Kyoko Watanabe

Kyoko Watanabe

by : Kyoko Watanabe Events, News

Life Science with Industry

For a full description of these challenges https://www.lorentzcenter.nl/lc/web/2018/1055/info.php3?wsid=1055&venue=Snellius

 

The workshop will take place in Leiden in the building of the Lorentz Center, an organisation that is specialised in organising scientific workshops (http://www.lorentzcenter.nl/).

To create multi-disciplinary teams, participants will be selected based on their (i) specific background, (ii) motivation to participate, and (iii) date of registration (first come first served).

 

Register on the workshop website: https://www.lorentzcenter.nl/lc/web/2018/1055/info.php3?wsid=1055&venue=Snellius

Deadline: Friday October 19, 2018.

Participation is free of charge, including hotel accommodation, lunches and two dinners during the workshop. The workshop is sponsored by the Lorentz Center, the Research School BioSB (http://biosb.nl/) and the three companies involved.

Need for more information?

Contact (Carey Batenburg-Einthoven) at the Lorentz Center (phone +31 715 275 578).

We hope to welcome you on November 19th 2018.

 

Scientific organizers:

Dennis Botman, Vrije Universiteit Amsterdam

Em. prof. dr. Roel van Driel, Universiteit van Amsterdam

Dr. Gökhan Ertaylan, VITO, Mol, Belgium

Eunice van Pelt-KleinJan, Vrije Universiteit Amsterdam

Klara Scupakova, Maastricht University

Prof. dr. Bas Teusink, Vrije Universiteit Amsterdam

 

Organizers (NWO):

Dr. Ansa Baykus-Fiaz, NWO-Domain Science, Den Haag

Dr. Margot Beukers, NWO-Domain Applied and Engineering Sciences, Utrecht

Drs. Lisette Krul, NWO-Domain Applied and Engineering Sciences, Utrecht

by : Kyoko Watanabe Events, News

BioCafe in Wageningen

We are organizing a BioCafe in Wageningen, on 25th June 2018. This BioCafe is co-organized with BioSB course Algorithms for Biological Networks.

Students joining the course as well as any other students/researchers working in bioinformatics and systems biology are welcome to join!!

Location: Spot, Bronland 103, 6708WH, Wageningen

No registration is required.

biocafe_2018-06-25

 

by : Kyoko Watanabe Courses, News

BioSB Course: Algorithm for Biological Networks (5th edition)

Date

June 25-29, 2018

Location

Wageningen University & Research (rooms TBA)

Course coordinators

  • dr. Maria Suarez Diez (WUR)
  • prof. dr. Dick de Ridder (WUR)
  • dr. Jeroen de Ridder (UMCU)

Lecturers

  • dr. Maria Suarez Diez, Wageningen University
  • prof. dr. ir. Dick de Ridder, Wageningen University
  • dr. ir. Jeroen de Ridder, University Medical Center Utrecht
  • dr. K. Anton Feenstra, Vrije Universiteit, Amsterdam
  • dr. Aalt-Jan van Dijk, Wageningen University
  • prof. dr. Jaap Heringa, Vrije Universiteit, Amsterdam

Target audience

The course is aimed at PhD students with a background in bioinformatics, computer science or a related field; a working knowledge of basic statistics and linear algebra is assumed. The BioSB course “Pattern recognition” and the ASCI course “Advanced pattern recognition” (a1) discuss many of the tools used in this course, but it is not required to have followed these. Prior knowledge of molecular biology is a bonus, but also not strictly required.

Preparation material on probability theory, linear algebra and molecular biology can be found at the course website and should be read by all students before the course starts

Course description

Molecular biology is concerned with the study of the presence of and interactions between molecules, at the cellular and sub-cellular level. In bioinformatics and systems biology, algorithms and tools are developed to model these interactions, with various goals: predicting yet unobserved interactions, assigning functions to yet unknown molecules through their relations with known molecules; predicting certain phenotypes such as diseases; or just to build up biological knowledge in a structured way.

Such interaction models are often best modelled as networks or graphs, which opens up the possibility of using a large number of readily available algorithms for inferring networks, performing simulations of biology, optimising paths or flows through networks, graph-based data integration and graph mining. Many of these algorithms can be applied (sometimes with slight alterations) to solve a particular biological problem, such as modeling transcriptional regulation or predicting protein interaction/complex formation, but also to derive systems behaviour by breaking down networks into modules or motifs with certain characteristics.

In this course, we will first give a brief overview of molecular biology, the advent of high-throughput measurement techniques and large databases containing biological knowledge, and the importance of networks to model all this. We will highlight a number of peculiar features of biological networks. Next, a number of basic network models (linear, Boolean, Bayesian) will be discussed, as well as methods of inferring these from observed measurement data. A number of alternative network models more suited for high-level simulation of cellular behaviour will also be introduced. Building on the network inference methods, a number of ways of integrating various data sources and databases to refine biological networks will be discussed, with specific attention to the use of sequence information to refine interaction and transcription regulation networks. Finally, we will give some examples of algorithms exploiting the networks found to learn about biology, specifically for inspecting protein interaction networks.

Course programme

The tentative course programme and course material can be found on the course website.

Registration

You can now register via the enrollment form.

by : Kyoko Watanabe Conferences, News

BioSB PhD Retreat 2018

YoungCB (ISCB Regional Student Group Netherlands) is pleased img_20170403_172913to invite you to the BioSB PhD retreat 2018 in the afternoon May 14th. The retreat will be held in Lunteren at the Congrescentrum De Werelt, preceding the BioSB conference. The retreat is sponsored by the BioSB research school. We encourage all (PhD-) students and young researchers in the fields of computational biology, bioinformatics, systems biology and related fields to attend this annual retreat to discuss your research and build a network with fellow young peers in the Netherlands.

The retreat provides you with the opportunity to present your research to fellow students and young professionals. This year’s them is Machine learning and Deep learning. We will have 3 keynote speakers including one work shop. In the evening there will be a dinner in the centre of Lunteren, followed by a fun social event at the conference centre bar. The evening program provides you the opportunity to network with fellow (PhD-) students and young researchers.

Program

13:00-13:15 Registration
13:15-13:30 Welcome and introduction
13:30-14:00 Keynote 1: Kurt Driessen
Assistant professor at Maastricht University
14:00-14:30 PhD flash talk
14:30-14:45 – Coffee break –
14:45-16:45 Workshop: Rachel Cavill
Assistant professor at Maastricht University
16:45-17:00 – Coffee break –
17:00-18:00 Keynote 2: Sultan Imangaliyev
PostDoc at VU Medical Center
18:00-19:00 Break + walk to Lunteren center
19:00-21:00 Dinner in Lunteren center
21:00- Social activity

Submit your abstract
Interested in giving a flash presentation? Submit your abstract to rsg-netherlands@iscbsc.org.
Abstract should be 250-300 words.
Deadline to submit your abstract: 30 April 2018 Extended deadline 4th May 2018

Registrationimg_20170403_200453
Register from BioSB 2018

Fee:
50 Euro (without hotel room)
41,50 Euro (hotel room)

NB: Do not forget to bring your laptop for the workshop!! You can also book a hotel room via the registration form. If you also register for the conference, please note that if you book a ‘private room’ for the PhD retreat but a ‘shared room’ for the conference, you may have to move to another room at the first day of the conference or will have to share the room the night after the PhD retreat.

retreat2018

by : Kyoko Watanabe Courses, News

BioSB Course: Optimisation Techniques in Bioinformatics and Systems Biology

Date

12-16 February 2018

Location

Wageningen

Course coordinators

Jaap Kaandorp (UvA), Jaap Molenaar (WU), Hans Stigter (WU), Cajo ter Braak (WU)

Course description

Many problems in bioinformatics and systems biology require at a certain moment application of some optimisation technique. When facing optimisation problems, many researchers suffice with applying a simple algorithm in Excel, coming to the conclusion that it does not work properly or runs into convergence problems. It is not necessary to stick to that stage, since optimisation is a rapidly expanding field of research, that generates more and more efficient, successful, and easy-to-use algorithms.

This course is intended to provide you with the main ideas underlying optimisation, and to get you acquainted with the optimisation techniques that are nowadays available and widely used. In addition, a great variety of examples of optimisation problems in life sciences will be presented and discussed.

Course programme

The course has the following structure:

  • Day 1: Math refresher and univariate optimisation (Jaap Molenaar+ Hans Stigter)
  • Dag 2: Local multivariate optimisation (Jaap Molenaar + Hans Stigter)
  • Dag 3: Global stochastic optimisation (simulated annealing, evolutionary algorithms) (Jaap Kaandorp)
  • Dag 4: Parameter estimation, systems control and optimisation (Hans Stigter + Jaap Molenaar)
  • Dag 5: MCMC techniques (Cajo ter Braak)

The first day is devoted to study simple problems that allow the use of algorithms that are intuitively clear. On day 2, we extend to problems that are bit more complicated. On day 3, we introduce techniques that are based on stochastic searching, while day 4 is spent on the frequently met problem of finding values for the parameters in a model, given a dataset. This challenging problem requires a bit more sophisticated optimisation tools. You will learn about uncertainty and identifiability of the parameters. In addition, you will get some experience with using appropriate parameter estimation tools. On the last day, the state-of-the-art will be presented, since then the popular and powerful Markov Chain Monte Carlo (MCMC) technique will be dealt with. This method is based on a Bayesian approach. So, you will learn about prior distribution, posterior distribution, likelihood, and how in MCMC likelihood and prior distribution are combined to arrive at a posterior distribution.

Target audience

We assume that the participants have some basic knowledge of modelling in the life sciences. However, it is not necessary to be an expert in mathematics, since the course starts with a session to refresh the mathematical background needed for optimisation.

Registration

You can register via the course enrollment form.

by : Kyoko Watanabe Conferences, News

Benelux Bioinformatics Conference 2017

Date
13 – 14 December 2017

Location
Leuven, Belgium
See here for more details

Website
https://bbc2017blog.wordpress.com/

Registration
https://bbc2017blog.wordpress.com/registration/ (Free of charge)

For more than ten years this event has been a great opportunity to face the rich and connected community of the bioinformatics and computational biology of our countries. At its 13th edition, BBC aims to continue with its central role for both junior researchers and more experienced scientists working in Benelux. However, we want to point out the relevance that this stage may have for young players of this field, like master students, PhD students, and new postdocs who would find in this conference the perfect mix of both formal and familiar environment to disseminate and communicate their projects, their results, their vision, in preparation for bigger and more prestigious stages. For that reason, the organizing committee strongly advises you to submit your research and share your ideas on the stage of BBC 2017.

by : Kyoko Watanabe Courses, News

BioSB Course: Managing and Integrating Life Science Information (5th Edition)

Date

22-26 January 2018

Lecturers

Confirmed lecturers: Frank van Harmelen, Andre Dekker

Course Coordinators

Marco Roos and Katy Wolstencroft

Credits and grading

The total study load of the course is 3 EC. There will not be a written examination.

Location

Amsterdam Science Park, The Netherlands

Hosted by: Amsterdam Data Science

Background

The amount of Life Science data available in the public domain is a vast and growing resource for bioinformatics research. There are over 20 million papers in PubMed and over 1600 biological databases. In many cases finding and applying the information from these resources is far from trivial. Following this course will show you techniques for working with these distributed resources, which includes using the web of Linked data and scientific workflows. It will also focus on methods for using or linking your own data into this large distributed Semantic Web of resources, in order to ensure that your data is FAIR(Findable, Accessible, Interoperable and Reusable).

Target audience

This course is for bioinformaticians who would like to learn about leading-edge data and knowledge integration solutions. You will learn (1) powerful and flexible approaches to data and information management for your bioinformatics application (Semantic Web and Linked Data), (2) how to work with data across remote locations, for instance by applying Web Services and workflows, (3) how to publish your own data to make it available and reusable for the rest of the community. We assume a basic understanding of bioinformatics programming for the hands on sessions. It would suit previous user participants of BYOD meetings who would like more hands-on experience of data integration. It would also suit data providers who would like to explore new ways of serving their data or integrating it with other resources.

Course description

This course introduces modern techniques for the management of life science data and knowledge for bioinformatics applications. After following this course students should be able to start creating their first applications based on these technologies or make more informed design decisions for their current application.

In this course you will learn about:

  1. Linked Data and the Semantic Web technologies that underpin it
  2. How you can use Linked Data for data and knowledge integration in the Life Sciences
  3. Available Linked Data resources in the public domain and large-scale projects that use these resources
  4. How you can integrate your own data with Linked Data resources
  5. How you can combine data integration and analysis over distributed resources, using Web Services and workflows

Tentative programme

The program will include the topics:

  • Introduction to Semantic Interoperability and the Semantic Web;
  • The Semantic Web in Use;
  • The Semantic web in use – systems and guidelines;
  • Data stewardship and making Data Understandable and Searchable (the FAIR principles);
  • Using, Integrating and Analysing Data

More information

For more information about the course programme you can contact Marco Roos or Katy Wolstencroft.
For more information about the registration or logistics you can contact the BioSB office.

Registration

You can now register for the course via the Enrollment form.

by : Kyoko Watanabe Courses, News

NSG course: RNA-seq data analysis (7th edition)

NGS Course: RNA-seq data analysis, 2017 (7th edition)

Date

November 6-8, 2017

Location

Venue: Universiteit Leiden – Faculty Social Sciences (FSW), Wassenaarseweg 52, 2333 AK Leiden
Room: 1A-21 on November 6 and 8
Room: 1A-37 on November 7

Course coordinators

Peter-Bram ‘t Hoen (LUMC), Leon Mei (LUMC), Jan Oosting (LUMC), Szymon Kielbasa (LUMC) and Celia van Gelder (BioSB)

Course description

The BioSB research school and partner LUMC are organizing a 3-day course on RNA-seq data analysis. This is an advanced course for people with experience in NGS. The course will consist of lectures, Galaxy and R practicals and will cover the analysis pipelines for differential transcript expression and variant calling. Examples will be taken from human and mouse studies. The course does not cover prokaryotic RNA profiling nor plant- and metagenomics aspects.

Course topics

  • RNA-seq experimental approaches and study design
  • Quality control and alignment
  • Statistics for differential gene expression
  • eQTL analysis and allele specific expression
  • Single cell RNA sequencing
  • Fusion transcript detection
  • Small RNA profiling
  • Software for RNA-seq data analysis

Programme

You can find the programme for the course here.

Target audience

Participants for the RNA-seq course should preferably have participated in the general NGS course or otherwise have demonstrated hands-on experience with NGS data analysis. The course is aimed at PhD students and post-docs, but scientific programmers and data analysts with a background in biology and bioinformatics may also attend.

NB: The practicals are mostly in R. We expect that participants have at least basic knowledge of R and experience in running R scripts. If you don’t have any experience with R yet but would like to follow this course, please read some online introductory material about R. For example, http://www.datacarpentry.org/R-genomics/00-before-we-start.html and http://www.datacarpentry.org/R-genomics/01-intro-to-R.html

Participants must bring own laptops capable of running RStudio. Please download and install RStudio before the course. For Galaxy tutorial, please install firefox or google chrome web browser.

Registrations will be handled on a first-come-first-served basis but experience and motivation will be reviewed. Seats have been reserved for participants in the FP7-funded projects RD-Connect and BBMRI-NL.

This tutorial should give R novices sufficient knowledge to do the practicals
https://www.nceas.ucsb.edu/files/scicomp/Dloads/RProgramming/BestFirstRTutorial.pdf

Hotel information

See BioSB page at http://biosb.nl/education/course-portfolio/rna-seq/

Registration

You can register for the course via the enrollment page.

by : Kyoko Watanabe Courses

BioSB Course: Protein structures (4th edition)

Protein structures: production, prowess, power, promises, and problems (4th edition)

Original page: http://biosb.nl/education/course-portfolio/protein-structures-production-prowess-power-promises-and-problems/

Date

30 October – 3 November 2017 

Lecturers

  • Gert Vriend (CMBI, course coördinator)
  • Daniel Hoffmann (University Duisburg/Essen (TBC))
  • Hanka Venselaar (CMBI)
  • Wouter Touw (CMBI)

Location

Center for Molecular and Biomolecular Informatics (CMBI), Radboud University Nijmegen-Medical Centre /NCMLS, Nijmegen, the Netherlands

Target audience

The course is suitable for both PhD students working in structural bioinformatics as well as for PhD students in the life sciences who want to learn more about using structural informatioin in their research. The course schedule accommodates both groups, parallel sessions for both groups will be scheduled when necessary.

Study load

3 EC

Course description

In the right hands, protein structures are a ‘power’ful tool to answer bio-molecular questions. Knowledge of the structure is a pre-requisite for rational drug design, for biotechnology, for chemical biology, and for answering a whole series of biomedical questions. In this course we will discuss the ‘production’ of protein structures by NMR, X-ray, and homology modelling. These methods all have their pro’s and cons so a certain ‘prowess’ is needed to follow all ‘promises’ and start attacking bio-medical ‘problems’ using protein structures.

The course will be split in three parts:

Part 1) Looking and seeing things in protein structures, learning to operate the software, understanding some of the algorithms.
Part 2) Protein structure determination (prediction) with NMR, X-ray, and homology modelling, and the possibilities and problems that come with each of these three techniques.
Part 3) Applying all that was learned in real-life example studies.

Examples of questions you will be able to answer after follwing the course:

  • Why is a person with this mutation sick? Or in other words, how does the molecular phenotype cause a disease state?
  • This enzyme converts mannose. Can I make is specificity broader?
  • This enzyme doesn’t function in my in vitro assay. Should I add some ions?
  • I want to add a tag to my enzyme, should I put it on the N-terminus, the C-terminus, or is something different needed?
  • This receptor binds a ligand, but if I look at the structure, that ligand doesn’t fit at all. Can I predict motions that take place upon ligand binding?

Preliminary course schedule


Day 1: Homology modelling seminar (H Venselaar).

YASARA practicals

  • Watching and seeing protein structures
  • Homology modelling
  • Answering biological/biomedical questions using protein structures and models”.

Day 2: Protein structure comparison seminars (H Venselaar, G Vriend).

Practicals

  • Sequences analysis when structure data is available
  • Answering medical questions with sequence-structure alignments

Day 3: Electrostatics and molecular dynamics seminars (D Hoffmann).

Practicals

  • Role of electrostatics
  • Answering biological questions with MD

Day 4: Protein structure determination and validation seminars (W. Touw, G Vriend).

Practicals

  • X-ray and NMR structure comparison
  • Protein structure validation and implications

Day 5: Own project executed with help from CMBI staff.

More information

For more information about the course you can contact Celia van Gelder.

Registration

To register for the course, please fill out the enrollment form.