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Workshops and courses
Machine learning and deep learning fundamentals
1 - 2 April 2026
Zwijnaarde, Belgium
Face-to-face
Artificial Inteligence programming software -
Workshops and courses
Spring School - Interpretable Machine Learning Models in Biomedicine
2 - 6 March 2026
Altheim, Germany
Face-to-face
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Workshops and courses
Introduction to Machine Learning with R
12 - 13 November 2026
Basel, Switzerland
Face-to-face
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Workshops and courses
Introduction to Machine Learning with Python
1 - 22 June 2026
Online
data mining machine learning training torsten schwede & thierry sengstag group mark ibberson group -
Workshops and courses
Introduction to Machine Learning with Python
1 - 2 October 2026
Bern, Switzerland
Face-to-face
data mining machine learning training torsten schwede & thierry sengstag group mark ibberson group -
Workshops and courses
Statistics and Machine Learning for Life Sciences
31 March - 1 April 2026
Online
training biostatistics data mining machine learning torsten schwede & thierry sengstag group -
Workshops and courses
Microscopy data analysis: machine learning and the BioImage Archive
16 - 20 March 2026
Online
Machine learning Bioimaging Image analysis Bioimage analysis Machine learning models Scientific computing Light microscopy Electron microscopy -
Workshops and courses
Ensuring More Accurate, Generalisable, and Interpretable Machine Learning Models for Bioinformatics
17 November 2026 @ 09:00 - 17:00
Online
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Workshops and courses
Data science for life scientists
15 - 19 June 2026
United Kingdom
Face-to-face
Data science Python Data visualisation Statistics Machine learning -
Workshops and courses
Data-driven approaches to understanding dementia
13 - 17 April 2026
United Kingdom
Face-to-face
Neurobiology Systems biology Machine learning Bioimaging -
Workshops and courses
Systems biology: from large datasets to biological insight
11 - 15 May 2026
United Kingdom
Face-to-face
Systems biology Network analysis Machine learning Deep learning Network inference Logic modelling Multi-Omics Factor Analysis Data integration -
Workshops and courses
9th Advanced in silico Drug Design workshop 2026
26 - 30 January 2026
Olomouc, Czech Republic
Face-to-face
Drug discovery Drug development Structure analysis Data acquisition Molecular modelling Computational biology Computational chemistry Cheminformatics Structure prediction Pharmacology Molecular docking Molecular surface analysis Structure database search Chemical similarity enrichment Binding site prediction Residue contact prediction Residue interaction calculation Trajectory visualization Optimisation and refinement Protein property calculation Protein structure prediction Simulation analysis Feature selection Feature extraction Hydrogen bond calculation Ligand-binding site prediction Molecular dynamics in silico drug design Drug design Drug screening Pharmacophores Chemical biology QSAR molecular modelling De novo modeling Deep Learning AlphaFold AlphaFold Database AI structure prediction AI based tools AlphaFold Database (13181) Quantum mechanics/molecular mechanics -
Workshops and courses
9th Advanced in silico Drug Design workshop 2026
26 - 30 January 2026
Online
Drug discovery Drug development Structure analysis Data acquisition Molecular modelling Computational biology Computational chemistry Cheminformatics Structure prediction Pharmacology Molecular docking Molecular surface analysis Structure database search Chemical similarity enrichment Binding site prediction Residue contact prediction Residue interaction calculation Trajectory visualization Optimisation and refinement Protein property calculation Protein structure prediction Simulation analysis Feature selection Feature extraction Hydrogen bond calculation Ligand-binding site prediction Molecular dynamics in silico drug design Drug design Drug screening Pharmacophores Chemical biology QSAR molecular modelling De novo modeling Deep Learning AlphaFold AlphaFold Database AI structure prediction AI based tools AlphaFold Database (13181) Quantum mechanics/molecular mechanics
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aml4td/website
Machine learning R
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jmacdon/Bioc2020Anno
Genome annotation R
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jmacdon/Bioc2022Anno
Genome annotation R
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Perl 1 Training Course - For Programming Beginners
Perl Programming
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GGPLOT2 : Pragmatic GGPLOT
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Video, Webinar
ELIXIR CZ Friday Coffee #5: Data Management with Data Stewardship Wizard
Data management data management plan data stewardship FAIR data management software tools
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Presentation
DSW Workshop for Finnish Data Support Personnel
•• intermediateData management DMP DMP tools data stewardship FAIR FAIR data -
WEBINAR: Baby steps in the AI-guided design of proteins to modulate gene transcription
Bioinformatics Structural biology Protein design AI Deep learning
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exercise, slides, tutorial
Machine Learning
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slides
Introduction to Machine learning
• beginnerStatistics and probability Statistics and machine learning -
e-learning
Basics of machine learning
• beginnerStatistics and probability Statistics and machine learning -
e-learning
Classification in Machine Learning
• beginnerStatistics and probability Statistics and machine learning -
e-learning
Regression in Machine Learning
• beginnerStatistics and probability Statistics and machine learning -
e-learning
Clustering in Machine Learning
• beginnerStatistics and probability Statistics and machine learning -
cambiotraining/intro-machine-learning
Machine learning
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Training materials
Machine Learning & BioStatistics Hackathon 2020
• beginnerMachine learning Statistics and probability Computer science machine learning biostatistics eLearning EeLP -
Video
Introduction to Machine Learning Algorithms
•• intermediateMachine learning -
slides
Foundational Aspects of Machine Learning
• beginnerStatistics and probability Statistics and machine learning ai-ml elixir -
e-learning
Machine learning: classification and regression
• beginnerStatistics and probability Statistics and machine learning -
e-learning
Age prediction using machine learning
• beginnerStatistics and probability Statistics and machine learning -
hands-on tutorial
A tour of Machine Learning
•• intermediateMachine learning Classification Deep Learning Machine Learning -
JuliaAcademy/Foundations-of-Machine-Learning
Machine learning Julia
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sdgroeve/Machine-Learning-Course-2days
Machine learning
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tutorial
Introduction to Machine Learning — CfRR
CfRR Introduction to Machine Learning programming reproducible research scientific computing
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Bioinformatics, Computational Biology, Computer Science, Programming, Coding, Education, Data Science, Transcriptomics, Machine Learning
R for Data Science: November 2024
•• intermediateBioinformatics Computational biology Machine learning Transcriptomics Computational Biology Coding Programming Data Science Data Analysis Computer Science … -
e-learning
PDBePISA: Identifying and interpreting the likely biological assemblies of a protein structure
Structure prediction Protein structure analysis Quaternary structure Macromolecular interfaces PDBe Macromolecular structures
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Introduction to Machine Learning with Python
• beginnerdata mining,machine learning,training,mark ibberson group,torsten schwede & thierry sengstag group data mining,machine learning,training,torsten schwede & thierry sengstag group,mark ibberson group -
e-learning
Introduction to Machine Learning using R
•• intermediateStatistics and probability Statistics and machine learning interactive-tools -
e-learning
Machine Learning Modeling of Anticancer Peptides
•• intermediateProteomics ML cancer -
carpentries-incubator/machine-learning-novice-sklearn
Machine learning Statistics and probability Statistics
Showing 4 content providers
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proteomicsML
ProteomicsML provides ready-made datasets for machine learning models accompanied by tutorials on how to work with even the most complex data types in the field of proteomics. The resource is set up to evolve together with the field, and we welcome everyone to contribute to the project by adding...
1 training materialproteomicsML https://proteomicsml.org/ https://tess.elixir-europe.org/content_providers/proteomicsml ProteomicsML provides ready-made datasets for machine learning models accompanied by tutorials on how to work with even the most complex data types in the field of proteomics. The resource is set up to evolve together with the field, and we welcome everyone to contribute to the project by adding new datasets and accompanying notebooks. ProteomicsML was set up as a joint effort of SDU, CompOmics, LUMC, PeptideAtlas, NIST, PRIDE, and MSAID. We believe that ProteomicsML is solid step forward for the field towards more open and reproducible science! /system/content_providers/images/000/000/676/original/proteomicsml-logo.png?1686658675 -
Pattern Institute
Mission | The Pattern Institute is a nonprofit research organization dedicated to advancing scientific discovery, education, and outreach, with a particular emphasis on systems and complexity science. It applies mathematical and computational approaches to uncover patterns across the...
3 training materialsPattern Institute https://www.pattern.institute/training/ https://tess.elixir-europe.org/content_providers/pattern-institute **Mission** | The **Pattern Institute** is a nonprofit research organization dedicated to advancing scientific discovery, education, and outreach, with a particular emphasis on systems and complexity science. It applies mathematical and computational approaches to uncover patterns across the natural, formal, and social sciences. /system/content_providers/images/000/000/822/original/pi-logotype2.svg?1753360127 -
EOSC4Cancer
EOSC4Cancer will make diverse types of cancer data accessible: genomics, imaging, medical, clinical, environmental and socio-economic. It will use and enhance federated and interoperable systems for securely identifying, sharing, processing and reusing FAIR data across borders and offer them via...
1 training material0 events (1 past event)EOSC4Cancer https://eosc4cancer.eu/ https://tess.elixir-europe.org/content_providers/eosc4cancer EOSC4Cancer will make diverse types of cancer data accessible: genomics, imaging, medical, clinical, environmental and socio-economic. It will use and enhance federated and interoperable systems for securely identifying, sharing, processing and reusing FAIR data across borders and offer them via community-driven analysis environments. EOSC4Cancer’s well curated data sets will be essential input for reproducible and robust analytics and computational methods – including machine learning and artificial intelligence. EOSC4Cancer’s five use cases will cover the patient journey from cancer prevention over diagnosis to treatment, laying the foundation of data trajectories and workflows for future European Cancer Mission projects. /system/content_providers/images/000/000/747/original/Logo-eosc-cancer-RGB-horizontal-STANDARD.png?1711439233 -
Jalview
Jalview (www.jalview.org) is free-to-use sequence alignment and analysis visualisation software that links genomic variants, protein alignments and 3D structure.
Protein, RNA and DNA data can be directly accessed from public databases (e.g. Pfam, Rfam, PDB, UniProt and ENA etc.). Jalview has...
0 events (2 past events)Jalview http://www.jalview.org/ https://tess.elixir-europe.org/content_providers/jalview Jalview (www.jalview.org) is free-to-use sequence alignment and analysis visualisation software that links genomic variants, protein alignments and 3D structure. Protein, RNA and DNA data can be directly accessed from public databases (e.g. Pfam, Rfam, PDB, UniProt and ENA etc.). Jalview has editing and annotation functionality within a fully integrated, multiple window interface. The sequence alignment programs Clustal Omega, Muscle, MAFFT, ProbCons, T-COFFEE, ClustalW, MSA Prob and GLProb can be run directly from within Jalview. Jalview integrates protein secondary structure prediction (JPred), generate trees, assesses consensus and conservation across sequence families. Journal quality figures can be generated from the results. The Jalview Desktop will run on Mac, MS Windows, Linux and any other platform that supports Java. It has been developed in Geoff Barton's group (www.compbio.dundee.ac.uk) in the School of Life Sciences (www.lifesci.dundee.ac.uk) at the University of Dundee with funding from the BBSRC and the Wellcome Trust. /system/content_providers/images/000/000/091/original/logo-boxg.png?1524735946