und weitere studentische Initiativen vorgestellt.

    Zielgruppe: Neuimmatrikulierte in einem Informatik-Studiengang (Bachelor)

    Weitere Informationen

  • 19406611 Seminar
    Journal Club: Biomedical Data Science (Katharina Jahn)
    Schedule: Di 16:00-18:00 (Class starts on: 2024-10-15)
    Location: A3/SR 115 (Arnimallee 3-5)
    

    Comments

    In this seminar, we study current research publications in biomedical data science. Master students either present a research article, or their master thesis, or they present about their research internship. Credit points can only be earned for the presentation of research articles.

  • 60100613 Lab Seminar
    Current topics in cell physiology (Dorothee Günzel)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Please bring lab coat, if available!

    Comments

    Block course during the semester break. Next available class: tba (two weeks, all day)

    Location: Charité Campus Benjamin Franklin (Steglitz, Hindenburgdamm 30), Institut für Klinische Physiologie

    For further information: http://klinphys.charite.de/bioinfo/

    or mail to Dorothee Günzel

    Within this course you will generate structural models of proteins by homology modelling. You will develop hypotheses which amino acids should be decisive for the structure.  These Hypotheses will be tested by carrying out molecular biologic experiments (such as site-directed mutagenesis by using two-step PCR). The construct will be cloned into expression vectors, transformed and amplified in bacteria, extracted, sequenced and overexpressed in cultured cells.

    These cells will be analyzed in the confocal laser scanning microscope and by other techniques. The results will be evaluated and interpreted in the context of the original hypitheses.

    The experimental part will be flanked by seminars introducing the theoretical background and the various techniques.

    The exact program of this course depends on the actual research of the institute and is tightly connected to our actual projects.

    Suggested reading

    Milatz S, Piontek J, Hempel C, Meoli L, Grohe C, Fromm A, Lee IM, El-Athman R, Günzel D (2017) Tight junction strand formation by claudin-10 isoforms and claudin-10a/-10b chimeras. Ann. N.Y. Acad. Sci. 1405: 102-115 (https://www.ncbi.nlm.nih.gov/pubmed/28633196)

    Piontek J, Winkler L, Wolburg H, Müller SL, Zuleger N, Piehl C, Wiesner B, Krause G, Blasig IE (2008) Formation of tight junction: determinants of homophilic interaction between classic claudins. FASEB J. 22: 146-158 (https://www.ncbi.nlm.nih.gov/pubmed/17761522)

     

  • 60101113 Lab Seminar
    Current questions of structural Bioinformatics (Robert Preissner, Priyanka Banerjee)
    Schedule: -
    Location: keine Angabe
    

    Comments

    The practical course gives the student a chance to test his or her understanding of the material taught in the theory course. A short introduction on each topic will be given on this course for individual topics. The students will be assigned to a small project/task which they have to perform. The students will be assigned into groups of two/three/max four members, depending on the total number of students registered for the course.

    Website: https://bioinformatics.charite.de/main/course_practical.php

    Structure of the course:

    Everyday students will be assigned projects in groups for each topic. They work together to solve some interesting scientific problem. Each group will be closely supervised by the respective tutors. At the end of the lecture series, students (individual group) will be assigned one of the topic of the course, which they have to present in front of the wider audience. This will provide students, a way to practice presentation skills and can help them to develop the expertise needed to discuss their research in a clear and meaningful way.

    Learning how to answer specific questions and present data to a range of individuals, will help students in other endeavors, including future conference presentations, masters or dissertation defenses.

    Topic for practical lectures are:

    1. Introductory session
    2. Homology modeling
    3. 3D molecular superimposition of small molecules
    4. In silico screening, molecular fingerprints and chemical similarity
    5. Natural products and fragments based drug discovery
    6. In silico toxicity prediction
    7. Personalized medicine

    Important: Material from the theory course will be intensively used in the practical course. It is advisable, that the students need to attend the theory course before participating in the practical course. Both the courses are interlinked.

     

  • 60102001 Lecture
    Methods for clinical trials (N.N.)
    Schedule: Fr 14:00-16:00 (Class starts on: 2024-10-18)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    

    Comments

    In this course, we introduce and discuss statistical methods and study design applied in clinical trials. Basic design aspects like randomization, blinding, the definition of control groups and endpoints will be discussed as well as different study types such as efficacy trials, equivalence and bioequivalence trials, phase I, II and III trials and principles of meta analyses. The related statistical models and test will be introduced as well. The aim of the lectures is to learn about biometrical thinking in the context of clinical trials which includes the application of statistical methods, but also critical thinking on the experimental setting.

  • 60102002 Practice seminar
    Practice seminar for Methods for clinical trials (N.N.)
    Schedule: Fr 16:00-18:00 (Class starts on: 2024-10-18)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    
  • 60102301 Lecture
    Statistical Methods for Small Sample Sizes (Frank Konietschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2024-10-16)
    Location: A6/SR 031 Seminarraum (Arnimallee 6)
    

    Comments

    In this course, we introduce and discuss statistical inference methods for analyzing trials with small sample sizes. We hereby explore the impact of the standard assumption “N is large” and try to find an answer to the question “what means large?” The inference methods will cover estimation of treatment effects, confidence interval computations and hypothesis testing in both parametric and nonparametric models. Rank tests, bootstrap and permutation methods will be investigated in detail as approximation methods. This class aspires to learn about modern statistical tools that were designed to make accurate conclusions when sample sizes are rather small.

     

  • 60102302 Practice seminar
    Practice seminar for Statistical Methods for Small Sample Sizes (Frank Konietschke)
    Schedule: Mi 16:00-18:00 (Class starts on: 2024-10-16)
    Location: A6/SR 031 Seminarraum (Arnimallee 6)
    
  • 60102401 Lecture
    Foundations in Bio-Medicine (Martin Atta Mensah)
    Schedule: Mi 10:00-12:00 (Class starts on: 2024-10-16)
    Location: A6/SR 031 Seminarraum (Arnimallee 6)
    
  • 60102402 Practice seminar
    Practice Seminar for Foundations in Bio-Medicine (Martin Atta Mensah)
    Schedule: Mi 12:00-14:00 (Class starts on: 2024-10-16)
    Location: A6/SR 031 Seminarraum (Arnimallee 6)
    
  • 60103101 Lecture
    Complex Systems in Biomedical Applications (Dorothee Günzel, Mathias Steinach)
    Schedule: Mo 14:00-16:00
    Location: Charité
    

    Comments

    Joint class taught by the Institute of Clinical Physiology and the Institute of Physiology at the Charité. The course will be split into two segments: the first seven appointments in the semester will take place at the Institute of Physiology, while the second seven appointments will take place at the Institute of Clinical Physiology.

    For further information: http://klinphys.charite.de/bioinfo/

    or mail to Dorothee Günzel

    Contents:

    Using selected, up-to-date examples from biology and physiology, the work steps from data acquisition, data processing, data preparation, data assessment to the modeling of complex physiological relationships are studied theoretically and practically. Models from the following areas are dealt with in more detail:

    - Basic biophysical and biochemical processes (e.g. free and facilitated diffusion through channel and transport proteins, active ion transport through membrane transporters, receptor-ligand interaction, interaction of structural and motor proteins)

    - Structure-function analysis of transport proteins

    - Biological networks (e.g. signal networks, metabolic networks, transportome models, feedback-mechanisms)

    - Modeling physiological functions of an organism (e.g. mass transfer to the kidney, blood- and immune-function, muscle movement, temperature regulation, circadian rhythm, cardiac- and circulatory function, autonomic regulation / heart-rate-variability, body-composition)

  • 60103102 Practice seminar
    Practice Seminar for Complex Systems in Biomedical Applications (Dorothee Günzel, Mathias Steinach)
    Schedule: Mo 16:00-18:00
    Location: Charité
    
  • 60103201 Lecture
    Structural Bioinformatics Methods in Drug Development (Robert Preissner, Priyanka Banerjee)
    Schedule: -
    Location: keine Angabe
    

    Comments

    Course overview:

    Website: https://bioinformatics.charite.de/main/course_theoretical.php

    The Structural Bioinformatics Group offers a broad and comprehensive set of lectures in the areas of structural bioinformatics and drug design. The course begins with a general introduction of the drug design pipeline and an introductory course on the structural bioinformatics research field. These lead on to more specialized topics, amongst others in chemo-informatics, molecular docking, homology modeling and more detailed aspects of toxicity prediction models.

    Structure of the course:

    This course consists of eight lecture series. A detailed lecture for a period of 2 hrs on individual topics is delivered in the morning session. Afternoon session consists of an assignment for each topic. This part of the lecture course is assessed by examination, which will take place at the end of the course. Students are asked to delivered a seminar/presentation for 25 minutes, on the topic assigned to them. The material for the examination will be provided in advance, ensuring that the students have required time for preparation.

    Topics for lectures are:

    • 1. Introductory session
    • 2. Peptide design
    • 3. Homology modeling
    • 4. 3D Molecular superimposition of small molecules
    • 5. In silico screening, molecular fingerprints and chemical similarity
    • 6. Molecular docking
    • 7. Natural products and fragments based drug discovery
    • 8. In silico toxicity prediction

  • 60103202 Practice seminar
    Practice seminar for Structural Bioinformatics Methods in Drug Development (Robert Preissner, Priyanka Banerjee)
    Schedule: -
    Location: keine Angabe