- Home
- Materials
Filters
Sort
-
-
Filter Clear filters
-
-
Scientific topic
- Data management1
- Metadata management1
- Show N_FILTERS more
-
-
-
Content provider
- BioData.pt1
- Show N_FILTERS more
-
-
-
Keyword
- FAIR Research
- FAIR6
- Computational modelling4
- ComputationalBiology4
- Data managment plan4
- Kinetic modeling4
- SystemsBiology4
- data management4
- COPASI3
- Data Life Cycle3
- EeLP3
- eLearning3
- Bioinformatics2
- Biological networks2
- Biomodelling2
- Data Steward2
- Data download2
- Data management2
- Data querying2
- Genomics2
- Introduction bioinformatics2
- Model2
- RDM2
- linked data2
- metadata2
- research data management2
- Annotation1
- R-programming1
- Visualisation1
- data science1
- Advanced bioinformatics training1
- ArrayExpress1
- Artificial Intelligence1
- Bioinformatics for schools, basic bioinformatics, SARS-CoV-2 pandemic, genome analysis, protein sequence analysis, protein structure analysis, virus variants, spike protein, training material1
- Biomedical data1
- COMBINE1
- CONVERGE1
- ChIPSeq1
- Clinical bioinformatics1
- Containers1
- DMP1
- Data Management Plan1
- Data Stewardship Wizard1
- Data analysis1
- Data management plan1
- Data management planning1
- De novo genome assembly1
- ELIXIR-CONVERGE1
- FAIRplus1
- Findability of data and code1
- Genome browsing1
- HPC1
- High throughput sequencing analysis1
- Identifying data and code1
- Machine learning1
- Mathematical modelling1
- Modeling1
- Multiple sequence alignment1
- NGS1
- Network Visualization1
- Network analysis1
- Open data1
- Open science1
- Pathway analysis1
- Pathways1
- Plants bioinformatics1
- Protein sequence analysis1
- Protein structure1
- Protein structure visualisation1
- Python1
- Python Programming1
- RNASeq1
- Rare Diseases1
- Rare Diseases & Research1
- Referencing data and code1
- Research Data Management1
- Research Infrastructure1
- Rna seq chip seq anayses1
- SED-ML1
- Sequence analysis1
- Signalling1
- Training (Training)1
- Unix1
- Variant calling1
- Wikidata1
- Workflows1
- biostatistics1
- boolean modelling1
- cancer1
- data FAIRness1
- data management plan1
- data sharing1
- data visualization1
- genomics1
- high-performance computing1
- life-sciences1
- logical modelling1
- machine learning1
- modeling1
- ontologies1
- Show N_FILTERS more
-
-
-
Difficulty level
- Not specified1
- Show N_FILTERS more
-
-
-
Target audience
- Life Science Researchers
- PhD Scholars, Graduates and Post Graduates, Professors, Associate Professors, Assistant Professors, Bio instruments Professionals, Bio-informatics Professionals, Directors, CEO’s of Organizations, Supply Chain companies, Manufacturing Companies, Software development companies, Research Institutes and members1
- PhD Students1
- PhD Students or young researchers in molecular biology and/or genetics with little or no background in bioinformatics.1
- Post Docs1
- Research scientists1
- Researchers1
- 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.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.1
- Show N_FILTERS more
-
-
-
Resource type
- Course materials1
- Training materials1
- Show N_FILTERS more
-
-
-
Status
- Active1
- Show N_FILTERS more
-
- Show archived materials
