Eugene Kolker, PhD

Chief Data Officer, Seattle Children's Hospital

Director, Bioinformatics & High-throughput Analysis Lab, Seattle Children's Research Institute

Executive and Founding Editor of OMICS: A Journal of Integrative Biology & Big Data journals

Affiliate Professor, Biomedical Informatics and Medical Education

Affiliate Professor, Pediatrics

Adjunct Professor, Departments of Chemistry and Chemical Biology, Northeastern University, Boston, MA


Data Analysis, Predictive Analytics, Big Data, Data Mining, Machine Learning, Optimization, Statistical and Algorithmic Development, Bioinformatics, Omics, Community Development, Proteomics, Systems Analysis, Systems Biology, Autism, Heart Diseases.


Eugene Kolker is the Chief Data Officer at Seattle Children’s — Hospital, Research Institute, and Foundation. Eugene has over 25 years of experience in multi-disciplinary data analysis, predictive analytics, and modeling and over 15 years of experience in management, business, and community development. At Seattle Children’s, Eugene heads the CDO Analytics team (, which focuses on leveraging large and complex data to improve outcomes and safety, reduce costs, broaden access, and drive innovation. In addition to his hospital work, he is also the Director of the Bioinformatics & High-throughput Analysis Laboratory at the Research Institute. Previously, Eugene Kolker was the Founder and President of BIATECH Biotechnology Innovation Center, which was acquired by Seattle Children’s. Currently, Dr. Kolker is an Adjunct Professor at Northeastern University College of Science, Boston and an Affiliate Professor at University of Washington School of Medicine, Seattle. He has 130 publications in 40 different journals and also serves as the Executive Editor of the journals “OMICS: A Journal of Integrative Biology” and “Big Data.” In 2015, Eugene was nominated by the HIMSS (Healthcare Information and Management Systems Society) members to be one of the top three “Innovators” in their annual HIT Awards. He was also named one of the “top 16 data-driven geeks to watch” by HIMSS.

Representative publications:

1. Keller, Nesvizhskii, Kolker, Aebersold, Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search, Analytical Chemistry, 2002, 74 (20): 5383-5392.

2. Kolker et al., Global profiling of Shewanella oneidensis MR-1: expression of hypothetical genes and improved functional annotations, PNAS USA, 2005, 102 (6): 2099-2104.

3. Taylor… Kolker et al., Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nature Biotechnology, 2008, 26 (8): 889-896.

4. Field… Kolker et al., Megascience. ‘Omics data sharing, Science, 2009, 326 (5950): 234-236.

5. Chain… Kolker et al., Genome project standards in a new era of sequencing. Science, 2009, 326 (5950): 236-237.

6. Hather… Kolker, The United States of America and scientific research, PLOS ONE, 2010, 5 (8): e12203.

7. Kolker… Kolker, Classifying proteins into functional groups based on all-versus-all BLAST of 10 million proteins, OMICS JIB, 2011, 15 (7-8): 513-521.

8. Higdon… Kolker, Predictive analytics in healthcare: Medications as a predictor of medical complexity. Big Data, 2013, 1 (4), 237-244.

9. Kolker, Kolker, Healthcare analytics: Creating a prioritized improvement system with performance benchmarking. Big Data, 2014, 2 (1), 50-54.

10. Montague… Kolker, Beyond protein expression, MOPED goes multi-omics. Nucleic Acid Research, 2015, 43 (D1): 1145-1151.