Contents: We begin with the notion of an algorithm, and we describe the cycle from problem statement to algorithmic solution to working code. We consider numerous examples that illustrate fundamental principles of algorithm design. In order to implement our algorithms, we introduce the functional programming language Haskell. Additionally, we explore the theoretical, technological, and organizational principles of computer systems. Topics covered include the binary representation of information in a computer, Boolean functions and their implementation as circuits, the design principles of CPUs, and the von-Neumann-architecture.

Prerequisites: We recommend that participants of this class attend the Brückenkurs Mathematical Foundations of Computer Science and Bioinformatics.

• S. Thompson; Haskell: The Craft of Functional Programming; Addison-Wesley
• F. Rabhi, G. Lapalme; Algorithms: A Functional Proramming Approach; Addison-Wesley
• G. Hutton; Programming in Haskell; Cambridge University Press
• A. Tanenbaum, J. Goodman; Computerarchitektur; Pearson Studium

This lecture deals with: Exact and approximative string matching, dynamic programming and scoring schemata, finite automata and formal languages, pairwise und multiple alignment, multiple string matching, basics of Markov Chains und Hidden Markov Models, algorithms for fast search in sequence data bases.

In the exercises the above topics will be deepened, and techniques of analysis and evidence will be practised.

There is an associated practical course "Algorithmen und Datenstrukturen" (19401330). Please check there for further information!

Please see German description.

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.

See German text.

Inhalt:

Aussagenlogik und mathematische BeweistechnikenMengenlehre: Mengen, Relationen, Äquivalenz- und Ordnungsrelationen,   Funktionen
Natürliche Zahlen und vollständige Induktion, Abzählbarkeit
Kombinatorik: Abzählprinzipien, Binomialkoeffizienten und Stirling-Zahlen,   Rekursion, Schubfachprinzip
Lineare Algebra: Vektorraum, Basis und Dimension; lineare Abbildung,   Matrix und Rang; Gauss-Elemination und lineare Gleichungssysteme;   Determinanten, Eigenwerte und Eigenvektoren; Euklidische Vektorräume und   Orthonormalisierung; Hauptachsentransformation;Anwendungen der linearen Algebra in der affinen Geometrie

Zielgruppe:  Studierende der Bioinformatik im 1. Semester

Voraussetzungen:  Empfohlen wird der Besuch des Brückenkurses 19320973: Mathematische Grundlagen für Informatik, Bioinformatik und Nebenfach Informatik

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

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

Content:

see German desciption

Goals: Students will gain a deeper understanding for mathematical concepts and methods in advanced algorithmics related to state of the art  research in bioinformatics. They will be acquainted with advanced tools for the development and analysis of deterministic and randomized algorithms. They are able to recognize various concepts and to apply the methods of analysis to similar problems. 

Contents: This lecture introduces different sorts of algorithms and analysis methods like advanced graph algorithms, the analysis of randomized datastructures, and hashing algorithms.

For MSc students in Bioinformatics

Content

    Methods for genome assembly and metagenome assembly
    Approximate, semiglobal alignments (read mapping)
    Identification of genetic variations (SNVs, structural variants and copy number alterations)
    Quantification problems with next generation sequencing data
    NGS protocols for different purposes: DNAseq, RNAseq, ChIPseq, from 3C to Hi-C

Content

• differential equation modeling in systems biology
• stiff and non-stiff ordinary differential equations (ODEs)
• numerical integrators (introduction to theory, strengths and weaknesses of different methods)
• parameter identification 

Literatur

• Darren J. Wilkinson: Stoachstic Modelling for Systems Biology. Chapman & Hall/CRC

• Peter Deuflhard, Susanna Röblitz: A Practical Guide to Numerical Modeling in Systems Biology.

Prerequisites

• basic knowledge of Numerics

Linear programming, Simplex algorithm, duality, integer linear programming, branch and bound, cutting planes, branch and cut, constraint programming, local search and metaheuristics.

The students should get a deeper understanding of advanced mathematical notions and methods in discrete mathematics and optimisation. They should be able to develop discrete mathematical models for problems in bioinformatics and systems biology, to apply suitable algorithms for their solution, and to analyse the results.

Linear programming, Simplex algorithm, duality, integer linear programming, branch and bound, cutting planes, branch and cut, constraint programming, local search and metaheuristics

The students should get a deeper understanding of advanced mathematical notions and methods in discrete mathematics and optimisation. They should be able to develop discrete  mathematical models for problems in bioinformatics and systems biology, to apply suitable algorithms for their solution, and to analyse the results.

 In this class we focus on advanced methods and mathematical background in statistics. Main topics are theory of Markov chains, Markov chain Monte Carlo methods, non-parametrical procedures and methods for statistical learning.

Please contact your advisor.

Further information on our homepage.

Block course during the semester break. Next available class: March 4 - March 15, 2019 (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.

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)

Please bring lab coat, if available!

Practical Course: Using open source software and libraries for data analysis and computer-aided drug design

This practical course introduces the students to diverse software tools and libraries which can support data generation and analysis in various areas of computer-aided drug design.  The course will sensitize the students to the ease and the profit of using bio-/cheminformatics methods.

The course shall enable the students to set-up their own drug design pipeline including protein target preparation, compound library set-up and filtering (i.e. using drug-like and toxicity filters), docking of the compounds to the target and evaluation of the results. The course will include the following tasks:

• There will be a short introductory part into python programming using the novel and interactive IPython notebooks.
• The students will write their own scripts using, e.g., python libraries for data handling (pandas), protein (BioPython) and compound (RDKit) processing as well as machine learning (scikit-learn) to prepare their compound libraries.  
• Open access tools for protein structure preparation and visual inspection (PyMol) will be used.
• AutoDock software will be engaged for docking of the compounds into the target protein and the results will be evaluated.   

Each day, we will perform a small task from the described computer-aided drug design pipeline (morning lecture followed by practical work asn presentation). The students can work individually or in groups, depending on the total number of participants.

Practical course date: 25.02.-01.03.2019, 5 days, daily 9 am - 5 pm.
Preliminary meeting: In early February, exact date will be announced soon.

Place: Campus Mitte, Vorchowweg 6 (or surrounding Charité Campus), 10117 Berlin

Research AG Volkamer

Content:

The course focuses on the modeling of molecular networks using discrete/logical approaches. The theoretical framework will be introduced and software tools presented. On the basis of suitable research articles, the participants will conduct their own modeling project in small groups.

Target group:

Students of Master Bioinformatics from the 2nd semester.

Welcome to the practical course, please look into the link for the theory module for the basic idea about the course.

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.

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

Website: http://bioinf-apache.charite.de/main/course_practical.php

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.

Max.no of particpants: 12

Language of instructtion: English

Practical course: 11.03. - 22.04.2019, 7 days during 2 weeks, daily 10 am - 5 pm

Preliminary meeting:

• Date: 11.03.2019
• Time: 11.00 am
• Place: Campus Mitte, Philippstr. 12, 10115 Berlin

website : http://bioinf-apache.charite.de/main/course_practical.php

The goal of this course is to give an introduction to the most important mathematical and algorithmic ideas underlying the constraint-based analysis of genome-scale metabolic networks, with applications to systems biology and biotechnology.

We will discuss the steady-state flux cone, flux balance analysis (FBA), flux variability analysis (FVA), flux coupling analysis (FCA), thermodynamic constraints, elementary flux modes (EFMs), and optimality principles for metabolic regulation. On the algorithmic side, the focus will be on linear and mixed-integer optimisation methods.

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 "Fortgeschrittenenpraktikum". Credits are only awarded for the presentation of papers.

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

Literature:

Current reading in Computational Biology.

Open for:

Master and PhD students

Content:

In modern life sciences, ever-increasing data collections have been generated in recent years. The problems are shifting from data generation to data analysis: in the past, biological experiments or medical data collection were the most time-consuming steps, today it is the runtimes of the analysis algorithms used.

In this course we will deal with the theoretical foundations as well as the practical application of current techniques for modelling and analysis of such large data collections.

In cooperation with the research campus MODAL, the project will be a fictitious but realistic one in which many aspects of a modern analysis pipeline will be considered and developed in practice.

Aims:

After attending this course, the students should be in a position to do so:

    to work on a problem in the field of data sciences from the definition of the problem to the actual solution. The aim is to demonstrate data collection and processing capabilities and to develop and implement a solution.
    to present the corresponding material in two presentations: (a) the solution approach and (b) the implemented solution.

Target group:

Master students of bioinformatics, mathematics and related disciplines

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.

This seminar is a mix of student talks on currents topics related to pathophysiology in the context of bioinformatics and evolution and contributions from lecturers of the Institute of Clinical Physiology.

Further information on this seminar (location, dates): http://klinphys.charite.de/bioinfo/

or mail to Dorothee Günzel

Depending on the wishes of the students the seminar will be either held regularly during term or as a block during winter break. This will be determined during the introduction at the beginning of winter term (18.10.2019, 14.00, Charité CBF, room 5573) .

Current program/topics (last term's program, respectively): https://klinphys.charite.de/bioinfo/3_k-pathophy-fromm/s_pphy_0.htm

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.

This seminar serves to introduce different biological, clinical and computational topics related to cancer bioinformatics.

We will discuss some notions of cancer biology (hallmarks of cancer, pathways, etc), specific characteristics of tumor data, and above all computational approaches and methods used for analyzing such data (e.g., Kaplan-Meier plots, b-allele frequencies, identification of recurrent mutations, estimation of sample purity, tumor and sample heterogeneity, etc.).

Each participant will be required to present a specific topic. Instead of presenting one specific paper (like in a journal club), however, the focus will lie on a critical discussion of the topic (e.g., pros and cons of a method, uses cases where it can be applied, examples of how it has been used, etc.). This will involve some literature search.

A short list of references for the individual topics will be distributed in the first session.

The seminar is about the different layers of gene regulation, including functional genomic elements (e.g. promoters and enhancers), DNA accessibility, transcription factors, epigenetic marks and the three-dimensional genome organization. The seminar will cover the underlying biology, experimental methods and the bioinformatics to analyze data from these experiments. The students will work themselves into selected topics from the field of gene regulation and give presentations.

The goal of this course is to give an introduction to the most important mathematical and algorithmic ideas underlying the constraint-based analysis of genome-scale metabolic networks, with applications to systems biology and biotechnology.

We will discuss the steady-state flux cone, flux balance analysis (FBA), flux variability analysis (FVA), flux coupling analysis (FCA), thermodynamic constraints, elementary flux modes (EFMs), and optimality principles for metabolic regulation. On the algorithmic side, the focus will be on linear and mixed-integer optimisation methods.

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 "Fortgeschrittenenpraktikum". Credits are only awarded for the presentation of papers.

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

Literature:

Current reading in Computational Biology.

Open for:

Master and PhD students

Content:

In modern life sciences, ever-increasing data collections have been generated in recent years. The problems are shifting from data generation to data analysis: in the past, biological experiments or medical data collection were the most time-consuming steps, today it is the runtimes of the analysis algorithms used.

In this course we will deal with the theoretical foundations as well as the practical application of current techniques for modelling and analysis of such large data collections.

In cooperation with the research campus MODAL, the project will be a fictitious but realistic one in which many aspects of a modern analysis pipeline will be considered and developed in practice.

Aims:

After attending this course, the students should be in a position to do so:

    to work on a problem in the field of data sciences from the definition of the problem to the actual solution. The aim is to demonstrate data collection and processing capabilities and to develop and implement a solution.
    to present the corresponding material in two presentations: (a) the solution approach and (b) the implemented solution.

Target group:

Master students of bioinformatics, mathematics and related disciplines

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.

This seminar is a mix of student talks on currents topics related to pathophysiology in the context of bioinformatics and evolution and contributions from lecturers of the Institute of Clinical Physiology.

Further information on this seminar (location, dates): http://klinphys.charite.de/bioinfo/

or mail to Dorothee Günzel

Depending on the wishes of the students the seminar will be either held regularly during term or as a block during winter break. This will be determined during the introduction at the beginning of winter term (18.10.2019, 14.00, Charité CBF, room 5573) .

Current program/topics (last term's program, respectively): https://klinphys.charite.de/bioinfo/3_k-pathophy-fromm/s_pphy_0.htm

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.

This seminar serves to introduce different biological, clinical and computational topics related to cancer bioinformatics.

We will discuss some notions of cancer biology (hallmarks of cancer, pathways, etc), specific characteristics of tumor data, and above all computational approaches and methods used for analyzing such data (e.g., Kaplan-Meier plots, b-allele frequencies, identification of recurrent mutations, estimation of sample purity, tumor and sample heterogeneity, etc.).

Each participant will be required to present a specific topic. Instead of presenting one specific paper (like in a journal club), however, the focus will lie on a critical discussion of the topic (e.g., pros and cons of a method, uses cases where it can be applied, examples of how it has been used, etc.). This will involve some literature search.

A short list of references for the individual topics will be distributed in the first session.

The seminar is about the different layers of gene regulation, including functional genomic elements (e.g. promoters and enhancers), DNA accessibility, transcription factors, epigenetic marks and the three-dimensional genome organization. The seminar will cover the underlying biology, experimental methods and the bioinformatics to analyze data from these experiments. The students will work themselves into selected topics from the field of gene regulation and give presentations.

ENGLISH: 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.

GERMAN: Diese Vorlesung dient der Einführung in raumbezogene Datenbanken, wie sie insbesondere in geographischen Informationssystemen (GIS) Verwendung finden. Schwerpunkte sind u.a. die Modellierung raumbezogener Daten, Anfragesprachen und Optimierung sowie raumbezogene Zugriffsmethoden und Navigationssysteme ("Location-based services"). Grundwissen in Datenbanken ist erforderlich. Die Vorlesung beinhaltet Übungsblätter und Rechnerpraktika mit PostGIS.

Sonstiges: Die Vorlesung wird in englischer Sprache gehalten

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)

Zielgruppe: Studierende im Masterstudiengang

Voraussetzungen: Vorlesung: Einf. in Datenbanksysteme

The class focuses on topics such as

• general principles of algorithm design,
• network flows,
• number-theoretic algorithms (including the RSA crypto system),
• string matching,
• NP-completeness,
• approximation algorithms for hard problems,
• arithmetic algorithms and circuits, fast fourier transform.

• Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms, 2nd Ed. McGraw-Hill 2001
• Kleinberg, Tardos: Algorithm Design Addison-Wesley 2005.

Target audience

All Master and Bachelor students who are interested in algorithms.

Prerequisites

Basic familiarity with the design and analysis of algorithms.

Work and Life Tools

In this course we will shed light on those questions which decisively influence a successful course of action in one's studies and profession and the success and contentment in private life.

These are mostly less technical abilities but rather characteristics: purposefullness, self confidence, ability to concentrate and relax, decision-making ability, clear communication, self-perception, motivation, stamina.

The purpose of this course is to trigger and improve a purposeful and self-motivated personal development.

Furthermore, it is explained how and why great parts of the so-called soft skills arise almost independently when developing the above-mentioned abilities.

This course is a seminar in the original sense: mainly a discussion in which each participant explores something on his/her own (in this case his/her own behavior). However, the format differs completely to what the title "Seminar" ususally suggests in Computer Science: there are no topics assigned, no presentations, no papers. It is about ...  (Es geht um Bildung, nicht um Ausbildung)

The number of participants is limited; prior registration is necessary. The course requires study experience and therefor cannot be attended by first semesters.

I expect an open and commited particpation of all particpants. The course demands only a moderate expenditure of time, but a considerable input of will power.

wird in der Veranstaltung bekannt gegeben

Duration

The weekly lecture is of three hours length.

Language

The course language is German.

Homepage

http://www.inf.fu-berlin.de/w/SE/KursArbeitsUndLebensmethodik2018

The lecture focuses on the interface between technology and society with respect to security solutions in different fields. Based on selected examples of research and development projects we shed light on the subjective perceptions of such technologies and the often unintended side effects they provoke. Moreover we will discuss why some technical solutions are socially more accepted than others. The lecture will bring together social science approaches of dealing with uncertainty and risk perception with technical case examples in an interdisciplinary manner.

Information for students:

Limited to a maximum of 20 participants

The lecture will be held in german.

Work and Life Tools

In this course we will shed light on those questions which decisively influence a successful course of action in one's studies and profession and the success and contentment in private life.

These are mostly less technical abilities but rather characteristics: purposefullness, self confidence, ability to concentrate and relax, decision-making ability, clear communication, self-perception, motivation, stamina.

The purpose of this course is to trigger and improve a purposeful and self-motivated personal development.

Furthermore, it is explained how and why great parts of the so-called soft skills arise almost independently when developing the above-mentioned abilities.

This course is a seminar in the original sense: mainly a discussion in which each participant explores something on his/her own (in this case his/her own behavior). However, the format differs completely to what the title "Seminar" ususally suggests in Computer Science: there are no topics assigned, no presentations, no papers. It is about ...  (Es geht um Bildung, nicht um Ausbildung)

The number of participants is limited; prior registration is necessary. The course requires study experience and therefor cannot be attended by first semesters.

I expect an open and commited particpation of all particpants. The course demands only a moderate expenditure of time, but a considerable input of will power.

wird in der Veranstaltung bekannt gegeben

Duration

The weekly lecture is of three hours length.

Language

The course language is German.

Homepage

http://www.inf.fu-berlin.de/w/SE/KursArbeitsUndLebensmethodik2018

 I – LEARNING OBJECTIVES

This course introduces the fundamentals of technology entrepreneurship. Students will learn about the process technology entrepreneurs use to start innovative companies, e.g. Design Thinking, Effectuation or Business Modelling. To gain practical experience alongside the theory, students form teams together with engineers and scientists from Freie Universität Berlin (FU) and/or with Berlin-based companies. In these interdisciplinary teams, students will have the opportunity to experience hands-on interdisciplinary collaboration by developing real life innovation. The module is part of ESCP Europe’s and FU Berlin’s joint InnoBridge initiative (www.berlin-innobridge.de). Its ultimate goal is to foster the creation of technology based innovation in interdisciplinary teams.

II – LEARNING OUTCOMES

This course permits students to learn how technological innovations can be developed on the basis of current trends, new technologies and existing businesses. In particular, students will achieve the following learning goals:

• method competencies of technology entrepreneurship
• professional competences on the basis practical experience of the application of these methods in real life cases
• interdisciplinary collaboration with company representatives as well as researchers

III – CONTENT

The course at hand views the interdisciplinary team building as part of the entrepreneurial process and will draw on the latest methods of innovation management as well as entrepreneurship research. During this course students will develop tangible innovation concepts together with managers and researchers. The course is split into four components:

• methodological lectures
• visits to companies and research institutes
• work in project teams
• participation in InnoBridge events (InnoMatch, InnoDrive, DemoDay)

IV – TEACHING METHODS

This course uses a broad range of teaching methods to empower students for their technology innovation challenges:

• Readings, lectures and class discussions on concepts and tools
• Real-life cases of entrepreneurial ventures
• Group works to apply newly acquired knowledge and strengthen soft skills
• Peer-to- peer workshops
• Industry experts as guest speakers

During the work in project teams as well as during the InnoBridge events, all teams will have access to experienced mentors.

V - ABLAUF

The course will take place from January 2019 to March 2019. A preparation date will probably be offered on 24.10.2018 at 5 pm. 

Expected course of events:

January
1. Preparation: Introduction to Technology Entrepreneurship (at FU Berlin)
2. Preparation: Roles and Processes in Technology Entrepreneurship (at FU Berlin)

February
3. InnoMatch (at ESCP Europe)
4. Technology and Product (at ESCP Europe)
5. Market, Competition and Marketing (at ESCP Europe)

March
6. Pitching (at ESCP Europe)
7. Intellectual Property (at ESCP Europe)
8. Demo Day (at ESCP Europe)
9. Follow-up: Debriefing and Follow-ups

VI – ASSESSMENT METHODS

The course is graded as follows:

• Project team work including management of interdisciplinary collaboration (50 %)
• Individual participation, involvement and co-creation (25 %)
• Individual reflection paper (25 %)

The course is considered validated if the overall average grade is above 10/20 and if none of the module grades are inferior or equal to 7/20.

• Brown, T., & Katz, B. (2011). Change by Design. Journal of Product Innovation Management, 28(3), 381–383.
• Grichnik, D., Brettel, M., Koropp, C. & Mauer, R. (2010). Entrepreneurship: Unternehmerisches Denken, Entscheiden und Handeln in innovativen und technologieorientierten Unternehmungen. Schäffer-Poeschel Verlag.
• Hoffmann, C., Lennerts, S., Schmitz, C., Stölzle, W., & Uebernickel, F. (ed.). (2016). Business Innovation: das St. Galler Modell. Springer Gabler.
• Osterwalder, A., & Pigneur, Y. (2010). Business model generation: a handbook for visionaries, game changers, and challengers. John Wiley & Sons.
• Osterwalder, A., Pigneur, Y., Bernarda, G., & Smith, A. (2014). Value proposition design. Strategyzer series. John Wiley & Sons.
• Plattner, H., Meinel, C., & Leifer, L. (ed.). (2012). Design Thinking Research. Springer Berlin.
• Ries, E. (2011). The lean startup: How today’s entrepreneurs use continuous innovation to create radically successful businesses. Random House LLC.
• Schmiedgen, J., Köppen, E., & Meinel, C. (2015). Parts Without a Whole? Technische Berichte des Hasso-Plattner-Instituts für Softwaresystemtechnik an der Universität Potsdam, 97.

The lecture focuses on the interface between technology and society with respect to security solutions in different fields. Based on selected examples of research and development projects we shed light on the subjective perceptions of such technologies and the often unintended side effects they provoke. Moreover we will discuss why some technical solutions are socially more accepted than others. The lecture will bring together social science approaches of dealing with uncertainty and risk perception with technical case examples in an interdisciplinary manner.

Information for students:

Limited to a maximum of 20 participants

The lecture will be held in german.

The professional life of almost each graduate of computer science will be comprised of software development or other computer technology related work organized in projects. Leading and being responsible for more or less big projects are important milestones in many career paths of computer scientists.

There is a number of widely accepted methodologies, tools and practices which can be applied to the variety of routine tasks and challenges within projects. The Project Management Institute has collected and systematized knowledge about project management and published it in the “Guide to the Project Management Body of Knowledge (PMBoK Guide)” as an ANSI standard.

Based on the PMBOK as a systematic blueprint this lecture covers the most important processes of project management throughout the typical lifecycle of a project. An accompanying case study as well as sample real life cases help understanding theoretical concepts.

There is a wide variety of software tools supporting project work. The lecture also covers typical tools one would use during a project. We will look more deeply at Microsoft Project as one of the most widespread project management tools.

The lecture series is split into two parts:

In winter term we cover basics of project management. The lecture shall enable participants to become a qualified project management assistant

• Project setup, -definition, scope planning
• Project time and cost planning
• Project controlling and monitoring
• Project status collection and reporting
• Procurement
• Project organization
• Project closure
• Usage of MS Project for these areas

The lecture during winter term is feasible for bachelor (Modul: Grundlagen des Managements von IT-Projekten) as well as master students (Modul: Projektmanagement).

A Guide to the Project Management Body of Knowledge - Fourth Edition (Project Management Institute), 2008

Homepage

https://www.mi.fu-berlin.de/w/SE/VorlesungGrundlagenProjektmanagement2018

Summary

This class gives an introduction to programming in C++ and in the second half also teaches some intermediate skills. No previous knowledge of C++ (or C) is required, but we assume that you have at least some general programming experience.

Target audience

1. Bioinformatics Bachelor students before their third semester (unless they are proficient in C++)
2. Bioinformatics Master students before their first semester if they did not learn C++ in their Bachelor's program (e.g. if they did not study at FUB before) [highly recommended, but you won't get credits]
3. anyone else interested in learning C++ (e.g. Informatics Bachelor students) provided there is sufficient space [they can get credits as ABV]

Language of the lectures and tests is English, but all teachers also speak German.

Timeframe

30.09.2018 Deadline for sign up in the KVV

08.10.2018 - 12.10.2018 (one week before the semester)

25.02.2019 - 08.03.2019 (two weeks after the semester)

Every day 10:00 - 12:00 (lecture) and 13:00 - 17:00 (computer lab)

It is possible to attend only the first week, but if you plan on doing so, please do not register for the class to not take away someone's place who wants to attend the full course. [Obviously you will also not get credits for attending only the first week]

Credits

There is a test at the end of each week. To receive the credits for this class (5 ECTS) you need to get at least 50% of the combined points of all three tests. There is no grade, only pass (or fail).

Topics (WIP)

1. Week (crash course)

• C++ Overview (History, paradigms, "Modern C++")
• Compilers and basics of the build process
• Types, variables, constants, references, initialisation, arithmetics
• basic I/O
• Loops, control statements
• Functions and functions objects
• simple class types
• simple class and function templates
• STL container types

2. Week

• Memory model, stack vs heap, pointer types, new and delete, rvalue references
• OOP (Inheritance,virtual functions and abstract base classes)
• compile time programming (constexpr and more templates)

3. Week

• Parallelisation
• performance optimisations and profiling
• Error handling and exceptions
• alternatives to OOP (CRTP and possibly C++20 Concepts)

Recommended reading

• Start here: https://isocpp.org/tour (the first lectures are based on the tour)
• The "Super-FAQ" (https://isocpp.org/faq) covers very many questions, both, new and intermediate programmers might have, as well as hints for people coming from other programming languages
• CPPReference: https://en.cppreference.com/w/ (difficult to read in the beginning, but very useful once you get used to the style)

See German text.

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.

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

For further information see german text version.

Work and Life Tools

In this course we will shed light on those questions which decisively influence a successful course of action in one's studies and profession and the success and contentment in private life.

These are mostly less technical abilities but rather characteristics: purposefullness, self confidence, ability to concentrate and relax, decision-making ability, clear communication, self-perception, motivation, stamina.

The purpose of this course is to trigger and improve a purposeful and self-motivated personal development.

Furthermore, it is explained how and why great parts of the so-called soft skills arise almost independently when developing the above-mentioned abilities.

This course is a seminar in the original sense: mainly a discussion in which each participant explores something on his/her own (in this case his/her own behavior). However, the format differs completely to what the title "Seminar" ususally suggests in Computer Science: there are no topics assigned, no presentations, no papers. It is about ...  (Es geht um Bildung, nicht um Ausbildung)

The number of participants is limited; prior registration is necessary. The course requires study experience and therefor cannot be attended by first semesters.

I expect an open and commited particpation of all particpants. The course demands only a moderate expenditure of time, but a considerable input of will power.

wird in der Veranstaltung bekannt gegeben

Duration

The weekly lecture is of three hours length.

Language

The course language is German.

Homepage

http://www.inf.fu-berlin.de/w/SE/KursArbeitsUndLebensmethodik2018

 I – LEARNING OBJECTIVES

This course introduces the fundamentals of technology entrepreneurship. Students will learn about the process technology entrepreneurs use to start innovative companies, e.g. Design Thinking, Effectuation or Business Modelling. To gain practical experience alongside the theory, students form teams together with engineers and scientists from Freie Universität Berlin (FU) and/or with Berlin-based companies. In these interdisciplinary teams, students will have the opportunity to experience hands-on interdisciplinary collaboration by developing real life innovation. The module is part of ESCP Europe’s and FU Berlin’s joint InnoBridge initiative (www.berlin-innobridge.de). Its ultimate goal is to foster the creation of technology based innovation in interdisciplinary teams.

II – LEARNING OUTCOMES

This course permits students to learn how technological innovations can be developed on the basis of current trends, new technologies and existing businesses. In particular, students will achieve the following learning goals:

• method competencies of technology entrepreneurship
• professional competences on the basis practical experience of the application of these methods in real life cases
• interdisciplinary collaboration with company representatives as well as researchers

III – CONTENT

The course at hand views the interdisciplinary team building as part of the entrepreneurial process and will draw on the latest methods of innovation management as well as entrepreneurship research. During this course students will develop tangible innovation concepts together with managers and researchers. The course is split into four components:

• methodological lectures
• visits to companies and research institutes
• work in project teams
• participation in InnoBridge events (InnoMatch, InnoDrive, DemoDay)

IV – TEACHING METHODS

This course uses a broad range of teaching methods to empower students for their technology innovation challenges:

• Readings, lectures and class discussions on concepts and tools
• Real-life cases of entrepreneurial ventures
• Group works to apply newly acquired knowledge and strengthen soft skills
• Peer-to- peer workshops
• Industry experts as guest speakers

During the work in project teams as well as during the InnoBridge events, all teams will have access to experienced mentors.

V - ABLAUF

The course will take place from January 2019 to March 2019. A preparation date will probably be offered on 24.10.2018 at 5 pm. 

Expected course of events:

January
1. Preparation: Introduction to Technology Entrepreneurship (at FU Berlin)
2. Preparation: Roles and Processes in Technology Entrepreneurship (at FU Berlin)

February
3. InnoMatch (at ESCP Europe)
4. Technology and Product (at ESCP Europe)
5. Market, Competition and Marketing (at ESCP Europe)

March
6. Pitching (at ESCP Europe)
7. Intellectual Property (at ESCP Europe)
8. Demo Day (at ESCP Europe)
9. Follow-up: Debriefing and Follow-ups

VI – ASSESSMENT METHODS

The course is graded as follows:

• Project team work including management of interdisciplinary collaboration (50 %)
• Individual participation, involvement and co-creation (25 %)
• Individual reflection paper (25 %)

The course is considered validated if the overall average grade is above 10/20 and if none of the module grades are inferior or equal to 7/20.

• Brown, T., & Katz, B. (2011). Change by Design. Journal of Product Innovation Management, 28(3), 381–383.
• Grichnik, D., Brettel, M., Koropp, C. & Mauer, R. (2010). Entrepreneurship: Unternehmerisches Denken, Entscheiden und Handeln in innovativen und technologieorientierten Unternehmungen. Schäffer-Poeschel Verlag.
• Hoffmann, C., Lennerts, S., Schmitz, C., Stölzle, W., & Uebernickel, F. (ed.). (2016). Business Innovation: das St. Galler Modell. Springer Gabler.
• Osterwalder, A., & Pigneur, Y. (2010). Business model generation: a handbook for visionaries, game changers, and challengers. John Wiley & Sons.
• Osterwalder, A., Pigneur, Y., Bernarda, G., & Smith, A. (2014). Value proposition design. Strategyzer series. John Wiley & Sons.
• Plattner, H., Meinel, C., & Leifer, L. (ed.). (2012). Design Thinking Research. Springer Berlin.
• Ries, E. (2011). The lean startup: How today’s entrepreneurs use continuous innovation to create radically successful businesses. Random House LLC.
• Schmiedgen, J., Köppen, E., & Meinel, C. (2015). Parts Without a Whole? Technische Berichte des Hasso-Plattner-Instituts für Softwaresystemtechnik an der Universität Potsdam, 97.

The lecture focuses on the interface between technology and society with respect to security solutions in different fields. Based on selected examples of research and development projects we shed light on the subjective perceptions of such technologies and the often unintended side effects they provoke. Moreover we will discuss why some technical solutions are socially more accepted than others. The lecture will bring together social science approaches of dealing with uncertainty and risk perception with technical case examples in an interdisciplinary manner.

Information for students:

Limited to a maximum of 20 participants

The lecture will be held in german.

The professional life of almost each graduate of computer science will be comprised of software development or other computer technology related work organized in projects. Leading and being responsible for more or less big projects are important milestones in many career paths of computer scientists.

There is a number of widely accepted methodologies, tools and practices which can be applied to the variety of routine tasks and challenges within projects. The Project Management Institute has collected and systematized knowledge about project management and published it in the “Guide to the Project Management Body of Knowledge (PMBoK Guide)” as an ANSI standard.

Based on the PMBOK as a systematic blueprint this lecture covers the most important processes of project management throughout the typical lifecycle of a project. An accompanying case study as well as sample real life cases help understanding theoretical concepts.

There is a wide variety of software tools supporting project work. The lecture also covers typical tools one would use during a project. We will look more deeply at Microsoft Project as one of the most widespread project management tools.

The lecture series is split into two parts:

In winter term we cover basics of project management. The lecture shall enable participants to become a qualified project management assistant

• Project setup, -definition, scope planning
• Project time and cost planning
• Project controlling and monitoring
• Project status collection and reporting
• Procurement
• Project organization
• Project closure
• Usage of MS Project for these areas

The lecture during winter term is feasible for bachelor (Modul: Grundlagen des Managements von IT-Projekten) as well as master students (Modul: Projektmanagement).

A Guide to the Project Management Body of Knowledge - Fourth Edition (Project Management Institute), 2008

Homepage

https://www.mi.fu-berlin.de/w/SE/VorlesungGrundlagenProjektmanagement2018

Summary

This class gives an introduction to programming in C++ and in the second half also teaches some intermediate skills. No previous knowledge of C++ (or C) is required, but we assume that you have at least some general programming experience.

Target audience

1. Bioinformatics Bachelor students before their third semester (unless they are proficient in C++)
2. Bioinformatics Master students before their first semester if they did not learn C++ in their Bachelor's program (e.g. if they did not study at FUB before) [highly recommended, but you won't get credits]
3. anyone else interested in learning C++ (e.g. Informatics Bachelor students) provided there is sufficient space [they can get credits as ABV]

Language of the lectures and tests is English, but all teachers also speak German.

Timeframe

30.09.2018 Deadline for sign up in the KVV

08.10.2018 - 12.10.2018 (one week before the semester)

25.02.2019 - 08.03.2019 (two weeks after the semester)

Every day 10:00 - 12:00 (lecture) and 13:00 - 17:00 (computer lab)

It is possible to attend only the first week, but if you plan on doing so, please do not register for the class to not take away someone's place who wants to attend the full course. [Obviously you will also not get credits for attending only the first week]

Credits

There is a test at the end of each week. To receive the credits for this class (5 ECTS) you need to get at least 50% of the combined points of all three tests. There is no grade, only pass (or fail).

Topics (WIP)

1. Week (crash course)

• C++ Overview (History, paradigms, "Modern C++")
• Compilers and basics of the build process
• Types, variables, constants, references, initialisation, arithmetics
• basic I/O
• Loops, control statements
• Functions and functions objects
• simple class types
• simple class and function templates
• STL container types

2. Week

• Memory model, stack vs heap, pointer types, new and delete, rvalue references
• OOP (Inheritance,virtual functions and abstract base classes)
• compile time programming (constexpr and more templates)

3. Week

• Parallelisation
• performance optimisations and profiling
• Error handling and exceptions
• alternatives to OOP (CRTP and possibly C++20 Concepts)