Filter

• Sort

• • Earliest Latest Most recent Last modified Title descending Title ascending

• Filter Clear filters

• • Date added
  • In the last 24 hours
  • In the last 1 week
  • In the last 1 month
• • Start
  • -
• • Content provider
  • European Bioinformatics Institute (EBI)468
  • Australian BioCommons1
  • BioExcel1
  • GTN1
  • Show N_FILTERS more
• • Keyword
  • Proteins (proteins)69
  • UniProt: The Universal Protein Resource64
  • Ensembl59
  • DNA & RNA (dna-rna)56
  • Protein Data Bank in Europe36
  • Ensembl Variant Effect Predictor29
  • Ensembl Genomes26
  • API25
  • Europe PubMed Central19
  • AlphaFold Database18
  • InterPro18
  • Programmatic access18
  • PDBe17
  • Literature (literature)15
  • Gene expression (gene-expression)14
  • Cross domain (cross-domain)13
  • Expression Atlas13
  • IntAct Molecular Interaction Database13
  • MGnify10
  • Molecular building blocks of life10
  • Reactome pathways database10
  • MetaboLights: Metabolomics repository and reference database9
  • Microbial ecosystems webinar9
  • Open access9
  • Plant webinar series9
  • AI8
  • Complex Portal8
  • European Variation Archive8
  • Structural biology8
  • Structures (structures)8
  • BioImage Archive7
  • ChEMBL: Bioactive data for drug discovery7
  • European Nucleotide Archive7
  • FAIR7
  • Structural data7
  • protein7
  • spatial transcriptomics7
  • Advances in spatial omics6
  • Cell-level simulations6
  • Chemical biology (chemical-biology)6
  • Data integration6
  • RNAcentral6
  • UniProtKB6
  • AI in bioinformatics5
  • BioModels database5
  • BioStudies Database5
  • Biocuration5
  • Bioimage analysis5
  • ChEMBL5
  • Data management5
  • Electron microscopy5
  • Europe PMC5
  • Genome5
  • Light microscopy5
  • Machine learning models5
  • Open Targets Platform5
  • Pangenomics5
  • PerMedCoE5
  • Personalised medicine5
  • Preprints5
  • Scientific computing5
  • Systems (systems)5
  • Transcriptomics5
  • Artificial intelligence4
  • Electron Microscopy Public Image Archive - EMPIAR4
  • European Genome-phenome Archive4
  • Galaxy4
  • Gene transcripts4
  • Multiomics4
  • NHGRI-EBI GWAS Catalog4
  • Protein science4
  • PubMed4
  • QM/MM4
  • RNA-Seq4
  • Spatial transcriptomics4
  • Transcriptome assembly4
  • UniProt4
  • programmatic access4
  • BLAST3
  • BioSamples3
  • Biocurator3
  • Computational simulations3
  • Data analysis3
  • Data protection3
  • Data sharing3
  • EBI BioSamples Database3
  • EOSC-Life3
  • EVA3
  • Electron Microscopy Data Bank3
  • Genetic variants3
  • International Mouse Phenotyping Consortium Portal3
  • Job Dispatcher3
  • LLMs3
  • Metadata3
  • PRIDE: The Proteomics Identifications Database3
  • Pfam3
  • Protein Data Bank in Europe - Knowledge Base3
  • Protein families3
  • Protein function3
  • Proteins3
  • Show N_FILTERS more
• • Scientific topic
  • Bioinformatics36
  • Protein function analysis25
  • Protein function prediction25
  • Protein structure22
  • Active learning21
  • Ensembl learning21
  • Kernel methods21
  • Knowledge representation21
  • Machine learning21
  • Neural networks21
  • Protein bioinformatics21
  • Protein databases21
  • Protein informatics21
  • Proteins21
  • Recommender system21
  • Reinforcement learning21
  • Supervised learning21
  • Unsupervised learning21
  • Protein structures20
  • Genome annotation18
  • Molecular diagnostics18
  • Personalised medicine18
  • Precision medicine18
  • Biomathematics17
  • Comparative transcriptomics17
  • Computational biology17
  • Function analysis17
  • Functional analysis17
  • Mathematical biology17
  • Theoretical biology17
  • Transcriptome17
  • Transcriptomics17
  • RNA-Seq analysis16
  • Bioimaging15
  • Biological imaging15
  • Exomes15
  • Genomes15
  • Genomics15
  • Personal genomics15
  • Synthetic genomics15
  • Viral genomics15
  • Whole genomes15
  • Antimicrobial stewardship14
  • Community analysis14
  • Data archival14
  • Data archiving14
  • Data curation14
  • Data curation and archival14
  • Data preservation14
  • Database curation14
  • Environmental microbiology14
  • Medical microbiology14
  • Microbial ecology14
  • Microbial genetics14
  • Microbial physiology14
  • Microbial surveillance14
  • Microbiological surveillance14
  • Microbiology14
  • Microbiome14
  • Molecular community analysis14
  • Molecular infection biology14
  • Molecular microbiology14
  • Research data archiving14
  • Data management13
  • Metadata management13
  • Research data management (RDM)13
  • Amino acid sequence12
  • Amino acid sequences12
  • Biological modelling12
  • Biological system modelling12
  • Protein sequence12
  • Protein sequences12
  • Systems biology12
  • Systems modelling12
  • Literature search11
  • Structural assignment11
  • Structural biology11
  • Structural determination11
  • Structure determination11
  • Bibliography10
  • Citations10
  • Documentation10
  • Language10
  • Literature10
  • Literature and language10
  • Metabolic network modelling10
  • Metabolic network reconstruction10
  • Metabolic network simulation10
  • Metabolic pathway modelling10
  • Metabolic pathway reconstruction10
  • Metabolic pathway simulation10
  • Metabolic reconstruction10
  • Metagenomics10
  • Omics10
  • Protein functional analysis10
  • References10
  • Scientific literature10
  • Shotgun metagenomics10
  • Structure analysis10
  • DNA variation9
  • Show N_FILTERS more
• • Operation
  • Data handling1
  • File handling1
  • File processing1
  • Processing1
  • Report handling1
  • Utility operation1
  • Show N_FILTERS more
• • Tool
  • BioSamples1
  • Show N_FILTERS more
• • Event type
  • Workshops and courses469
  • Show N_FILTERS more
• • Venue
  • , 291
  • European Bioinformatics Institute, Hinxton14
  • EBI, Wellcome Genome Campus8
  • EMBL-EBI, Wellcome Genome Campus7
  • , Wellcome Genome Campus2
  • University of Cambridge, Downing Street2
  • Zoom2
  • Bhupat and Jyoti Mehta School of Biosciences, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras1
  • Center of Data and Knowledge Integration for Health - CIDACS, Instituto Gonçalo Moniz (IGM), technical-scientific unit (FIOCRUZ), R. Mundo 121, Ed. Tecnocentro, Trobogy1
  • EMBL-EBI, EMBL EBI1
  • EMBL-EBI, Wellcome genome campus1
  • European Bioinformatics Institute1
  • USP / FIOCRUZ Amazonas, Rua Terezina, 476 - Adrianópolis1
  • University of Costa Rica (UCR), Ciudad universitaria Rodrigo Facio Brenes1
  • Show N_FILTERS more
• • City
  • Zoom1
  • Show N_FILTERS more
• • Country
  • United Kingdom38
  • Brazil2
  • Costa Rica1
  • Global1
  • India1
  • Show N_FILTERS more
• • Target audience
  • Wet-lab researchers and bioinformaticians8
  • 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
  • Research presentation3
  • Plant research2
  • 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.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
  • 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
  • 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
  • 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. We encourage the audience to go through our introductory online course on human genetic variation prior to attending the workshop.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 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 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 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.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 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
  • 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 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 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 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 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 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 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
  • 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
  • This course is aimed at scientists working with bioimage data across the life sciences. It is suitable for those involved in creating bioimages or taking their first steps in analysis. The content would also be suitable for those wanting to learn more about the BioImage Archive and gain experience with machine learning approaches for image analysis. The programme will be of particular interest to bio-image analysts with questions relating to the use of ‘big data’ and using the wealth of publically available data curated in the BioImageArchive. The course should be accessible to members of the bioimaging community and does not require prior experience with machine learning methods or use of the BioImage Archive is necessary, but applicants are encouraged to explore the resources below before starting their application. Applicants should be comfortable with basic programming tasks and have experience working with Python. Prerequisite reading: Nature: BioImage Archive: A call for public archives for biological image data biorxiv: ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy Nucleic Acids Research: The BioStudies database—one stop shop for all data supporting a life sciences study Nature Methods: EMPIAR: a public archive for raw electron microscopy image data Nature: Image Data Resource: a bioimage data integration and publication platform BioModelZoo1
  • This course is aimed at scientists working with biomage data across the life sciences. It is suitable for those involved in creating bioimages or taking their first steps in analysis. The content would also be suitable for those wanting to learn more about the BioImage Archive and gain experience with machine learning approaches for image analysis. The programme will be of particular interest to bioimage analysts with questions relating to the use of ‘big data’ and using the wealth of publically available data curated in the BioImage Archive. The course should be accessible to members of the bioimaging community and does not require prior experience with machine learning methods or use of the BioImage Archive. Applicants are encouraged to explore the resources below before starting their application. Applicants should be comfortable with basic programming tasks and have experience working with Python. Prerequisite reading: BioImage Archive: A call for public archives for biological image data ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy The BioStudies database - one stop shop for all data supporting a life sciences study EMPIAR: a public archive for raw electron microscopy image data Image Data Resource: a bioimage data integration and publication platform BioImage Model Zoo  1
  • This course is aimed at those wishing to undertake analysis of microbial communities, with a particular emphasis on understanding the interactions and cross-talk of community members, especially using metabolomics.  Participants are expected to have a good understanding of microbiology, metagenomics and/or metabolomics. Familiarity with Unix is a requirement, as is general use of bioinformatics tools.   15 places are reserved for SymbNET members. Participants from SymbNET institutes will be entitled to free registration. For any enquiries, please contact [email protected]    1
  • This course is aimed at wet-lab researchers who are generating, planning on generating, or working with single cell RNA sequencing data. Prerequisites 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-introduction1
  • This course is aimed at wet-lab researchers within Latin America (excluding Chile and Uruguay due to funding restrictions) who are working with and/or generating their own crop genomic data or who are working on genotyping technologies, including data analysis software development.  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). 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. 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: 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: The course will use genomic data from crop plant species throughout the week. It will not explore in detail methods for assembling genomes.1
  • This course is aimed at wet-lab scientists generating structural data or scientists utilising structural data in their analysis and/or interpretation. No previous experience in the field of structural bioinformatics is required, however a basic knowledge of protein structure would be of benefit. Prerequisites  A working knowledge of the Linux operating system and ability to use the command line would be a benefit but is not mandatory. 1
  • This course is aimed at scientists generating structural data or scientists utilising structural data in their analysis and/or interpretation. No previous experience in the field of structural bioinformatics is required, however a basic knowledge of protein structure would be of benefit.1
  • This course is intended for graduate students, postdocs and young researchers working in the fields of metagenomics and viral discovery in the CABANA grand challenge areas of communicable diseases, protection of biodiversity, and/or sustainable crop production.  Applicants must be employed within Latin America only. Additional we cannot accept applications from Chile or Uruguay due to funding restrictions.   Prerequisites 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. Students should be familiar with using the Linux command line. As the course will be held remotely, all students must have Zoom previously installed on their computers. Also, as classes will be held synchronously, a good Internet connection is mandatory. A knowledge of virology, especially from previous research experience, is also desirable.   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.  1
  • This course is suitable for anyone interested in learning about running sequence alignment programs and detecting homologous sequences. It is also aimed at those wanting to learn about the EMBL-EBI Tools and how to access the services via user-friendly command-line clients.  For attending Session 1, no previous bioinformatics experience is required but familiarity with the EMBL-EBI resources and applications would be advantageous. An undergraduate-level knowledge of biology would also be recommended.  For attending Session 2, some familiarity with using the command-line, general bioinformatics and/or programming experience would be advantageous.  As part of the application process, applicants will need to provide their attendance preferences for attending Session 1, Session 2 or both.   1
  • This course is suitable for postgraduate (MSc-level and above) scientists within Latin America (excluding Chile and Uruguay) who are working with or generating genomic datasets related to SARS-CoV-2. Ideally, trainees will be working in the field of virology, and performing sequencing and/or analysing viral sequences, especially those within the coronaviridae family. We welcome applications from universities, research centres, hospitals, public health, and private laboratories. Scientists from underrepresented ethnic and gender groups are especially encouraged to apply for this workshop. 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. Attendance priority will be given to those who have not attended a CABANA event yet. Prerequisites Undergraduate-level knowledge of biology would be advantageous. You will also require access to a computer for the duration of the workshop. While most practicals are browser-based, a few will require a UNIX environment. Trainees will therefore require a basic knowledge of the Unix command line. 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 Training will be delivered via Zoom; trainees need to ensure they have working audio and microphones.1
  • This course is suitable for postgraduate (MSc-level and above) scientists within Latin America (excluding Chile and Uruguay) who are working with or generating genomic datasets related to communicable diseases. Ideally, trainees will be working in the field of virology. We welcome applications from universities, research centres, hospitals, public health, and private laboratories.   Prerequisites 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. 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.    1
  • This course is suitable for postgraduate students (MSc-level and above), postdoctoral-level researchers, newly established principal investigators and other research scientists within Latin America, who wish to use omics resources/analysis in their own research. We welcome applications from universities, research centres, hospitals, public health, and private laboratories. 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. Please note this course will be taught in English, however the trainers are fluent in either Portuguese or Spanish and can offer language support where feasible. Attendance priority will be given to those who have not attended a CABANA event yet. Prerequisites Working knowledge of genetics and/or molecular biology would be advantageous. You will also require access to a computer for the duration of the workshop. You do not need to know how to use UNIX / Linux operating systems and the command line, as the course covers the basics.  1
  • This course is suitable for postgraduate wet-lab researchers and also bioinformaticians at graduate-level upwards within Latin America who are working with and/or generating their own microbiome datasets. Ideally your research or application is related to CABANA's challenge areas of sustainable food production, protection of biodiversity, or communicable diseases.   This workshop is part-funded by the CABANA project and has a maximum capacity of 50 trainees, 25 of which are for trainees within Latin America (excluding Chile and Uruguay due to GCRF grant conditions). If you are not currently employed within Latin America, you can still register for this course via general admission, please visit the QIIME workshop website for more details. Early-stage researchers and researchers from underrepresented ethnic groups are especially encouraged to apply for this workshop. Please note this course will be taught in English.  1
  • This introductory course is aimed at biologists who are embarking on multiomics projects and computational biologists / bioinformaticians who wish to gain a better knowledge of the biological challenges presented when working with integrated datasets. 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-introduction For advanced-level training in using large-scale multiomics data and machine learning to infer biological models you may wish to consider our course on Systems Biology: From large datasets to biological insight.1
  • This introductory course is aimed at biologists who are embarking on multiomics projects and computational biologists/bioinformaticians who wish to gain a better knowledge of the biological challenges presented when working with integrated datasets. 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 is a highly interactive virtual workshop which will be delivered fully in Portuguese. Applications are open for researchers based in Latin America. Selection criteria: There are a number of criteria upon which selection of participants for this workshop will be made. Candidates should be able to demonstrate: They are at late-stage PhD level OR have equivalent years of research experience They are working in a Latin American institution and are likely to remain in the institution for the next year or more They are actively involved in a research project and actively using bioinformatics tools / methods They have a strong interest in training and have been involved in some training prior to joining the course They have identified a need / gap where training could be provided, and have thought about potential training they would like to deliver The ideal candidate will have 3+ years of research experience which includes a bioinformatics component, and a strong interest in developing or delivering bioinformatics training. You do NOT have to be a bioinformatician to apply. Early-stage researchers and researchers from underrepresented gender and ethnic groups are especially encouraged to apply. 1
  • This workshop is aimed at PhD students within the PhD programme "Genetics, Molecular and Cellular Biology" (University of Pavia) and the PhD programmme "Biomolecular Sciences and Biotechnology" (IUSS, University School for Advanced Studies Pavia. No knowledge of programming is required, but an undergraduate level knowledge of biology or molecular biology would be useful.1
  • This workshop is aimed at bioinformaticians, software engineers and data analysts working in genomic medicine. Participants are likely to be working to set up and operate compute infrastructure and analysis pipeline to support clinical decision making in genomic medicine. Participants will require a basic knowledge of computational script writing and command line tools. Knowledge of next generation sequencing technologies and familiarity with genomic data will be useful for comprehending the content.1
  • 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.  1
  • This workshop is for a cohort of early-stage researchers working on the EU-funded NEUcrest Innovative Training Network.1
  • This is a highly interactive virtual workshop which will be delivered simultaneously in Spanish. Applications are open for researchers based in Latin America. Selection criteria: There are a number of criteria upon which selection of participants for this workshop will be made. Candidates should be able to demonstrate: They are at late-stage PhD level OR have equivalent years of research experience They are working in a Latin American institution and are likely to remain in the institution for the next year or more They are actively involved in a research project and actively using bioinformatics tools / methods They have a strong interest in training and have been involved in some training prior to joining the course They have identified a need / gap where training could be provided, and have thought about potential training they would like to deliver The ideal candidate will have 3+ years of research experience which includes a bioinformatics component, and a strong interest in developing or delivering bioinformatics training. You do NOT have to be a bioinformatician to apply. Early-stage researchers and researchers from underrepresented ethnic groups are especially encouraged to apply.1
  • Who can participate: Students (B.Sc./B.Tech/M.Sc./M.Tech), Research Fellows, PhD Student, Faculty, Scientists, and Company Personals.  Prerequisites Participants must have access to the laptop/desktop with a stable internet connection. Basic knowledge of R or Python for full REST API course (only for last four day of workshop e.g. 27th - 30th July).1
  • beginner bioinformaticians1
  • intermediate bioinformaticians1
  • Show N_FILTERS more
• • Eligibility
  • First come first served2
  • Show N_FILTERS more
• • Language
  • English1
  • Show N_FILTERS more
• • Node
  • EMBL-EBI
  • Switzerland146
  • Germany141
  • Belgium120
  • United Kingdom108
  • Finland73
  • Sweden59
  • Norway35
  • Italy33
  • Estonia30
  • Portugal19
  • Netherlands18
  • Spain14
  • Czech Republic11
  • Slovenia11
  • Greece8
  • France7
  • Cyprus4
  • Denmark4
  • Israel2
  • Luxembourg2
  • Ireland1
  • Show N_FILTERS more
• • Collection
  • ELIXIR Biodiversity Community7
  • ELIXIR Systems Biology Community: training events and materials1
  • Single-cell Omics Community - collection of courses and materials1
  • Show N_FILTERS more
• • Instructor
  • Aleena Mushtaq27
  • Michal Szpak15
  • Benjamin Moore12
  • Emily Perry12
  • Nancy George10
  • Birgit Meldal9
  • Kalpana Panneerselvam9
  • Typhaine Paysan-Lafosse9
  • Anna Swan8
  • David Armstrong8
  • Dayane Rodrigues Araujo8
  • Louisse Paola Mirabueno8
  • Alexandra Holinski7
  • Baron Koylass7
  • Emily Bowler-Barnett7
  • Wendi Bacon7
  • Alexandre Bonvin6
  • Andrew Hercules6
  • Nandana Madhusoodanan6
  • Rahuman Sheriff6
  • Rossana Zaru6
  • Sam Holt6
  • Sarah Morgan6
  • Ugis Sarkans6
  • Eliot Ragueneau5
  • Gerard Kleywegt5
  • Osman Salih5
  • Paul Denny5
  • Pedro Raposo5
  • Thawfeek Varusai5
  • Tom Hancocks5
  • Ajay Mishra4
  • Alex Bateman4
  • Alexey Larionov4
  • Dona Shaju4
  • Fabio Madeira4
  • James Stephenson4
  • Johannes Griss4
  • Jonathan Manning4
  • Lee Larcombe4
  • Lorna Richardson4
  • Maira Ihsan4
  • Patricia Carvajal Lopez4
  • Piv Gopalasingam4
  • Sara Rocio Chuguransky4
  • Tobias Rausch4
  • Varsha Kale4
  • Yvonne Lussi4
  • Alexey Sokolov3
  • Attilio Vittorio Vargiu3
  • Aurelien Dugourd3
  • Chris Quince3
  • Deborah Harrus3
  • Garth Ilsley3
  • Giuliano Malloci3
  • Gun Antonia Nilsson Lock3
  • Helder Pedro3
  • Helena Cornu3
  • Irene Papatheodorou3
  • James Tolchard3
  • Janet Thornton3
  • Josephine Burgin3
  • Juan Caballero Perez3
  • Julia Foreman3
  • Kerstin Meyer3
  • Krishna Kumar Tiwari3
  • Kristina Kirschner3
  • Maria Levchenko3
  • Mariia Levchenko3
  • Martin Beracochea3
  • Matthew Hartley3
  • Michael Sternberg3
  • Pablo Moreno3
  • Pablo Rodriguez Mier3
  • Piraveen Gopalasingam3
  • Sandra Orchard3
  • Sebastien Raguideau3
  • Silvie Fexova3
  • Summer Rosonovski3
  • Tamir Chandra3
  • Tatiana Gurbich3
  • Tomas Helikar3
  • Zhichao Miao3
  • Adam Hospital2
  • Alan Tracey2
  • Alessandra Villa2
  • Alexandre Almeida2
  • Alvis Brazma2
  • Andreas Dräger2
  • Andrew Green2
  • Andrew Stubbs2
  • Andrii Iudin2
  • Anja Fullgrabe2
  • Anna Gaulton2
  • Anna Kreshuk2
  • Arnau Montagud2
  • Awais Athar2
  • Aybuke Kupcu Yoldas2
  • Barbara Diaz-Rohrer2
  • Ben Allen2
  • Show N_FILTERS more
• Show all events
• Show events from all spaces
• Hide past events
• Show disabled events
• Show events with broken links