Links in this page: Two Day Workshops | Galaxy Africa | Machine Learning & Omics Data
One Day Workshops | New Features of the UCSC Genome Browser | Resources for Mining & Interrogating Large-scale (Genomic and) Epidemiological Datasets | Resources and Tools for Computer-Aided Drug Discovery | H3BioNet
Description
GalaxyAfrica 2019: After a successful GalaxyAfrica2018 in South Africa, we are pleased to announce the next GalaxyAfrica workshop in collaboration with the ASBCB/ISCB Africa conference in Kumasi, Ghana. Building on the previous event, we will offer Galaxy training for researchers, and training for systems administrators who need to maintain a local installation. This year we are calling for abstracts for three oral presentations that demonstrate the use of Galaxy in your research projects.
Participants will NOT need to bring their own computers as the room provides them but you may bring your own device if preferred.
Intended audience and level
Galaxy Africa will target 2 audience groups:
Description
Machine learning has emerged as a discipline that enables computers to assist humans in making sense of large and complex data sets. With the drop in cost of sequencing technologies, large amounts of omics data are being generated and made accessible to researchers. Analyzing these complex high volume data is not trivial and the use of classical tools can not explore their full potential. Machine learning can thus be very useful in mining large omics datasets to uncover new insights that can advance the field of medicine and improve health care. The aim of this tutorial is to introduce participants to the Machine learning (ML) taxonomy and common machine learning algorithms, as well as the necessary concepts related to the experimental design. The tutorial will cover the methods being used to analyze different omics data sets by providing a practical context through the use of basic but widely used R and Python libraries. The workshop will comprise a number of hands on exercises and challenges, where the participants will acquire a first understanding of the standard ML processes as well as the practical skills in applying them on familiar problems and publically available real-world data sets.
Participants will need to bring their own computers.
Intended audience and level
This tutorial is aimed towards novices (no prior knowledge / expectations in NGS data analysis or Machine learning). However, participants should be somewhat familiar with:
Participants should bring their own laptops for the practical exercises.
Description
The UCSC Genome Browser workshop will be a one-day experience consisting of a half day of presentation showing the latest tools and features of this large and complicated online software package. The afternoon session will be hands-on problem solving to solidify the learning and offer opportunity to discuss participant-generated questions. Specifically, the new data types, interact and barChart, available for user-generated custom tracks will be presented, as will the very new Genome Browser API.
Participants will NOT need to bring their own computers as the room provides them but you may bring your own device if preferred.
Intended audience and level
The session is for bioinformatics professionals and students and molecular biologists, typically at the graduate student level or above. Participants should have considerable background in Molecular Biology and Genomics and at least a basic understanding of databases. Some previous familiarity with the Genome Browser will be useful. The session should be considered intermediate in difficulty. The session should be considered Intermediate in molecular biology expertise and Introductory/Intermediate in bioinformatics/programming/genomics.
Description
EuPathDB.org is a free, online resource intended to empower investigators with tools/materials necessary to interrogate data associated with global infectious disease. This workshop will introduce users to ClinEpiDB.org focusing on clinical and epidemiological datasets. the majority of sessions will be hands-on, facilitating understanding of foundational epidemiologic and exploratory data analysis concepts. Participants should have a basic understanding of epidemiologic research, data collection and data storage but ClinEpiDB is intended for novice data managers or analysts.
Participants will need to bring their own computers.
Intended audience and level
The ideal participant has a desire to become an expert user of ClinEpiDB, either as a biologist driven by infectious disease, public health or epidemiologic research questions, or as an informaticist interested in exploring available datasets with the potential to carry out novel analysis, or develop new analytical tools for broader distribution (perhaps in partnership with the EuPathgDB team). Attendees should have a basic understanding of epidemiologic research, data collection and data storage … but note that ClinEpiDB is intended for exploratory data analysis, rather than as a cutting-edge research tool for professional statisticians and epidemiologists.
Description
Advances in computational technologies coupled with rapid growth in available chemical and genomic data provide multifaceted in silico approaches to the discovery of new bioactive compounds for diseases like tuberculosis, malaria, HIV etc that are burdening the world. Supported by the Wellcome Genome Campus Advanced Courses and Scientific Conferences, this introductory level workshop for Postgraduate students and researchers in life sciences, offers participants an overview of computational resources and tools, basic bioinformatics and chemoinformatics techniques used in the early stages of drug discovery as well as data retrieval from related databases. Activities will consist of presentations, demonstrations and practical activities to give participants hands - on exercises.
Participants will NOT need to bring their own computers as the room provides them but you may bring your own device if preferred.
Intended audience and Learning Outcomes
Postgraduate students and researchers in the life sciences (including the fields of computational biology/chemistry, chemistry, biology etc.). The material is considered introductory.
By the end of the course, participants will be able to:
Attendance is limited to 30. Participants are expected to bring their own laptops. The course will not cover programming.
Description
Research funding agencies are increasingly demanding the submission of a data management plan (DMP) as part of the application. A DMP serves as an instrument for managing the research data generated in a project. It describes what data to collect or generate in the course of the work and what should be done with it during the entire data lifecycle (eg storage, publication, citation, long-term availability, anonymization, reuse, etc.). The aim is to make not only publications but also research data findable, accessible, comprehensible and reusable. The availability of research data in the sense of open science can be ensured by data archives or repositories. Nevertheless, data protection and copyright aspects must also be considered.
The H3ABioNet workshop deals with the core elements of the DMP and introduces the single stages of the data life cycle from the perspective of bioinformatics and genomics research practice in human health and agriculture.
The workshop also discusses strategies for compatibility of the requirements of open science and data protection - such as anonymization, informed consent, licensing or access restrictions. In addition, useful data archives and repositories and their possible uses will also be presented.
Participants will need to bring their own computers.
Intended audience and level
This is an introductory session to data management plan aiming to help PhD students, Post-doctoral and early career researchers understand the DM process and how to write a good DMP to apply for grants and/or to organize their projects data. This workshop will also cover other aspects related to data management such as the process of making data FAIR and ethical aspects related to data sharing.