Contact information
Research groups
Recent publications
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SIMON: Open-Source Knowledge Discovery Platform
Journal article
Tomic A. et al, (2021), Patterns, 2, 100178 - 100178
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The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system.
Journal article
Tomic A. et al, (2019), Sci Data, 6
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SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses.
Journal article
Tomic A. et al, (2019), J Immunol, 203, 749 - 759
Ivan Tomić
Senior Software Engineer Team Lead
I am leading development of SIMON -- open source machine learning platform.
SIMON is a powerful, flexible, open-source and easy to use Data Science Knowledge Discovery software. Currently SIMON implements Machine Learning and many other statistical data discovery features (Hierarchical clustering, Correlation, PCA Analysis, UMAP, t-SNE and others) that will help you to illustrate dynamic relationships and provide you with a structural sense of your data.
SIMON exist to make user interface that will empower scientists to extract meaningful information from their data and enable them to rapidly use and quickly prototype with different machine learning algorithm.
SIMON is great software for biomarker discovery and validation, drug discovery, precision medicine. You can use it to build robust reproducible AI models and in AI Drug Design.
It is open source! It is community driven! It is used all over the globe with more than 3000 installs!
Current version features
- 200+ machine learning algorithms to choose from
- nicely designed drag&drop user interface to easily apply data modeling techniques
- supports high sparsity data via data imputation or mulset
- supports local and cloud backend data storage
- compare all model performance measures in one place
- visual data analysis that supports clustering and correlation graphs
- visual feature analysis with dot-plots that supports 280 visual styles
- visual model performance comparison and model insights
- in-build data preprocessing (correlation filtering, normalization, imputation...)
- public dataset repository import to easily import and analyze already published data* (in progress)
- integrated SAM (Significance Analysis of Microarrays) technique for finding significant genes in a set of microarray experiments
- multi-language localization support
- model & data export take your ML models and other performed analysis, reproducibility code and associated data with you on the go* (in progress)