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Keyword
- Bioinformatics9
- ABR5
- bioinformatics5
- Computational Biology4
- VLSCI4
- Artificial Intelligence3
- Cloud computing3
- Computational simulations3
- ComputationalBiology3
- Data protection3
- H3Africa genotyping array3
- HPC3
- Nextflow3
- Population Genomics3
- Workflows3
- AI based tools2
- AI structure prediction2
- African populations2
- AlphaFold2
- AlphaFold Database2
- AlphaFold Database (13181)2
- Cancer therapy response2
- Chemical biology2
- Cheminformatics2
- De novo modeling2
- Deep Learning2
- Drug design2
- Drug discovery2
- Drug screening2
- European Genome-phenome Archive2
- GPU2
- GWAS workflow2
- Genome Wide Association Studies2
- Genotype calling2
- H3ABioNet2
- H3ABioNet GWAS 2018 Lecture Series2
- Human ecosystems2
- Imaging2
- Molecular docking2
- NHGRI-EBI GWAS Catalog2
- Pharmacophores2
- QSAR2
- Quantum mechanics/molecular mechanics2
- Signalling prior knowledge2
- Virtual humans2
- environmental readouts2
- ethics2
- genes and environment interactions2
- human phenotypes2
- in silico drug design2
- lifescience2
- machine learning2
- molecular modelling2
- R programming1
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- Statistics1
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- Agent-based modelling1
- Annotations1
- Array processing1
- Big Data1
- BioCloud1
- Biological databases1
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- Boolean1
- Boolean modelling1
- Building blocks1
- COBREXA1
- Carbon footprint1
- Cell signaling1
- CellNOpt1
- Clinical Bioinformatics1
- Competency framework1
- Computational biology1
- Computer Programming1
- Constraint-based metabolic modelling1
- Containers1
- Convert to PLINK format 1
- Data analysis1
- Demonstration1
- Discordant Sex information1
- Docker1
- Drug-target identification1
- EeLP1
- Environmental impact1
- Evolutinary genomics1
- File formats1
- GWAS1
- Galaxy Australia1
- Genome Studio1
- Genomics1
- Genotype array probes1
- Genotyping1
- Genotyping array analysis 1
- Genotyping rate call1
- Green Algorithms1
- HPC workflows1
- Hackathon1
- Hardy Weinberg Equilibrium1
- Heterozygosity rate1
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Scientific topic
- Biomathematics
- Bioinformatics741
- Genome annotation321
- Exomes312
- Genomes312
- Genomics312
- Personal genomics312
- Synthetic genomics312
- Viral genomics312
- Whole genomes312
- Biological modelling217
- Biological system modelling217
- Systems biology217
- Systems modelling217
- Biomedical research185
- Clinical medicine185
- Experimental medicine185
- General medicine185
- Internal medicine185
- Medicine185
- Data management157
- Metadata management157
- Research data management (RDM)157
- Bottom-up proteomics152
- Discovery proteomics152
- MS-based targeted proteomics152
- MS-based untargeted proteomics152
- Metaproteomics152
- Peptide identification152
- Protein and peptide identification152
- Proteomics152
- Quantitative proteomics152
- Targeted proteomics152
- Top-down proteomics152
- Cloud computing62
- Computer science62
- HPC62
- High performance computing62
- High-performance computing62
- Exometabolomics58
- LC-MS-based metabolomics58
- MS-based metabolomics58
- MS-based targeted metabolomics58
- MS-based untargeted metabolomics58
- Mass spectrometry-based metabolomics58
- Metabolites58
- Metabolome58
- Metabolomics58
- Metabonomics58
- NMR-based metabolomics58
- Immunology56
- Computational pharmacology54
- Pharmacoinformatics54
- Pharmacology54
- Comparative transcriptomics51
- Data archival51
- Data archiving51
- Data curation51
- Data curation and archival51
- Data preservation51
- Database curation51
- Research data archiving51
- Transcriptome51
- Transcriptomics51
- Computational biology50
- FAIR data50
- Findable, accessible, interoperable, reusable data50
- Mathematical biology50
- Theoretical biology50
- Pipelines46
- Software integration46
- Tool integration46
- Tool interoperability46
- Workflows46
- Active learning45
- Ensembl learning45
- Kernel methods45
- Knowledge representation45
- Machine learning45
- Neural networks45
- Recommender system45
- Reinforcement learning45
- Supervised learning45
- Unsupervised learning45
- RNA-Seq analysis43
- Data visualisation39
- Metagenomics34
- MicroRNA sequencing34
- RNA sequencing34
- RNA-Seq34
- Shotgun metagenomics34
- Small RNA sequencing34
- Small RNA-Seq34
- Small-Seq34
- Transcriptome profiling34
- WTSS34
- Whole transcriptome shotgun sequencing34
- miRNA-seq34
- Data rendering32
- High-throughput sequencing31
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Operation
- Attribute selection2
- Binding site prediction2
- CG analysis2
- Chemical class enrichment2
- Chemical similarity enrichment2
- Contact map prediction2
- Docking simulation2
- Feature extraction2
- Feature projection2
- Feature selection2
- Hydrogen bond calculation2
- Ligand-binding site detection2
- Ligand-binding site prediction2
- MD analysis2
- Macromolecular docking2
- Molecular docking2
- Molecular dynamics2
- Molecular dynamics simulation2
- Molecular surface analysis2
- Nucleic Acid Dynamics Analysis2
- Optimisation and refinement2
- Peptide-protein binding prediction2
- Protein Dynamics Analysis2
- Protein binding site detection2
- Protein binding site prediction2
- Protein contact map prediction2
- Protein dynamics2
- Protein flexibility and motion analysis2
- Protein flexibility prediction2
- Protein folding pathway prediction2
- Protein motion prediction2
- Protein property calculation2
- Protein property calculation (from sequence)2
- Protein property calculation (from structure)2
- Protein property rendering2
- Protein structural property calculation2
- Protein structure prediction2
- Residue contact prediction2
- Residue interaction calculation2
- Residue interaction prediction2
- Simulation analysis2
- Structural property calculation2
- Structure analysis2
- Structure database search2
- Trajectory analysis2
- Trajectory visualization2
- Variable selection2
- Variable subset selection2
- Protein design1
- Protein redesign1
- Rational protein design1
- de novo protein design1
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Tool
- AlphaFold 23
- AlphaCharges2
- AlphaFill2
- AlphaFind2
- AutoDock Vina2
- PyMOL2
- SPCI2
- TmAlphaFold database2
- CAVER1
- CAVER Web1
- CalFitter1
- CaverDock1
- EnzymeMiner1
- FireProt1
- FireProt 2.01
- FireProt ASR1
- FireProtDB1
- HotSpot Wizard1
- LoopGrafter1
- SoluProt1
- SoluProtMutsupDB1
- Tamarind1
- pyCaverDock1
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Venue
- , 16
- European Bioinformatics Institute, Hinxton4
- Lab-14, VLSCI3
- Faculty of Science, Palacky University Olomouc, 17. listopadu 1192/122
- Crowne Plaza Hunter Valley1
- Dipartimento di Scienze Biochimiche - Alessandro Rossi Fanelli, 332, Viale Regina Elena1
- EMBL-EBI South Building and ELIXIR Hub1
- Escuela Técnica Superior de Ingeniería Informática, 35, Bulevar Louis Pasteur1
- Hotel Montanyà, Avda. Montseny, s/n1
- Kamenice 5 625 00 Brno-Bohunice Česko1
- La Pedrera, 92, Passeig de Gràcia1
- Lab-14 Seminar Space, VLSCI1
- Meyerhofstraße 11
- Online1
- Pasteur Hellenic Institute, 127 Vasilissis Sofias1
- Provinciehuis, Provincieplein 1, Leuven1
- Sapienza University of Rome1
- UAntwerp - Campus Middelheim 1 Middelheimlaan 2020 Antwerpen Belgium Downing Site Downing Street Cambridge CB2 3EA United Kingdom1
- University of Liverpool1
- University of Melbourne1
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Target audience
- Life Science Researchers4
- Anyone intersted in GWAS and using the H3Africa genotyping chip3
- Master students3
- PhD Students3
- Researchers3
- Bioinformaticians2
- Biologists2
- Computational biologists2
- Post Docs2
- Academia1
- Academics1
- Anyone who wants to learn more about GWAS1
- Bioinformatician1
- Bioinformatics beginners 1
- Biostatisticians1
- Clinical Scientists1
- Computer science1
- Data Scientists1
- Doctoral students1
- ELIXIR members1
- Early Career Researcher1
- 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
- Industry1
- Industry professionals, and people with a keen interest in the subject.1
- PhD candidates1
- PhD students1
- Postdoctoral Researchers1
- Postdoctoral students1
- 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
- Undergraduate students1
- bioinformaticians1
- life scientists1
- postdocs1
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Language
- English5
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Instructor
- Arnau Montagud2
- Marco Ruscone2
- Åsmund Flobak2
- Adam Smelko1
- Alex Bateman1
- Anna Niarakis1
- Anshika Chowdhary1
- Cath Brooksbank1
- Danielle Welter1
- Davide Cirillo1
- Dénes Türei1
- Henrik Nortamo1
- Javier Conejero1
- Jesse Harrison1
- Joaquín Dopazo1
- Jun Wang1
- Laurence Calzone1
- Lee Larcombe1
- Loïc Lannelongue1
- Malvina Marku1
- Marco Fariñas1
- Mariano Vázquez1
- Marta Teperek1
- Miguel Ponce de León1
- Pablo Rodríguez Mier1
- Paul Macklin1
- Sarah Morgan1
- St. Elmo Wilken1
- Thalia Diniaco1
- Thomas Keane1
- Vera Pancaldi1
- Vincent Noël1
- Viviam Bermúdez1
- Will Rayner1
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