Centre for Integrative BioInformatics IBIVU Bioinformatics Masters in The Netherlands Contents: Nine bioinformatics Masters programmes at eight Dutch universities.

Slides:



Advertisements
Similar presentations
Sweden MALMÖ UNIVERSITY THIS IS MALMÖ UNIVERSITY Founded in students staff Five interdisciplinary faculties Faculty.
Advertisements

LESSON 1: What is Genetic Research? PowerPoint slides to accompany Using Bioinformatics : Genetic Research.
School of Computer Engineering Master of Science (Bioinformatics) A/P Kwoh Chee Keong 2009 presented by.
Undergraduate and MSc courses in the Division of Biosciences Dr. Christian Rudolph
Bioinformatics For MNW 2 nd Year Jaap Heringa FEW/FALW Integrative Bioinformatics Institute VU (IBIVU) Tel ,
Bioinformatics Master’s Course Genome Analysis ( Integrative Bioinformatics ) Lecture 1: Introduction Centre for Integrative Bioinformatics VU (IBIVU)
Systems Biology Existing and future genome sequencing projects and the follow-on structural and functional analysis of complete genomes will produce an.
Bioinformatics Dr. Aladdin HamwiehKhalid Al-shamaa Abdulqader Jighly Lecture 1 Introduction Aleppo University Faculty of technical engineering.
Jeffery Loo NLM Associate Fellow ’03 – ’05 chemicalinformaticsforlibraries.
. Class 1: Introduction. The Tree of Life Source: Alberts et al.
The Golden Age of Biology DNA -> RNA -> Proteins -> Metabolites Genomics Technologies MECHANISMS OF LIFE Health Care Diagnostics Medicines Animal Products.
Computational Molecular Biology (Spring’03) Chitta Baral Professor of Computer Science & Engg.
Using Bioinformatics to Make the Bio- Math Connection The Confessions of a Biology Teacher.
Bioinformatics: a Multidisciplinary Challenge Ron Y. Pinter Dept. of Computer Science Technion March 12, 2003.
Workshop in Bioinformatics 2010 What is it ? The goals of the class… How we do it… What’s in the class Why should I take the class..
Modeling Functional Genomics Datasets CVM Lesson 1 13 June 2007Bindu Nanduri.
Computational Genomics Lecture 1, Tuesday April 1, 2003.
Sanguinetti, 2012Bio2 lecture 1 Bioinformatics 2 “My main problem these days is that I don’t understand how we go from an experiment in the lab to a number.
Signaling Pathways and Summary June 30, 2005 Signaling lecture Course summary Tomorrow Next Week Friday, 7/8/05 Morning presentation of writing assignments.
Protein Structures.
Ayesha Masrur Khan Spring Course Outline Introduction to Bioinformatics Definition of Bioinformatics and Related Fields Earliest Bioinformatics.
From T. MADHAVAN, & K.Chandrasekaran Lecturers in Zoology.. EXIT.
University of Latvia Faculty of Biology Biology Bachelor Study Programme.
Bioinformatics Jan Taylor. A bit about me Biochemistry and Molecular Biology Computer Science, Computational Biology Multivariate statistics Machine learning.
Jennifer Oldford PAHS All information from All information from: “Biology guide. First assessment 2016.” Welcome to IB Biology.
Meer perspectief Master’s programme in Bioinformatics Bio-tools for the Future International 2-year Bioinformatics Master’s Programme.
9/30/2004TCSS588A Isabelle Bichindaritz1 Introduction to Bioinformatics.
Bioinformatics.
Knowledgebase Creation & Systems Biology: A new prospect in discovery informatics S.Shriram, Siri Technologies (Cytogenomics), Bangalore S.Shriram, Siri.
By the Ahmadiyya Muslim Women's’ Student Association.
1 Bio + Informatics AAACTGCTGACCGGTAACTGAGGCCTGCCTGCAATTGCTTAACTTGGC An Overview پرتال پرتال بيوانفورماتيك ايرانيان.
Institute of Systems Biology (INBIOSIS)/ School of Biosciences & Biotechnology (Faculty of Science & Technology), Bioinformatics Development in Malaysia.
The Finnish Strategy in Teacher Education at the 2nd cycle level
University of Latvia Higher Professional Studies Programme Faculty of Biology SECONDARY SCHOOL BIOLOGY AND ELEMENTARY SCHOOL CHEMISTRY TEACHER SECONDARY.
EuPA- EC Education Committee (EC) working plan.
Structure of Study Programmes
University of Tampere, CS Department Studying Computer Sciences at the University of Tampere Jyrki Nummenmaa
Turkish Education System...
Introduction to Bioinformatics Prologue. Bioinformatics Living things have the ability to store, utilize, and pass on information Bioinformatics strives.
Master’s Degrees in Bioinformatics in Switzerland: Past, present and near future Patricia M. Palagi Swiss Institute of Bioinformatics.
CS397-CXZ Algorithms in Bioinformatics ChengXiang (“Cheng”) Zhai, Robert Skeel (Department of Computer Science) Nick Sahinidis (Department of Chemical.
Intelligent systems in bioinformatics Introduction to the course.
CSCI 6900/4900 Special Topics in Computer Science Automata and Formal Grammars for Bioinformatics Bioinformatics problems sequence comparison pattern/structure.
Bioinformatics For MNW 2 nd Year Jaap Heringa FEW/FALW Centre for Integrative Bioinformatics VU (IBIVU) Tel ,
Bioinformatics: Theory and Practice – Striking a Balance (a plea for teaching, as well as doing, Bioinformatics) Practice (Molecular Biology) Theory: Central.
Introduction to Bioinformatics Biostatistics & Medical Informatics 576 Computer Sciences 576 Fall 2008 Colin Dewey Dept. of Biostatistics & Medical Informatics.
Introduction to Bioinformatics (Lecture for CS397-CXZ Algorithms in Bioinformatics) Jan. 21, 2004 ChengXiang Zhai Department of Computer Science University.
Biological Signal Detection for Protein Function Prediction Investigators: Yang Dai Prime Grant Support: NSF Problem Statement and Motivation Technical.
DIALing the IBIVU Vrije Universiteit Amsterdam Jaap Heringa Centre for Integrative Bioinformatics VU (IBIVU) Faculty of Sciences / Faculty of Earth and.
Course Sequence Analysis for Bioinformatics Master’s Bart van Houte, Radek Szklarczyk, Victor Simossis, Jens Kleinjung, Jaap Heringa
Overview of Bioinformatics 1 Module Denis Manley..
AdvancedBioinformatics Biostatistics & Medical Informatics 776 Computer Sciences 776 Spring 2002 Mark Craven Dept. of Biostatistics & Medical Informatics.
Epidemiology 217 Molecular and Genetic Epidemiology Bioinformatics & Proteomics John Witte.
Central dogma: the story of life RNA DNA Protein.
EB3233 Bioinformatics Introduction to Bioinformatics.
An overview of Bioinformatics. Cell and Central Dogma.
Algorithms for Biological Sequence Analysis Kun-Mao Chao ( 趙坤茂 ) Department of Computer Science and Information Engineering National Taiwan University,
داده های عظیم در دوران پساژنوم Big Data in Post Genome Era مهدی صادقی پژوهشگاه ملی مهندسی ژنتیک و زیست فناوری پژوهشکده علوم زیستی، پژوهشگاه دانش های بنیادی.
Molecular Diagnostics Certificate Program January 23, 2008 Information Session.
School of Mechanical, Materials and Manufacturing Engineering About this course Biomedical industries provide a rich diversity.
Bioinformatics Professor: Monica Bianchini Department of Information Engineering and Mathematics E–mail: Phone: 1012.
Faculty of Biology University of Latvia UL Faculty of Biology.
Teachers’ evaluation by the Petroleum – Gas University of Ploiești
Bioinformatics Overview
LB73 - Implementation of Biotechnology Projects of Different Inquiry Level to Promote Career Success of Non-Science Majors Paloma Valverde, PhD;
C E N T R F O I G A V B M S U 2MNW/3I/3AI/3PHAR bachelor course Introduction to Bioinformatics Lecture 1: Introduction Centre for Integrative Bioinformatics.
Protein Structures.
Bioinformatics For MNW 2nd Year
BIOINFORMATICS Summary
Integrating research in teaching
Presentation transcript:

Centre for Integrative BioInformatics IBIVU Bioinformatics Masters in The Netherlands Contents: Nine bioinformatics Masters programmes at eight Dutch universities –Materials and teaching generally in English Core national bioinformatics teaching initiative within Netherlands BioInformatics Centre (NBIC) Overview of the 2-year bioinformatics Master at the IBIVU, Free University of Amsterdam

Centre for Integrative BioInformatics IBIVU Bioinformatics Masters in The Netherlands Core masters: CMBI, University of Nijmegen (Gert Vriend) – classical, general Wageningen University (Peter Schaap), in collaboration with CMBI – genomics oriented IBIVU, Free University of Amsterdam (Jaap Heringa) – classical, general, tool creation

Centre for Integrative BioInformatics IBIVU Bioinformatics Masters in The Netherlands Combination masters: Master Life Sciences, Groningen University (Ritsert Jansen) – Bioinformatics courses planned Major Bioinformatics in Master Life Science & Technology, University of Leiden (Joost Kok) Master Molecular Cell Biology and Bioinformatics, University of Amsterdam, starting 2005 Major Bioinformatics in Master Life Sciences, University of Maastricht (Robert Vlietinck) Master Theoretical Biology & Bioinformatics, University of Utrecht (Paulien Hogeweg) - modelling Master Genomics and Bioinformatics, University of Utrecht (Albert Heck)

Centre for Integrative BioInformatics IBIVU Netherlands BioInformatics Centre (NBIC) Bioinformatics Application Service Provider (BioASP) BioRANGE – National collaborative bioinformatics integrated project (~25 M) Biowise – National bioinformatics training initiative –Biotune Software for categorising and storing teaching materials Software for course development

Centre for Integrative BioInformatics IBIVU International 2-year Master VU Centre for Integrative Bioinformatics (IBIVU) Faculty of Sciences/Faculty of Earth & Life Sciences, Free University Amsterdam Co-ordination: Jaap Heringa VU = Vrije Universiteit

Centre for Integrative BioInformatics IBIVU International 2-year Master VU Target group: since Sep 2003 Students with Bachelor Physics, Chemistry, Mathematics, Computer Science, Biology, or Medical Natural Sciences Students write reasons for their choice Students pay ~1600 Euro tuition fees, rest funded by state/university Students from Medicine or Health sciences? Computer science students dont know the biology and biology students dont know the computer science Remarks: 1.We require programming experience for some courses. 2.VU master teaching is moving towards pre-master of 6 months maximally, to fill in deficiencies and to aim at students coming from non-academic higher education.

Centre for Integrative BioInformatics IBIVU International 2-year Master VU Centre for Integrative Bioinformatics (IBIVU) Faculty of Sciences/Faculty of Earth & Life Sciences Free University Amsterdam Outline: 45 ECTS courses, 75 ECTS practical work (120 ECTS total): Compulsory courses 30 credits Optional courses credits First traineeship credits (Major) Second traineeship credits (Minor) Optional third traineeship credits

Centre for Integrative BioInformatics IBIVU Compulsory courses (6 ECTS each): Course 1. Sequence Analysis Course 2. DNA/Protein structure-function analysis and prediction Course 3. Bioinformatics data analysis and tools Course 4. Genome analysis: structural and functional genomics Course 5. Integrative bioinformatics International 2-year Master VU

Centre for Integrative BioInformatics IBIVU Optional courses (3-6 ECTS each): Are provided by the IBIVU mainly through the Biology, Mathematics and Computer Science Departments. Students may also choose courses at other departments in consultation with your mentor. A range of optional courses is available, including Introduction to Bioinformatics, Statistical Genetics, Statistical Models, Machine Learning, Evolutionary Methods, Neural Networks, Data Mining Techniques, Scientific Visualization and Parallel Programming (Department of Computer Science). One student has attended a course at Stockholm Bioinformatics Centre International 2-year Master VU

Centre for Integrative BioInformatics IBIVU Traineeships: Can be carried out VU-wide: The Centre for Neurogenomics and Cognitive Research (CNCR) The Institute for Molecular Cell Biology (IMC) The IBIVU The Centre for Complex Molecules … Embedded in national initiatives in which the IBIVU participates: Ecogenomics Center for Medical Systems Biology (CMSB) Other national or international institutes (VU Internationalisation): one student is currently doing a project at Stockholm Bioinformatics Centre (Bob McCallum) Optional third traineeship can be literature survey. International 2-year Master VU

Centre for Integrative BioInformatics IBIVU nameSequence Analysis aimA theoretical and practical bioinformatics course about biological sequence analysis. The course provides an introduction to the algorithmic and biological principles of sequence analysis, as well as practical implications. Goals: At the end of the course, the student will be aware of the major issues, methodology and available algorithms in sequence analysis. At the end of the course, the student will have hands-on experience in tackling biological problems in sequence analysis. contentsTheory: Dynamic programming, database searching, pairwise and multiple alignment, probabilistic methods, pattern matching, evolutionary models, and phylogeny. Practical: Assignment programming own alignment software based on dynamic programming Assignment homology searching and pattern recognition using biological and disease examples Assignment multiple alignment of biological sequences methodology13 Lectures (2 two-hour lectures per week); Assignment introductions; Computer practicals; Hands-on support literatureE-course material: Books: Richard Durbin, Sean R Eddy, Anders Krogh, Graeme Mitchison (1998). Biological Sequence Analysis. Cambridge University Press, 350 pp., ISBN teachingActive participation (November/December 2004). testAssignment results and oral or written exam (depending on number of course students) target groupStudents with Bachelor Physics, Chemistry, Mathematics, Computer Science, Biology, or Medical Natural Sciences, with a strong interest in Bioinformatics remarksThe course is taught in English required knowledgeSome experience in programming is required.

Centre for Integrative BioInformatics IBIVU nameDNA/Protein Structure-Function Analysis and Prediction aimA theoretical and practical bioinformatics course on the analysis and prediction of structure- function relationships of DNA and protein molecules. The course provides an introduction to the molecular principles of structure and function, available bioinformatics analysis and prediction techniques, and biological databases. Goals: At the end of the course, students will be aware of the major issues, methodology and. At the end of the course, the student will have hands-on experience in molecular modeling and studying structure-function relationships. contentsTheory: Protein folding and energetics, experimental structure determination, protein fold families, protein structure databases, protein secondary structure prediction, fold prediction, molecular modeling, protein-protein interactions, DNA/RNA structure/function, DNA/RNA structure prediction Practical: Assignment homology modelling Assignment immunocomplex modelling methodology13 Lectures (2 two-hour lectures per week); Assignment introductions; Computer practicals; Hands-on support literatureE-course material: Books: Carl Branden & John Tooze (1998). Introduction to Protein Structure. 2 nd Edition or higher. Garland Science, 410 pp., ISBN teachingActive participation (January/February 2005). testAssignment results and oral or written exam (depending on number of course students) target groupStudents with Bachelor Physics, Chemistry, Mathematics, Computer Science, Biology, Medical Natural Sciences or Medicine, with a strong interest and some basic knowledge in Bioinformatics remarksThe course is taught in English. required knowledgeA completed course Sequence Analysis is a strong advantage.

Centre for Integrative BioInformatics IBIVU NameBioinformatics data analysis and tools aimA theoretical and practical bioinformatics course on the fundamentals of bioinformatics tools and tool creation for biological data mining. Goals: At the end of the course, students will be aware of the issues, methodology and available bioinformatics tools for At the end of the course, students will have hands-on experience in molecular modeling and studying structure-function relationships. contentsTheory: Inverse protein folding, introduction to statistical thermodynamics of soft and biological matter (5 lectures), genetic algorithm, repeat recognition tools and concepts (e.g. transitivity), molecular mechanics simulations, (hidden) Markov models, pattern recognition, machine learning techniques Practical: Assignment Statistical Thermodynamics Assignment hidden Markov modelling methodology13 Lectures (2 two-hour lectures per week); Assignment introductions; Computer practicals; Hands-on support literatureE-course material (slides, assignment material, papers): Books: Biological Physics. Energy, Information, Life. Philip Nelson. 600 pages, W H Freeman & Co., (July 2003), ISBN: teachingActive participation (April/May 2005). testAssignment results and oral or written exam (depending on number of course students) target groupStudents with Bachelor degree in Physics, Chemistry, Mathematics, Computer Science, Biology, Medical Natural Sciences or Medicine, with a strong interest and some basic knowledge in Bioinformatics remarksThe course is taught in English. required knowledgeA completed course Sequence Analysis and DNA/Protein Structure-Function Analysis and Prediction is a strong advantage. Some experience in programming is required.

Centre for Integrative BioInformatics IBIVU nameGenome Analysis aimA 1-month intensive course for introduction to genomics and bioinformatics techniques used to analyse and integrate genomics data sets. contentsStatic genome analyses: DNA, RNA and protein primary, secondary, tertiary en quaternary structures; genome sequencing, methods and annotation; genome projects (bacteria, yeast, plant, animal, human), bioinformatics and databases; COG, EST, SNP, motifs Dynamic genome analyses: transcriptome (arrays en clustering, QPCR, SAGE); proteomics (mass spectrometry, arrays, 2D gel electrophoresis, homology modeling); metabolomics (methods, interpretation, databases) Functional genetics: knock-out, reporter genes, expression vectors, promoter-probe studies; reverse genetics, RNAi, transgenese Integrative genome analyses: network modelling, Metabolic Control Analysis, biochemical databases; physiomics Application areas: medical genomics; ecogenomics; sociogenomics; pharmacogenomics; biotechnological genomics; ethical aspects methodology15 short modules, each including a lecture, (computer) practical and self study Tutorials/discussions of book material, lecture notes Computer practicals Lab demonstrations: Students follow and assist an experienced postdoc/Ph D student performing a key experiment. Data evaluation and interpretation on site. literaturePowerpoint presentations via Blackboard Book: A primer of genome science. Gibson G and Muse, SV, Sinauer Associates Inc Publishers, 2002, ISBN (pbk). E-course material: teachingActive participation testExam (50%), assignments (25%) and computer analyses (25%) target groupStudents with Bachelor Physics, Chemistry, Mathematics, Computer Science, Biology, or Medical Natural Sciences, with a strong interest in Bioinformatics remarksThe course will be taught in Dutch; provisions can be made for English speakers. required knowledgeBachelor Physics, Chemistry, Mathematics, Computer Science, Biology, Medical Natural Sciences.

Centre for Integrative BioInformatics IBIVU nameIntegrative Bioinformatics - Intracellular networks aimA 1-month intensive course providing an introduction to cell biological networks. contentsTheory: The course gives an introduction to the behavior of intracellular networks, including metabolic pathways, signal transduction chains, gene expression pathways and their hierarchical organization. Metabolic and Hierarchical Control Analysis, Biological Non Equilibrium Thermodynamics, Genetic Network Analysis, Elementary Mode Analysis, Flux (Balance Analysis) will be explained and practiced. The levels of genomics (genome, transcriptome, proteome, metabolome and function) and their interrelationships will be clarified, both theoretically and experimentally. Practical: inspection experiments performing flux and metabolite; measurements and subsequent regulation analysis; inspection experiments; designing network targeted inhibitors of parasites; flux analysis on the basis of a set of computer data; control analysis on the basis of earlier experimental results; extra assignment integrative bioinformatics for bioinformatics master students (1 ECTS) methodologyLectures; Tutorials/discussions of book material; Lecture notes Web-courses ( ); Computer practicals; Lab-inspection work: Students follow and assist an experienced postdoc/Ph D student performing a key experiment. Data evaluation and interpretation on site. literatureE-course material: Books: Chapters from:Understanding the Control of Metabolism (Fell, D) Portland Press; Metabolic Engineering in the Postgenomic Era (Kohlodenko & Westerhoff, Editors), Horizon Bioscience; Thermodynamics and Control of Biological Free-energy transduction (Westerhoff and Van Dam), Elsevier teachingActive participation (March/April 2005) testWritten exam target groupStudents with Bachelor Physics, Chemistry, Mathematics, Biology, Medical Biology with a strong interest in the interface between these disciplines and bioinformatics remarksThe course is taught in the English language and involves extensive direct contact with the professors and associate professors. Required knowledgeBachelor Physics, Chemistry, Mathematics, Informatics, Biology, Medical Natural Sciences, or equivalent;

Centre for Integrative BioInformatics IBIVU Bioinformatics bachelor IBIVU: Introduction to Bioinformatics 26 two-hour course blocks Medical Natural Sciences 2 nd year

Centre for Integrative BioInformatics IBIVU Visualisation and Teaching The VU A cheap scalable solution: multiple beamers (from the back), stereo viewing Challenges: alignment, porting software 4096 x 1536 pixels

Centre for Integrative BioInformatics IBIVU Integrative Visualisation The SARAThe VU Porting SARAgene virtual reality comparative genomics software

Centre for Integrative BioInformatics IBIVU SaraGene 3D visualisation important for large genomic data sets: Clustering and mapping genes onto location, expressome, metabolome, etc. Many data objects (labels): need 3D to place objects and high resolution to read labels CAVE has good 3D but low resolution (e.g. labels not easily readable) ICwall has bit less 3D capability but much higher resolution.

Centre for Integrative BioInformatics IBIVU Problems/suggestions Diverse target group, how to get students up to scratch before starting Masters. Lost a (biology) student due to inability to program. –Biosapiens pre-master? –Biosapiens driven bioinformatics bachelor? Standards/exams –Competence based learning: minimal skills/knowledge definition –European bioinformatics master certificate Structuring subjects: students dont always appreciate where things fit in. Teacher was OK but subject is idiotic Lack of students in Dutch science faculties –Biosapiens driven Bioinformatics PR initiative (e.g. Bioinformatics and Society) –Modular teaching (blocks that can be taught to other disciplines) Utilities –Bioinformatics practical course book; slides, exercises, practical, exam questions DB; E-learning; Grid-based distance learning, Visualisation/ICwall