Educators:
Pelin Yilmaz (Biodata), Daniel McDonald, Tony Walters, Antonio Fernandez-Guerra

Date:
Wednesday 15 August 2018, 9:00-17:00
 
Location:
Congress Center Leipzig - ISME

Contents:
The workshop will include lectures covering basic QIIME and SILVA usage and theory, and hands-on work with QIIME to perform microbiome analysis from raw sequence data through publication-quality statistics and visualizations. The workshop will also cover related bioinformatics tools including DADA2, Emperor, and scikit-bio. This workshop will provide the foundation on which students can begin using these tools to advance their own studies of microbiome analysis or microbial ecology.

Learning goals:
    • Understand the most recent QIIME2 features for microbial community analysis
    • Select the best databases and workflow and parameters to perform the different steps for microbial community analysis
    • Understand and apply on their own datasets different phylogenetic and non-phylogenetic metrics to compare microbial diversity samples

Prerequisites:
This is a hands-on workshop. Participants must bring their laptop. Basic knowledge of Linux command line is nice to have, but not must.

Keywords:
microbial ecology, microbiome, diversity, amplicon analysis, NGS

Tools:
qiime2 platform, SILVA datasets

Contact:
This email address is being protected from spambots. You need JavaScript enabled to view it. OR This email address is being protected from spambots. You need JavaScript enabled to view it.

Educators:
Florian Jug, Kashif Rasul, Peter Steinbach, others (DAIS/CIBI)

Date:
24.09.2018 – 28.09.2018

Location:
Center for Systems Biology Dresden / MPI-CBG

Registration website:
https://indico.mpi-cbg.de/event/118/

Contents:
This hands-on course will take you from 0 to 100 in Deep Learning with Keras. Our aim is to teach the fundamentals of deep learning with Convolutional Neural Networks (CNN) based on modern techniques using the Keras API and the Tensorflow backend. By the end participants will know how to build deep learning models, how to train them, what to avoid during training, what to check during training and how to perform model inference, especially for image based problems. We hope participants will then go out and apply these methods to their own problems and use cases.

The core curriculum is planned from Monday (September 24) to Friday afternoon (September 28) to take place at the MPI CBG campus, Pfotenhauerstrasse 108, Dresden, Germany. As the agenda is currently being prepared please check-in from time to time.

All participants are expected to bring their laptop. During the workshop, a uniform access to GPU-enabled workstations or servers will be provided that hold the software stack used. Thus, your laptop is not required to hold a mobile GPU
or alike. All participants are expected to have a solid understanding of fundamentals of linear algebra as well as programming.

The workshop admission fee amounts to € 250 per participant. Every successful applicant is required to bring a poster to the workshop that describes their current scientific challenge that they would like to solve with Deep Learning. Posters have to be sent in 1 week prior to the workshop.

Learning goals:
- Fundamentals of deep learning with CNNs.
- Keras API with the Tensorflow backend.
- How to define your deep net.
- How to train it.

Prerequisites:
Bring your own laptop. Keras and Tensorflow backend should already be installed. (We will have GPU nodes you can use if your laptop does not offer a fast GPU.) Solid understanding of the fundamentals of linear algebra. Programming skills (never programmed… that will not work out, sorry!)

Keywords:
DeepLearning, Keras, Tensorflow, Python

Tools:
Keras, Python, Tensorflow

Contact:
Florian Jug (This email address is being protected from spambots. You need JavaScript enabled to view it.) and Peter Steinbach (This email address is being protected from spambots. You need JavaScript enabled to view it.)

Educators:
Michael Berthold, Greg Landrum, Patrick Winter, Alexander Fillbrunn, Julianus Pfeuffer, René Rahn (CIBI)

Date:
23-07-2018 – 25-07-2018, all day

Location:
University of Konstanz, Universitätsstraße 10, 78457 Konstanz

Contents:
This hands-on course will introduce classic and modern techniques for the analysis of various types of data: molecular databases, sequences, and mass spectrometry data. Analysis techniques range from standard logistic regression and random forests to deep natural networks. Participants will learn how to process and integrate their data using the open source platform KNIME and gain experience with extensions such as RDKit (cheminformatics), SeqAn (NGS), and OpenMS (mass spec).
Greg Landrum, the main author of RDKit, will cover the cheminformatics and machine learning part of the course. Further teachers are members of the SeqAn and OpenMS group.

Learning goals:
Using KNIME for Life Science data.

Prerequisites:
None.

Keywords:
KNIME, OpenMS, SeqAn, Workflows, Mass Spectrometry, Sequence Data, ChemInformatics

Tools:
KNIME, OpenMS, SeqAn, RDKit

Contact:
Alexander Fillbrunn
This email address is being protected from spambots. You need JavaScript enabled to view it.
+49 7531 88 2510

Educators: 
Georg Zeller (HD-HuB), Clara Amid, Rob Finn, Alexandra Holinski, Alex Mitchell, Chris Quince, Jeena Rajan, Joao Matias Rodrigues, Aleksandra Ola Tarkowska, Darren Wilkinson

Date:
Tuesday 17 - Friday 20 July 2018

Location:
European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom

Contents:
This course will cover the use of publicly available resources to manage, share, analyse and interpret metagenomics data, including marker gene, whole gene shotgun (WGS) and assembly-based approaches. Delegates will gain hands-on experience using a range of data resources and tools, interspersed with lectures. Additionally, there will be the opportunity to discuss the challenges facing researchers in the field.

This course is aimed at life scientists who are working in the field of metagenomics, in the early stages of their data analysis, and who may already have some prior experience in using bioinformatics in their research.

Learning goals:
After this course you should be able to:
- Submit data to public resources for metagenomics
- Interpret results and compare with other metagenomics datasets
- Use a range of tools to perform some data analyses
- Discuss the pitfalls and challenges in the field

Prerequisites:
Some practical sessions in the course require a basic understanding of the Unix command line and the R statistics package. If you are not already familiar with these then please ensure that you complete these free tutorials before you attend the course:
- Basic introduction to the Unix environment: http://www.ee.surrey.ac.uk/Teaching/Unix
- Basic R concept tutorials: http://www.r-tutor.com/r-introduction

Keywords:
metagenomics, bioinformatics, data analysis, course, training

Tools:
Data generation: Next Generation Sequencing, amplicon-based approaches (ribosomal  RNA), WGS, assembly
Data analysis: The EBI Metagenomics Portal, HMMER, InterPro, GO, FASTQC, diversity, coverage, metabolic and pathway analyses, tools for comparative metagenomics
Data standards and submission: European Nucleotide Archive (ENA), Genomic Standards Consortium (GSC), SRA, Webin
Public resources for metagenomics

Contact:
Georg Zeller
This email address is being protected from spambots. You need JavaScript enabled to view it.
https://www.hd-hub.de/training

Educators:
Bérénice Batut, Björn Grüning (RBC), Gabriella Rustici, Sarah Morgan (ELIXIR), Nicola Soranzo, Anil Thanki, Emily Angiolini (Earlham Institute)

Date:
2018-05-21 to 2018-05-23

Location:
Norwich, Earlham Institute

Contents:

The objectives are to further pursue some of the objectives of the ELIXIR Galaxy Community for training, e.g.:
 -improve and extend the collection of Galaxy training materials, in particular with the goal of integrating the admin training slides and tutorials
- add support for BioSchemas
- complete the upload on Zenodo of the collection of datasets used for the tutorials, which will provide stable Digital Object Identifiers (DOIs) and reliable data hosting
- plan internationalisation and localisation support in order to make the training material available to users in their own language
- implement Galaxy tutorials in e-Learning platforms
- annotate each tutorial with the existing public Galaxy instances where it can be executed (i.e. where the necessary tools and genome indexes are installed), allowing users to immediately try it on the server of their choice
- create more Docker containers providing on-demand Galaxy instances for a given tutorial.
 
Learning goals:
How to train people efficiently and how to develop Galaxy training material.

Prerequisites:
None

Keywords:
Galaxy, train-the-trainer, GTN

Tools:
Galaxy, travis, jekyll, planemo

Contact:
This email address is being protected from spambots. You need JavaScript enabled to view it.

For more information:
http://www.earlham.ac.uk/elixir-workshop-galaxy-training-material-and-skills-improvement#Abouttheevent