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  • Plant research
  • Wet-lab researchers and bioinformaticians9
  • Bioinformaticians and wet-lab biologists who can program in Perl, Python or R.4
  • Bioinformaticians and wet-lab biologists who can program in Python or R.3
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  • This course is aimed at advanced PhD students and post-doctoral researchers who are applying or planning to apply high throughput sequencing technologies in cancer research and wish to familiarise themselves with bioinformatics tools and data analysis methodologies specific to cancer data. Familiarity with the technology and biological use cases of high throughput sequencing is required, as is some experience with R/Bioconductor (basic understanding of the R syntax and ability to manipulate R objects) and the Unix/Linux operating system.3
  • This workshop is aimed at wet-lab scientists and bioinformaticians. Participants should have degree-level understanding of molecular biology/genetics and be proficient at using web browsers.3
  • Wet-lab Researchers3
  • PhD Students2
  • PhD students2
  • Principal Investigators2
  • The summer school is intended for researchers (primarily PhD and post-docs) using or planning to use biomolecular modeling and simulation in their everyday research. Familiarity with Linux and some basic knowledge of molecular modelling software is a requirement.2
  • This course is aimed at individuals working across life sciences who have little or no experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their knowledge and skills further. No previous knowledge of programming is required for this course; group projects may give you the opportunity to learn basic programming, but participants will be supported in this by their mentors. Depending on your chosen project, an introductory programming tutorial may be given as homework prior to attending the course.2
  • This workshop is aimed at new and experienced managers of bioinformatics core facilities, or other facilities that support their users to analyse and interpret large biomolecular data sets.  This course will not provide a platform for teaching hands-on bioinformatics analysis.2
  • Any students, postdocs or RAs with an interest in HPC1
  • Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their knowledge and skills further. No previous knowledge of programming is required for this course; group projects may give you the opportunity to learn basic programming, but participants will be supported in this by their mentors. Depending on your chosen project, an introductory programming tutorial may be given as homework prior to attending the course. Though programming skills are not a prerequisite for attending the course, we will ask participants to specify their current level of programming skills in the applications. This will allow the mentors to target the group projects better to the skills and needs of the final course participants.1
  • Applicants must be employed within Latin America only. A relevant undergraduate-level degree in a biology or computer science / informatics degree would be helpful. You may have an MSc/PhD in biology, computer science and/or bioinformatics, or relevant experience through employment. Please note this course will be taught in English, however some trainers are fluent in either Spanish/Portuguese, and can offer language support where feasible. Priority will also be given to those who have not attended a CABANA event yet.   You may be expected to watch pre-recorded videos and complete short assignments prior to attending the workshop. This should amount to up to 5 hours of work.  1
  • Applicants should be researchers who are using large multi-omics datasets to infer systems biology models. This is an advanced-level course, and so we will select applicants who already have some experience (ideally 1-2 years) of working with systems biology modelling or related large-scale multi-omics data analysis. Additionally, applicants will be expected to have a working knowledge of using Linux commands, and experience of using a programming language (e.g. Python or Perl).1
  • Bench biologists1
  • Bioinformaticians1
  • Bioinformaticians and wet-lab biologists1
  • Bioinformaticians and wet-lab biologists who can program1
  • Bioinformaticians and wet-lab biologists who can program in Perl, Python or R. The Ensembl browser workshop is a pre-requisite for this course.1
  • Boinformaticians1
  • Core Facility Managers1
  • Early Career Researcher1
  • El curso está dirigido para académicos de países latinoamericanos, que incluyen estudiantes de posgrados, postdocs e investigadores iniciando su carrera científica. En todos los casos, se prefiere que estén trabajando en metodologías moleculares para el estudio de enfermedades tropicales. Conocimiento en biología molecular es requerido, al igual que estar familiarizados con conceptos básicos en Bioinformática. Esperamos tener alrededor de 30 participantes de diferentes países latinoamericanos.   Se alienta especialmente a participantes de grupos étnicos y de géneros subrepresentados a postularse para este curso. Tenga en cuenta que este curso se impartirá en español. Sin embargo, algunos de los formadores dominan el inglés y/o el portugués, por lo que se ofrecerá apoyo lingüístico cuando sea posible. Se dará prioridad de asistencia a aquellos que aún no hayan asistido a un evento de CABANA.  1
  • Este curso introductorio está destinado principalmente a becaries doctorales de iniciación, que buscan dar sus primeros pasos en el uso de R para análisis de datos genómicos. El curso está dirigido únicamente a académicos de países de América Latina, excluyendo a Chile y Uruguay por restricciones de financiamiento.   Prerrequisitos No es necesario tener conocimiento previo o experiencia en línea de comandos. Se valorarán los conocimientos de biología molecular.  Dado que la modalidad de cursada será virtual (sincrónica/ asincrónica) cada uno debe contar con acceso a PC y conexión a internet estable. No se requiere la instalación de programas, ya que se proveerá acceso a herramientas virtuales (ejemplo: RStudio virtual). Tenga en cuenta que este curso se impartirá en español, aunque los formadores dominan el inglés y pueden ofrecer apoyo lingüístico cuando sea posible. Se dará prioridad en la inscripción a estudiantes de doctorado de iniciación.  Alentamos la postulación de todes les becaries de grupos subrepresentados a este taller. Se dará prioridad de asistencia a aquellos que aún no hayan asistido a un evento de CABANA.1
  • Experience from previous years has led to preference being given to candidates who: are doctoral candidates in the early to middle stages of their thesis research already have some familiarity with phylogenetic methods (i.e. have already used some of the relevant tools) have already collected/assembled a molecular sequence dataset to analyze in their work have experience of working in a Unix/Linux command-line environment We will also select a small number of participants that already work in bioinformatics labs, to intensify collaboration between early career stage biologists and bioinformaticians. Applicants from labs with a strong focus on computational molecular evolution methodology need to carefully outline their motivation for attending the course in this context, since they have ready access to expert supervision and are likely to be very skilled already in the topics we teach, or are in the course of becoming very skilled therein. The course is also suitable for established researchers who would like to refresh their memory of modern statistical methods for phylogenetic analysis of genomic sequence data and to interact with developers of such methods.1
  • Experimental Researchers1
  • Graduate students1
  • Institutions and other external Institutions or individuals1
  • Life Science Researchers1
  • Life science researchers who are new to high performance computing1
  • No prior experience of bioinformatics is required, but an interest in finding out more about genetic variation resources and an undergraduate level understanding of biology would be of benefit. Experience with command line usage would be very beneficial. This workshop will focus specifically on human genetic variation. Prerequisite We encourage the audience to go through our online course on human genetic variation prior to attending the workshop - www.ebi.ac.uk/training/online/course/human-genetic-variation-i-introduction-2019 .1
  • No prior experience of bioinformatics is required, but an interest in finding out more about genetic variation resources and an undergraduate level understanding of biology would be of benefit. Experience with command line usage would be very beneficial. This workshop will focus specifically on human genetic variation. We encourage the audience to go through our introductory online course on human genetic variation prior to attending the workshop.1
  • No prior experience of bioinformatics is required, but an interest in finding out more about variation resources and an undergraduate level understanding of biology would be of benefit. This workshop will focus specifically on human variation.1
  • Operators, developers and managers of bioinformatics resources1
  • Participants from both experimental and theoretical backgrounds would benefit from this workshop.1
  • Postdocs and Staff members from the University of Cambridge1
  • Researchers1
  • Researchers with an interest in metabolomics and its applications1
  • Support Staff1
  • The BioExcel school is intended for primarily PhD and post-doctoral researchers using or planning to use biomolecular modeling and simulation in their everyday research. Familiarity with Linux and basic knowledge of molecular modelling software is a requirement.1
  • The BioExcel school is intended for researchers (primarily PhD and post-docs) using or planning to use biomolecular modeling and simulation in their everyday research. Familiarity with Linux and basic knowledge of molecular modelling software is a requirement.1
  • The course is aimed at PhD students and post-doctoral researchers who are starting to use high-throughput sequencing technologies and bioinformatics methods in their research. The content is most applicable for those working with eukaryotic genomes, especially in the area of human genetics and rare-disease research. Participants will require a basic knowledge of the Unix command line and the Ubuntu 18 operating system. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Please note: participants without basic knowledge of these resources will have difficulty in completing the practical sessions.1
  • The course is aimed at early-stage researchers working in the field of ecological genomics who want to make bioinformatics a significant part of their research. The course will also support the research of the Moore Foundation symbiosis community, in particular those working on the Aquatic Symbiosis Genomes project. Participants will require a basic knowledge of the Unix command line and the Ubuntu 18 operating system. We recommend taking these tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Experience with both R and Python will also be essential for the computational sessions. Participants without basic knowledge of these resources will struggle to learn the practical skills developed during the course.1
  • The course is aimed at individuals working in immunology research who have minimal experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their skills and knowledge further. Participants will need a basic knowledge of the Unix command line, and the R statistical package. We recommend these free tutorials: Introduction to the Unix environment – http://www.ee.surrey.ac.uk/Teaching/Unix/ Basic R concepts – http://www.r-tutor.com/r-introduction1
  • The course is aimed at individuals working in immunology research who have minimal experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their skills and knowledge further. Participants will require a basic knowledge of the Unix command line, and the R statistical package. We recommend these free tutorials: Introduction to the Unix environment – http://www.ee.surrey.ac.uk/Teaching/Unix/ Basic R concepts – http://www.r-tutor.com/r-introduction1
  • The course is aimed at research scientists with a minimum of a degree in a biological discipline, including laboratory and clinical staff, as well as specialists in related fields. The practical elements of the course will take raw data from a proteomics experiment and analyse it. Participants will be able to go from MS spectra to identifying and quantify peptides and finally to obtain lists of protein identifiers that can be analysed further using a wide range of resources. The final aim is to provide attendees with the practical bioinformatics knowledge they need to go back to the lab and process their own data when collected.1
  • The course is aimed at research scientists with a minimum of a degree in a biological discipline, including laboratory and clinical staff, as well as specialists in related fields. The practical elements of the course will take raw data from a proteomics experiment and analyse it. Participants will be able to go from MS spectra to identifying and quantifying peptides, and finally to obtaining lists of protein identifiers that can be analysed further using a wide range of resources. The final aim is to provide attendees with the practical bioinformatics knowledge they need to go back to the lab and process their own data when collected.1
  • The course is aimed at research scientists with a minimum of a degree in a biological discipline, including laboratory and clinical staff, as well as specialists in related fields. The practical elements of the course will take raw data from a proteomics experiment and analyse it. Participants will be able to go from MS spectra, to identifying peptides and finally to lists of protein identifiers that can be analysed further using a wide range of resources. The final aim is to provide attendees with the practical bioinformatics knowledge they need to go back to the lab and process their own data once it has been generated.1
  • The course is aimed at researchers interested in core bioinformatics techniques, sequence searching and alignment. No prior experience of bioinformatics is required, but familiarity with biological databases and web tools would help. An undergraduate level understanding of molecular biology would be of benefit to those attending the workshop.1
  • The course is aimed at wet-lab scientists working in the field of immunology who wish to learn more about available data and tools that can help them in their research. 15 places are reserved for early-stage researchers from the ENLIGHT-TEN+ project.  1
  • The course is suitable for graduate students and young researchers with a background in biology who are keen to become proficient bioinformaticians within the fields of genomics and/or transcriptomics. We will start with the basics, so students with no prior programming knowledge are welcome. We have a number of Linux computers that you can use, and you can bring your own laptops*.  Please note this course will be taught in English, however the trainers are fluent in either Spanish or Portuguese, and can offer language support where feasible. A number of travel fellowships are available for this course - early-stage researchers and researchers from underrepresented groups are especially encouraged to apply for CABANA travel fellowships. You can apply for travel fellowships via the course application form. *If you bring your own laptop (any operating system is fine), you must have installed the following programs: R (at least version 3.5), the latest Rstudio and Bioconductor.  To download R please visit: https://www.r-project.org/ To download RStudio please visit: https://www.rstudio.com/products/rstudio/download/ Bioconductor must be downloaded and installed via R, instructions on how to do this can be found here: https://www.bioconductor.org/install/1
  • The primary target audience is researchers working in FAANG projects, including AQUA-FAANG, GENE-SWitCH and BovReg. Familiarity with running bioinformatic analysis of sequencing data in a Unix environment is essential for those attending this training.1
  • The summer school is intended for researchers (primarily PhD and post-docs) using or planning to use biomolecular modeling and simulation in their everyday research. Familiarity with Linux and basic knowledge of molecular modelling software is a requirement.1
  • The workshop is aimed at PhD students and researchers at The Open University. Participants would benefit from an undergraduate knowledge of the biological or chemical life sciences, or a background in human health and disease.1
  • The workshop is aimed at a general audience of biologists and bioinformaticians working with non-coding RNA who are interested in using RNAcentral and Rfam, or for users who would like to bring their projects and discuss them with the RNAcentral and Rfam teams. A basic familiarity with web browsing and an undergraduate level knowledge of molecular biology is recommended for this course. Familiarity with Unix/Linux command line is desirable for part of the course. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/resources/free-courses/introduction...1
  • The workshop is aimed at biologists and computer scientists in Latin American countries only (excluding Chile and Uruguay due to funding restrictions) wanting to learn the basics of network analysis and biological data cure for clinically relevant pathogens. Trainees should be undertaking research at postgraduate-level upwards focusing on infectious diseases. No previous experience using interaction data resources is needed. Please note this course will be taught in English, however the trainers are fluent in either Spanish/Portuguese, and can offer language support where feasible. Priority will also be given to those who have not attended the CABANA event yet. Researchers who apply for CABANA courses should have projects in one or more of the CABANA challenge areas (sustainable crop production, communicable diseases, protection of biodiversity). Scientists from underrepresented ethnic and gender groups are especially encouraged to apply for this workshop, for example women and those with Black and/or Indigenous heritage.   Prerequisites Participants will require a basic knowledge of the Unix command line, and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment:  www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux:  https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials:  www.r-tutor.com/r-introduction1
  • The workshop is aimed at biologists and computer scientists wanting to learn the basics of network analysis and biological data curation for clinically relevant pathogens. Trainees should be undertaking research at postgraduate-level upwards focusing on infectious diseases. No previous experience using interaction data resources is needed. Please note this course will be taught in English, however the trainers are fluent in either Spanish/Portuguese, and can offer language support where feasible. Priority will also be given to those who have not attended a CABANA event yet. Travel fellowships are available for this course - early-stage researchers and researchers from underrepresented groups are especially encouraged to apply for CABANA travel fellowships. You can apply for travel fellowships via the course application form. Up to 30% of workshop delegates can be awarded fellowships and these are normally awarded by reimbursement after the event. Prerequisites Participants will require a basic knowledge of the Unix command line, and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction1
  • The workshop is open to postdocs in Cambridge, including candidates from University and affiliated institutions1
  • The workshop is suitable for scientists that are producing sequence data and require a platform to publish it1
  • This course is aimed at PhD students and post-doctoral researchers who are applying or planning to apply high throughput sequencing technologies in cancer research and wish to familiarise themselves with bioinformatics tools and data analysis methodologies specific to cancer data. Familiarity with the technology and biological use cases of high throughput sequencing (HTS) is required, as is some experience with R/Bioconductor (basic understanding of the R syntax and ability to manipulate R objects) and the Unix/Linux operating system.1
  • This course is aimed at PhD students and post-doctoral researchers who are using high-throughput sequencing technologies and bioinformatics methods in their research. The content is most applicable for those working with eukaryotic genomes, human genetics and in rare disease research. Participants will require a basic knowledge of the Unix command line, the Ubuntu 16 operating system and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction Please note: participants without basic knowledge of these resources will have difficulty in completing the practical sessions.1
  • This course is aimed at PhD students and postdoctoral researchers needing to learn about methods and approaches for manipulating and analysing livestock genomic data. It will help those wanting to start basic identification of genetic variation, annotating function to genomic data, and using public data to interpret new findings. Participants will require a basic knowledge of the Unix command line, the Ubuntu 18 operating system and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction Regardless of your current knowledge we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.  1
  • This course is aimed at advanced PhD students and post-doctoral researchers who are applying or planning to apply high throughput sequencing technologies and bioinformatics methods in their research. Familiarity with the technology and biological use cases of high throughput sequencing is required, as is some experience with R/Bioconductor.1
  • This course is aimed at advanced PhD students and post-doctoral researchers who are currently working with large-scale omics datasets with the aim of discerning biological function and processes. Ideal applicants should already have some experience (ideally 1-2 years) working with systems biology or related large-scale multi-omics data analyses. Applicants are expected to have a working knowledge of the Linux operating system and the ability to use the command line. Experience of using a programming language (i.e. Python) is highly desirable, and while the course will make use of simple coding or streamlined approaches such as Python notebooks, higher levels of competency will allow participants to focus on the scientific methodologies rather than the practical aspects of coding and how they can be applied in their own research. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Python turorial: https://www.w3schools.com/python/ R tutorial: https://www.datacamp.com/courses/free-introduction-to-r Regardless of your current knowledge we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.1
  • This course is aimed at advanced PhD students, post-doctoral researchers, and non-academic scientists who are currently working with large-scale omics datasets with the aim of discerning biological function and processes. Ideal applicants should already have some experience (ideally 1-2 years) working with systems biology or related large-scale (multi-)omics data analyses. Applicants are expected to have a working knowledge of the Linux operating system and the ability to use the command line. Experience of using a programming language (i.e. Python) is highly desirable, and while the course will make use of simple coding or streamlined approaches such as Python notebooks, higher levels of competency will allow participants to focus on the scientific methodologies rather than the practical aspects of coding and how they can be applied in their own research. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Python tutorial: https://www.w3schools.com/python/ R tutorial: https://www.datacamp.com/courses/free-introduction-to-r Regardless of your current knowledge we encourage successful participants to use these to prepare for attending the course and future work in this area. Selected participants will also be sent materials prior to the course. These might include pre-recorded talks and required reading that will be essential to fully understand the course.1
  • This course is aimed at anyone interested in finding out more about protein biology. No prior experience of bioinformatics is required, but participants should have an undergraduate level understanding of biology. For those who wish to attend the session on programmatic access a prior knowledge of coding/programming would be of benefit. For an introduction to the concept of web services and how you can use them to access the tools and data available at EMBL-EBI please watch our webinar.1
  • This course is aimed at anyone interested in finding out more about protein biology. No prior experience of bioinformatics is required, but participants should have an undergraduate level understanding of biology. For those who wish to attend the sessions on programmatic access, prior knowledge of coding/programming would be of benefit. For an introduction to the concept of web services and how you can use them to access the tools and data available programmatically, please watch this EMBL-EBI, programatically webinar.1
  • This course is aimed at bench biologists working in the area of discovery science who want to learn more about bioinformatics tools and resources. No prior knowledge of bioinformatics is required and no experience of programming or the use of Unix / Linux is necessary.1
  • This course is aimed at both new and established investigators who lead a research team which currently uses bioinformatics, or where bioinformatics will be a component in future research. No prior knowledge of bioinformatics, or experience of analysis is required for this course.1
  • This course is aimed at both new and established investigators who lead a research team which currently uses bioinformatics, or where bioinformatics will be a component in future research. No prior knowledge of bioinformatics, or experience of analysis is required for this course. Applications are invited from investigators working in all settings, including academic, clinical and industrial organisations.1
  • This course is aimed at both new and established investigators who lead a research team which currently uses bioinformatics, or where bioinformatics will be a component in future research. No prior knowledge of bioinformatics, or experience of analysis is required for this course. Applications are invited from investigators working in all settings, including academic, clinical, and industrial organisations.1
  • This course is aimed at experimental biologists, bioinformaticians and mathematicians who have just started in systems biology, are familiar with the basic terminology in this field and who are now keen on gaining a better knowledge of systems biology modelling approaches to understand biological and biomedical problems. A working knowledge of the Linux operating system and ability to use the command line or experience of using a programming language (e.g Python) would be a benefit but is not mandatory. An undergraduate knowledge of molecular and cellular biology or some background in mathematics is highly beneficial. 1
  • This course is aimed at experimental biologists, bioinformaticians and mathematicians who have just started in systems biology, are familiar with the basic terminology in this field and who are now keen on gaining a better knowledge of systems biology modelling approaches to understand biological and biomedical problems. An experience of using a programming language (e.g Python, R, Matlab) would be a benefit but is not mandatory. An undergraduate knowledge of molecular and cellular biology or some background in mathematics is highly beneficial.1
  • This course is aimed at experimental biologists, bioinformaticians and mathematicians who have just started in systems biology, are familiar with the basic terminology in this field and who are now keen on gaining a better knowledge of systems biology modelling approaches to understand biological and biomedical problems. An experience of using a programming language (e.g Python, R, Matlab) would be a benefit but is not mandatory. An undergraduate knowledge of molecular and cellular biology or some background in mathematics is highly beneficial. Priority will be given to applicants from low and middle income countries - however applications are open to candidates from all over the world.1
  • This course is aimed at experimental biologists, bioinformaticians and mathematicians who have just started in systems biology, are familiar with the basic terminology in this field and who are now keen on gaining a better knowledge of systems biology modelling approaches to understand biological and biomedical problems. An experience of using a programming language (e.g Python, R, Matlab) would be a benefit but is not mandatory. An undergraduate knowledge of molecular and cellular biology or some background in mathematics is highly beneficial. 1
  • This course is aimed at individuals working across biological sciences who have little or no experience in bioinformatics. Applicants are expected to be at an early stage of using bioinformatics in their research with the need to develop their skills and knowledge further. No previous knowledge of programming / coding is required for this course.1
  • This course is aimed at life science researchers needing to learn more about the basic processing of raw RNA-Seq data and downstream analysis. It will help those wanting to learn how to interpret gene expression data and explore results of biological significance from processed data. Participants will require a basic knowledge of the Unix command line, the Ubuntu 18 operating system and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction Regardless of your current knowledge we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.1
  • This course is aimed at life science researchers wanting to learn more about processing RNA-Seq data and later downstream analysis. It will help those wanting a basic introduction to handling RNA-Seq data, guiding them through several common approaches that can be applied to their own datasets. It features taught and practical sessions that cover how to interpret gene expression data and learn more about the biological significance of certain results. Participants will require a basic knowledge of the Unix command line, the Ubuntu 18 operating system and the R statistical packages. We recommend these free tutorials:

 Basic introduction to the Unix environment:
 www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux:
 https://training.linuxfoundation.org/free-linux-training
 Basic R concept tutorials: 
www.r-tutor.com/r-introduction Regardless of your current knowledge we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.1
  • This course is aimed at life science researchers wanting to learn more about processing RNA-seq data and later downstream analysis. It will help those wanting a basic introduction to handling RNA-seq data, guiding them through several common approaches that can be applied to their own datasets. It features taught and practical sessions that cover how to interpret gene expression data and learn more about the biological significance of certain results. Participants will require a basic knowledge of the Unix command line, the Ubuntu 18 operating system, and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction Regardless of your current knowledge, we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.1
  • This course is aimed at life science researchers wanting to learn more about processing RNA-seq data and later downstream analysis. It will help those wanting a basic introduction to handling RNA-seq data, guiding them through several common approaches that can be applied to their own datasets. It features taught and practical sessions that cover how to interpret gene expression data and learn more about the biological significance of certain results. Participants will require a basic knowledge of the Unix command line, the Ubuntu 18 operating system, and the R statistical packages. We recommend these free tutorials: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training Basic R concept tutorials: www.r-tutor.com/r-introduction Regardless of your current knowledge, we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.1
  • This course is aimed at life scientists who are working in the field of metagenomics and are currently in the early stages of data analysis. Participants should have some prior experience of using bioinformatics in their research. The 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: www.ee.surrey.ac.uk/Teaching/Unix Basic R concept tutorials: www.r-tutor.com/r-introduction1
  • This course is aimed at life scientists who are working in the field of metagenomics and are currently in the early stages of data analysis. Participants should have some prior experience of using bioinformatics in their research. The practical sessions in the course require a basic understanding of the Unix command line and the R statistics package. Participants should ensure that they complete these free tutorials before attending the course: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Basic R concept tutorials: www.r-tutor.com/r-introduction1
  • 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. 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: www.ee.surrey.ac.uk/Teaching/Unix Basic R concept tutorials: www.r-tutor.com/r-introduction1
  • This course is aimed at new managers of core facilities or those looking to embark on developing such a facility within their organisation.1
  • This course is aimed at researchers at any career stage within the University of Pavia and Institute of Molecular Genetics who are working with and/or generating their own genomic and biomolecular datasets. No knowledge of programming is required, but an undergraduate level knowledge of Biology / molecular biology would be beneficial.1
  • This course is aimed at researchers at graduate level upwards within Latin America who are working with and/or generating their own crop genomic data or who are working on genotyping technologies, including data analysis software development.  Prerequisites: Basic computational or previous bioinformatics experience is required for this workshop, such as basic commands in R. Undergraduate-level knowledge of plant biology would be an advantage.  Please note this course will be taught in English. There will be assistants fluent in Spanish who can offer language support where feasible.1
  • This course is aimed at researchers currently working with zebrafish and generating genomic and functional data. Graduate students, postdoctoral fellows, research scientists and faculty are encouraged to apply.  Little to no experience with RNA-seq analysis is required, however, applicants who have already generated an RNA-seq dataset from zebrafish samples relevant to their project will gain the most benefit from this course.  Some experience with R is beneficial.  1
  • This course is aimed at researchers from Masters-level upwards within Latin America who are working with and/or generating their own plant genomic and transcriptomic datasets.  Prerequisites: Some basic computational or previous bioinformatics experience is required for this workshop, particularly using the UNIX operating system (basic command line skills) and R. You may find the resources below useful: Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix Introduction and exercises for Linux: https://training.linuxfoundation.org/free-linux-training  Basic R concept tutorials: www.r-tutor.com/r-introduction  Important: All participants must bring a laptop for the course. We will use a virtual machine (VM) provided by instructors for the course practical sessions. All laptops must be of 64-bit architecture with any Operating System and have at least 60 GB free space. Please also note: this course will be taught in Spanish, however the trainers are fluent in English and can offer language support where feasible. A number of travel fellowships are available for this course - early-stage researchers and researchers from underrepresented groups are especially encouraged to apply for CABANA travel fellowships. You can apply for travel fellowships via the course application form.1
  • This course is aimed at researchers from postgraduate level upwards interested in using R to analyse genomics data for crop biodiversity studies. Please note this course will be taught in English, however the trainers are fluent in Spanish, and can offer language support where feasible. A number of travel fellowships are available for this course - early-stage researchers and researchers from underrepresented groups are especially encouraged to apply for CABANA travel fellowships. You can apply for travel fellowships via the course application form.   Prerequisites An undergraduate level degree in plant biology or a related discipline would be an advantage.  You will need to know basic commands in R in order to get the most from this course, though a review of basic concepts and commands in R will be covered on the first day. You can find a good introduction to R here: http://www.r-tutor.com/r-introduction You will also need to bring a laptop with R installed and working knowledge of how to navigate your working directory effectively using R commands. To download R please visit: https://www.r-project.org/ To download RStudio please visit: https://www.rstudio.com/products/rstudio/download/1
  • This course is aimed at researchers who are generating, planning on generating, or working with single cell RNA sequencing data. Prerequisites Participants will be using a Galaxy resource in-depth. Participants may also be asked to do brief coding in R. Please ensure that you complete the free tutorials before you attend the course: Introduction to Galaxy: https://galaxyproject.org/tutorials/g101/ Basic R concept tutorials: www.r-tutor.com/r-introduction There are other tutorials here, although they are not required: https://galaxyproject.org/learn/1
  • This course is aimed at researchers who are generating, planning on generating, or working with single cell RNA sequencing data.  Prerequisites Participants will be using a Galaxy resource in-depth. Participants may also be asked to do brief coding in R. Please ensure that you complete the free tutorials before you attend the course: Introduction to Galaxy: https://galaxyproject.org/tutorials/g101/ Basic R concept tutorials: www.r-tutor.com/r-introduction There are other tutorials here, although they are not required: https://galaxyproject.org/learn/1
  • This course is aimed at researchers who are generating, planning on generating, or working with single cell RNA sequencing or image-based transcriptomics data. This course will not cover any aspects of data analysis, therefore no prior computational knowledge is required.1
  • This course is aimed at researchers who are new to the field of metabolomics and wish to learn about the process of conducting a metabolomics study. Attendees will gain an understanding of a standardised workflow, from experimental design to data acquisition and analysis, and will benefit those who are planning to integrate metabolomics into their work, either moving into the field or as an investigator from other omics. We will primarily focus on a basic introduction to metabolomics with worked examples using a predesigned LC-MS analysis workflow. The course assumes little prior knowledge of using bioinformatics tools.1
  • This course is aimed at researchers who are new to the field of metabolomics and wish to learn about the process of developing a metabolomics study. Attendees will gain an understanding of the workflow process and some of the analysis techniques and so should benefit those who are planning to include metabolite profiling in their work, either moving into the field or as an addition to other omics. We will primarily focus on a basic introduction to metabolomics with a worked example using a predesigned LC-MS analysis workflow. The course assumes little prior knowledge of using bioinformatics tools.1
  • This course is aimed at researchers with little to no experience in big data analysis and who are generating, planning on generating, or working with single cell RNA sequencing data.1
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