Unique Blend of Expertise

EdgeLeap blends different expertises to provide powerful data science solutions:

Analytics

We excel in finding and applying the right machine learning methods, graph algorithms and visual analytics to get the most out of your data.

Domain knowledge

Our team has years of experience in generating and analyzing life sciences data. We speak your language.

Technology

We use solid development technology to ensure modular and scalable solutions, seamless integration with your current infrastructure, and smooth user interfaces.

Toolbox for Craft Solutions

A single tool doesn’t fit all. EdgeLeap has unique expertise in finding, combining, and customizing the right tools and methods for your specific application.

We use R as allround platform for data science tasks

We model life sciences data as graphs using Neo4j

We use Python as allround platform for data science tasks

We use git to work together on code

We visualize biological pathways with PathVisio

Cytoscape for powerful interactive network visualization

Bioconductor serves as our allround bioinformatics toolbox

We build smooth end user tools using ReactJS

We build robust data processing pipelines with Java

We perform advanced graph analysis with igraph

We Dockerize our analysis pipelines and products for optimal reproducibility and hassle-free deployment

We mine unstructured information using the UIMA framework

Still favorite in large enterprises – we embed enterprise solutions in a flexible data science environment

BridgeDB for linking molecules across databases

We use Electron for flexible deployment of our tools, in the cloud or on your local PC

We build scalable NLP pipelines using spaCy

Our toolbox is continuously growing – we find the right tools for your specific application!

Navigating the Data Landscape

Game changing insights come from linking different data and information. We empower our clients in navigating the full data landscape:

Your data

Analyze and integrate data generated within your organization.

Public data

Reinforce your data with the wealth of publicly available datasets.

Structured knowledge

Mine existing knowledge to give context to your findings.

Unstructured information

Mine unstructured data to derive transitive relations and discover new leads.

Scientific Track Record & Publicity

Talks

EdgeLeap @ invited talks and lectures.

  • M. Radonjic. Steering R&D innovation: From information to intelligence. Personalised Food: Tech & Data outlook, Klarenbeek (The Netherlands), 12 October 2017.
  • M. Radonjic. EdgeFlow: Streamlining R&D innovation strategy. Big Data Symposium, DSM Delft (The Netherlands), 3 October 2017.
  • M. Radonjic. From idea to business: Craft solutions in data science. BioSB 2017, Bioinformatics Industrial User Platform session, Lunteren (The Netherlands), 5 April 2017.
  • M. Radonjic. Data science SMEs in Life Science & Health ecosystem. Health~Holland Plaza meeting, The Hague (The Netherlands), 3 April 2017.
  • M. Radonjic. Data-driven biomarker research. Twelfth Annual Meeting: Transatlantic Heart Failure Biomarker Working Group, Cannes (France), 2 April 2017.
  • M. Radonjic. Empowering decision making through data science. VUMC Biobusiness course, Amsterdam (The Netherlands), 26 January 2017.
  • M. Radonjic. From data to insights: Network science applications. FIGHT-HF annual meeting, Nancy (France), 18 January 2017.
  • M. Radonjic. Data science in action: applications to real-world data. Utrecht Bioinformatics Center seminar, Utrecht (The Netherlands), 11 November 2016.
  • M. Radonjic. From big data to greater decisions: a user guide. With healthy foods to the market, Summer event AgriFood Capital & Grow Campus Den Bosch (The Netherlands), 7 July 2016.
  • M. Radonjic. Data landscape of The Netherlands. Agri & Food Top 2016, Wageningen (The Netherlands), 1 June 2016.
  • M. Radonjic. Unravelling complexity of cardiac health. Transatlantic Heart Failure Biomarker Working Group, Cannes (France), 23-24 April 2016.
  • M. Radonjic. From data to decisions: challenges and opportunities for food & nutrition industry. VMT Food Event 2016, Den Bosch (The Netherlands), 12 April 2016
  • M. Radonjic. From Disconnected Data to Emerging Insights: Unravelling Complexity of Food-Health Interactions. Keystone Symposium “Human Nutrition, Environment and Health”, Beijing (China), 14-18 October 2015.
  • T. Kelder. Visualizing personalized food-health interactions. BioJS Conference, Norwich (UK), 3 July 2015.
  • M. Radonjic. From big data to big picture: Interplay between diet, microbiome and cardiovascular health. BIOVISION, Lyon (France), 15-16 April 2015.
  • M. Radonjic. Data Science For Healthcare. Innovation for Health, Amsterdam (The Netherlands), 5 February 2015.
  • M. Radonjic. Network analysis for personalized health and disease. O2 for Personalized Medicine and Nutrition, Amsterdam (The Netherlands), 30 January 2015.
  • T. Kelder, G. Summer, M. Radonjic. Tackling Personalized Health Through Data Integration. SB@NL2014 Systems Biology Symposium, Maastricht (The Netherlands), 15 December 2014.
  • T. Kelder. Using graphs to decipher complexity of health and disease. Graph Database Meetup, Amsterdam (The Netherlands), 5 November 2014.
  • M. Radonjic. Embracing systems complexity to empower personalized health: data science in action. MaCSBio Seminar Systems Biology, Maastricht (The Netherlands), 26 September 2014.
  • M. Radonjic. Organizing data to empower decision making. NuGO week 2014 – Nutrigenomics of Foods, Castellammare di Stabia (Italy), 8 to 11 September 2014.
  • M. Radonjic. Network science: Enabling P4 medicine. AIMMS Post-graduate course “From systems biology to personalized medicine”, VU University Amsterdam (The Netherlands), 30-31 January 2014.

Publications

All publications by Thomas Kelder, Marijana Radonjic.

  • T. Kelder & M. Radonjic, interview by N. Beintema, EdgeLeap: Culture shift in data science. C2W – Platform for professionals in chemistry and life sciences (2017).
  • F. Pinet, M. Cuvelliez, T. Kelder, P. Amouyel, M. Radonjic, C. Bauters. Integrative network analysis reveals time-dependent molecular events underlying left ventricular remodeling in post-myocardial infarction patients. Biochimica et Biophysica Acta (BBA) – Molecular Basis of Disease (2017).
  • J. Kaput, G. Perozzi, M. Radonjic, F. Virgili. Propelling the paradigm shift from reductionism to systems nutrition. Genes & Nutrition (2017).
  • G. Summer, T. Kelder, M. Radonjic, M. van Bilsen, S. Wopereis, S. Heymans. The Network Library: a framework to rapidly integrate network biology resources. Bioinformatics (2016).
  • J. Kaput, M. Kussmann, M. Radonjic, F. Virgili, G. Perozzi. Human nutrition, environment, and health. Genes & nutrition (2015).
  • G. Summer, T. Kelder, K. Ono, M. Radonjic, S. Heymans, B. Demchak. cyNeo4j: connecting Neo4j and Cytoscape. Bioinformatics (2015).
  • L.M.T. Eijssen, V.S. Goelela, T. Kelder, M.E. Adriaens, C.T. Evelo, M. Radonjic A user-friendly workflow for analysis of Illumina gene expression bead array data available at the arrayanalysis.org portal. BMC Genomics (2015).
  • D. Derous, T. Kelder, E.M. van Schothorst, M. van Erk, A. Voigt, S. Klaus, J. Keijer, M. Radonjic. Network-based integration of molecular and physiological data elucidates regulatory mechanisms underlying adaptation to high-fat diet. Genes & Nutrition (2015).
  • A. Wagner, N. Cohen, T. Kelder, E. Liebman, D. Steinberg, M. Radonjic, E. Ruppin. Drugs that reverse disease transcriptomics are more effective in a mouse model of dyslipidemia. Molecular Systems Biology (2015).
  • T. Kelder, G. Summer, M. Caspers, E.M. van Schothorst, J. Keijer, L. Duivenvoorde, …, M. Radonjic. White adipose tissue reference network: a knowledge resource for exploring health-relevant relations. Genes & Nutrition (2015).
  • M. Kutmon, M.P. van Iersel, A. Bohler, T. Kelder, N. Nunes, A.R. Pico, C.T. Evelo. PathVisio 3: An Extendable Pathway Analysis Toolbox. PLoS Computational Biology (2015).
  • T. Kelder, L. Verschuren, B. van Ommen, A.J. van Gool, M. Radonjic. Network signatures link hepatic effects of anti-diabetic interventions with systemic disease parameters. BMC systems biology (2014).
  • T. Kelder, J.H.M. Stroeve, S. Bijlsma, M. Radonjic, G. Roeselers. Correlation network analysis reveals relationships between diet-induced changes in human gut microbiota and metabolic health. Diabetes and Nutrition (2014).
  • L. Verschuren, P.Y. Wielinga, T. Kelder, M. Radonjic, et al. A systems biology approach to understand the pathophysiological mechanisms of cardiac pathological hypertrophy associated with rosiglitazone. BMC medical genomics (2014).
  • M. Kutmon, T. Kelder, P. Mandaviya, C.T.A. Evelo, S.L. Coort. CyTargetLinker: a cytoscape app to integrate regulatory interactions in network analysis. PLoS One (2013).
  • M. Radonjic, P.Y. Wielinga, S. Wopereis, T. Kelder, V.S. Goelela, et al.Differential Effects of Drug Interventions and Dietary Lifestyle in Developing Type 2 Diabetes and Complications: A Systems Biology Analysis in LDLr−/− Mice. PLoS One (2013).
  • T Kelder, M.P. van Iersel, K. Hanspers, M. Kutmon, B.R. Conklin, C.T. Evelo, A.R. Pico. WikiPathways: building research communities on biological pathways. Nucleic Acids Research (2012).
  • L. Verschuren, M. Radonjic, P.Y. Wielinga, T. Kelder, T. Kooistra, et al. Systems biology analysis unravels the complementary action of combined rosuvastatin and ezetimibe therapy. Pharmacogenetics and Genomics (2012).
  • T. Kelder, L. Eijssen, R. Kleemann, M. van Erk, T. Kooistra, C. Evelo. Exploring pathway interactions in insulin resistant mouse liver. BMC Systems Biology (2011).
  • T. Kelder, B.R. Conklin, C.T. Evelo, A.R. Pico. Finding the Right Questions: Exploratory Pathway Analysis to Enhance Biological Discovery in Large Datasets. PLoS Biology (2010).
  • L. Coulier, S. Wopereis, C. Rubingh, H. Hendriks, M. Radonjic, R. H. Jellema. Application Systems Biology (In: Brown S, Tauler R, Walczak R (eds.) Comprehensive Chemometrics, volume 4, pp. 279-312 Oxford: Elsevier, 2009).
  • M. Radonjic, M.J. van Erk, W.J. Pasman, H.M. Wortelboer, H.F. Hendriks, B. van Ommen. Effect of body fat distribution on the transcription response to dietary fat interventions.Genes and Nutrition (2009). Associated press release.
  • A.R. Pico, T. Kelder, M.P. van Iersel, K. Hanspers, B.R. Conklin, C. Evelo. WikiPathways: pathway editing for the people. PLoS Biology (2008). Highlights in Nature & Science.
  • M. Radonjic, J.C. Andrau, P. Lijnzaad, P. Kemmeren, T.T. Kockelkorn, D. van Leenen, N.L. van Berkum, F.C. Holstege. Genome-wide analyses reveal RNA polymerase II located upstream of genes poised for rapid response upon S. cerevisiae stationary phase exit. Molecular Cell (2005). Highlight in Nature & Science Signaling.