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Pedro Fernandes
onto Bioinformatics Training |
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As you scour through the Internet today, you may come across such hyperbolic headlines as “The genetic code has a double meaning” or “Scientists discover double meaning in genetic code”. They...
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Bioinformatician - About usGenomics Medicine Ireland is a recently incorporated company Irish life sciences company leading a large-scale research progr
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Overview This is an entry level course aimed that those with a reasonable biological background but no significant experience with bioinformatics. The course is broadly based around a series of exercises in which a combination of simple analytical tools and reference to publicly available databases is applied to the investigation of a single human gene. The training manual for the course is comprised of detailed instructions for the tasks undertaken. Included are, questions (with answers) and discussion of and the interpretation of the results achieved. Participants are asked to imagine an interest in the disease aniridia. Course exercises then provide extremely detailed instruction leading participants to discover the gene primarily associated with this disease and all that is interesting about that gene and its protein products. This course will also provide a soft introduction to Next Generation Sequencing (NGS) data analysis. This part of the course aims at providing basic skills that are needed when one needs to process NGS data, such as evaluating data quality, trimming sequences, changing data formats, visualising data, etc. Then, participants will learn how to address a simple transcriptomics problem, stepwise, using open source bioinformatics tools.
Objectives The operation of the various programs used in the exercises will be explained, but only to the extent that allows a user to select parameters intelligently and to interpret results. The course will provide participants with an awareness of a wide range of bioinformatics tools and sufficient experience to use those tools in basic investigations with a relatively high degree of user independence. In the training course design, this is intentionally built-in, to allow us to show a wide range of analytical techniques while providing enough experience to break the ice in all of them.
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Bioschemas is an open community supported by ELIXIR to improve the discoverability of biological information and help researchers to easily find data, tools, training materials and other information they need for their research. Via Sandrine Palcy
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... and our community should take the chance to be fully informed about it.
Sandrine Palcy's curator insight,
December 12, 2017 7:10 AM
Bioschemas is an open community supported by ELIXIR to improve the discoverability of biological information and help researchers to easily find data, tools, training materials and other information they need for their research.
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OPEN e-book @ http://osodos.org The goal of these resources is to give a bird's eye view of the developments in open scientific research. That is, we cover both social developments (e.g. the culture in various communities) as well as technological ones. As such, no part of the contents are especially in-depth or geared towards advanced users of specific practices or tools. Nevertheless, certain sections are more relevant to some people than to others. Specifically: The most interesting sections for Graduate students will be about navigating the literature, managing evolving projects, and publishing and reviewing. Lab technicians may derive the most benefit from the sections about capturing data, working with reproducibility in mind and sharing data. For data scientists, the sections on organizing computational projects as workflows, managing versions of data and source code, open source software development, and data representation will be most relevant. Principal investigators may be most interested in the sections on data management, data sharing, and coping with evolving projects. Scientific publishers may be interested to know how scientists navigate the literature, what the expectations are for enhanced publications, and the needs for data publishing. Science funders and policy makers may easily find value in the capturing data, data management, data sharing and navigating the literature. Science communicators may be more interested in exploring the content by starting with navigating the literature, working with reproducibility in mind and sharing data.
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Citation: Rutger Vos, & Pedro Fernandes. (2017, October 17). Pfern/OSODOS v1.0.0. Zenodo. http://doi.org/10.5281/zenodo.1015288
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A fully practical, hands-on approach will ensure that the newly acquire skills can be used with a great deal of autonomy.
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The immuno-oncology approach leverages on the unique capability of the immune system to recognize and kill tumour cells. This action is hampered by escape mechanisms put in place by tumour cells like, for instance, the engagement immune checkpoints, i.e. inhibitory molecules that modulate the amplitude and duration of immune responses. Immunotherapies that block checkpoint molecules are amongst the most promising approaches in immuno-oncology for the enhancement of antitumour immunity. Thanks to high-throughput technologies, such as next-generation sequencing (NGS) and proteomics, we have now access to large-scale tumour data that can be used to investigate the interplay between tumour and immune cells and the role of the immune system in tumour progression and response to therapy. In this course, you will learn to use bioinformatics tools and mathematical modelling techniques operating on high-throughput tumour data, in order to extract features that can be used to characterise this complex tumour-immune cell interface, such as: tumour antigens recognized by T cells tumour-infiltrating immune cells deregulated signalling pathways in cancer and immune cells A fully practical, hands-on approach will ensure that the newly acquire skills can be used with a great deal of autonomy.
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"Life scientists urgently need early training in bioinformatics skills. That is the finding of surveys by the Global Organisation for Bioinformatics Learning, Education and Training (GOBLET; http://mygoblet.org). Bioinformatics is now intrinsic to life-sciences research, but the skills necessary for basic data stewardship are still taught in only some 25% of education programmes, creating an unacceptable chasm between theory and practice." Read more...
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Nature | Correspondence | Training: Plug gap in essential bioinformatics skills Michelle D. Brazas, Sarah Blackford & Teresa K. Attwood http://www.nature.com/nature/journal/v544/n7649/full/544161c.html
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In this workshop, participants will familiarise with docking approaches to the study of protein-protein interactions (PPIs) and protein-small molecule interactions. Irreversible binders design using molecular docking and computational methods to rational drug design will be also described, as well as the functional role of the intrinsically disordered proteins. The Plenary lectures of N. Davey (10.02.2017), A. Bonvin, S. Forli and S. Moro (11.02.2017) will be open and free to everyone but require application. Practical sessions are limited to 30 participants. On the afternoon of day 3, participants can bring their own data (e.g. proteins they want to study interactions for). They will be split in groups based on the type of system they want to study (i.e protein-protein, protein-small ligand interactions or virtual screening) and will analyse it assisted by A. Bonvin and S. Forli.
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advanced content, great instructors.
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In-depth exploration of the content with 10 very active participants, Lennart Martens, Harald Barsnes and Astrid Guldbrandsen.
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Course Participants at the IB16S Introductory Bioinformatics, our entry level hands-on training course, in December 2016. Getting equipped with new skills and gaining autonomy.
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Just before the end of its 17th year, the GTPB has reached a nice number to be proud of. Thanks to all the people that have made it possible.
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In this talk, we will be surveying the ever-changing landscape of genomic analysis tools and frameworks to better understand the latest trends, and ho
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A comprehensive lecture. This is a good example on how an engineering workforce approached the computational needs ahead of us in genomics. Performance and data volume challenges are addressed.
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I have an unusual occupation. A couple of weeks ago I attended a meeting in an office furniture warehouse in a small industrial park in Vancouver. The purpose of the meeting? To explore how online learning is going to change the design of campus classrooms.
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Source of inspiration for the design of the new Bioinformatics Training Room at the Instituto Gulbenkian de Ciência. Active Learning. Online education provision. And more...
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"Wikimedia has been developing and hosting open initiatives to help the scientific community and to make ongoing research more approachable to a wider citizen audience long before Open Science became a central topic of debate among scientists, policymakers and funders. Open Science, as supported by the European Commission, aims to open up the research process by fostering open access to publications, open and FAIR data, open tools, open peer review, research integrity, stakeholder engagement and citizen science."
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Computational PANgenomics, hands-on training course
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A new theme is introduced in the GTPB
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AbstractSummary. Fully exploiting the wealth of data in current bacterial population genomics datasets requires synthesizing and integrating different types of Via Chris Upton + helpers
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with Allegra Via and Pedro Fernandes Python is a programming language that is ideal for data processing. The course will start from zero knowledge, and will introduce the participants to all the basic concepts of programming such as calculating, repeating things, making choices, reading and writing files, filtering and organising data, program logic and writing larger programs. The examples and practical sessions will mostly focus on managing biological data. In particular the sessions will cover: - parsing common file formats (Uniprot, GenBank, PDB, BLAST) - data retrieval from files and their manipulation - finding motifs in sequences - manipulating tables - plotting data The course will be highly interactive and the participants will continuously put theory into practice while learning. At the end of the course, the participants will have a good understanding of programming basics and will have acquired the skills to manage bioinformatics database record and data files. Basic Unix/Linux skills will be provided at the beginning of the course. Participants are welcome to bring to the course the "typical" text file that they may need to filter, manipulate or analyse such a table, a file in fastq or fasta format, a PDB file, etc.
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Training course en Programming in Python for Biologists
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A comprehensive hands-on course in Biostatistics in 5 days
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This is one of our "Foundations" type courses, providing a systematic and detailed review of fundamental concepts and techniques in Biostatistics. Participants can expect to go through a set of exercises that are based on biomedical problems. These exercises are preceded by short lectures that are simple to follow. The lectures are designed to provide the conceptual framework that is needed to release the training power of the exercises, not to flood the participants with formality, which will be kept to a minimum. We will make use of a highly interactive methodology, taking advantage of our well equipped Bioinformatics training room. With this approach, we expect to bring the participants to a high degree of usage independence in using the methods that we cover.
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This course is targeted for Biostatistical techniques often employed in analytical tools for high throughput data and multivariate data. Participants can expect to attend a thorough set of lectures that will reveal the conceptual frameworks that are needed to understand the methods. Extensive hands-on practice will be the main vehicle for providing the skills and user independence. To keep things in context, the course is exclusively based on biological examples. We will be using custom-built R scripts and packages that are available from the CRAN and/or Bioconductor repositories. Care has been taken not to use any proprietary data or software, so that the hands-on experience can carry on after the course, providing maximum user independence. We will be using custom-built R scripts and packages that are available from the CRAN and Bioconductor repositories.
Methodology This intensive course will introduce a relatively high number of concepts and methods. To keep it highly practical, we will spend most of the time in hands-on sessions. - We will focus on each method using examples taken from biological data. - We will then dissect the method, identifying the concepts and exploring their interrelationships. - The applicability and limitations of each method will be emphasized. - The use of the method will be illustrated using appropriate Bioinformatics tools and biological data resources.
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with Lisete Sousa and Carina Silva, long term collaborators of the GTPB
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Model-based approaches in Population Genetics and Demographic History
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Course Participants at the IB16S Introductory Bioinformatics, our entry level hands-on training course, in December 2016. Getting equipped with new skills and gaining autonomy.
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This article examines how connectivism is useful for academic advising as a theory that links previous information to current information Via Ana Cristina Pratas
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This is the first module in the 2016 Bioinformatics for Cancer Genomics workshop hosted by the Canadian Bioinformatics Workshops. This lecture is by Trevo
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Interesting talk by Trevor Pugh, a former participant of bioinformatics.ca workshops, now a fully fledged professional working in cancer genomics. Lots of material to learn from.
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Excellent explanation