Predrag Radivojac

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Pedja Radivojac, Indiana University, 2013

Professor of Computer Science

Adjunct Professor of Statistics


Department of Computer Science and Informatics

Indiana University

150 South Woodlawn Avenue

Bloomington, IN 47405

Office:  Lindley Hall 301F

Phone:  (812) 856-1851


Download my curriculum vitae in pdf format (last updated on 12/24/2016). Google Scholar profile.


Post-doctoral fellow, Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, 2004

Ph.D., Computer and Information Sciences, Temple University, Philadelphia, Pennsylvania, 2003

M.S., Electrical Engineering, University of Belgrade, Serbia, 1997

B.S., Electrical Engineering, University of Novi Sad, Serbia, 1994

Professional Activities:

Board of Directors Member, International Society for Computational Biology (ISCB), 2012-

Associate Editor, PLoS Computational Biology, 2014-

Editorial Board Member, Bioinformatics, Oxford University Press, 2010-

Critical Assessment of Functional Annotations (CAFA) at ISMB 2017

The CAFA3 experiment is currently on. The submission deadline is January 22 February 2, 2017. Check out the following papers about CAFA: CAFA1, CAFA2, and a gentle introduction to CAFA. An even gentler introduction to protein function prediction is available here.

Recent Updates:

  1. (January 2017) Shantanu to give a talk at AAAI 2017.

  2. (December 2016) Jose defends Ph.D. dissertation on December 12. Congratulations! Staying at Indiana on the Precision Health Initiative Project!

  3. (December 2016) Pedja awarded August-Wilhelm Scheer Visiting Professor position at Technical University of Munich in Germany, 2017. Also visited in 2016.

  4. (November 2016) Vikas defends Ph.D. dissertation on November 17. Congratulations! Moving soon to University of Washington (eScience Moore/Sloan Data Science Postdoctoral Fellowship).

  5. (November 2016) Shantanu's paper about performance estimation in positive-unlabeled learning accepted for AAAI 2017.

  6. (October 2016) Shantanu receives travel award for NIPS 2016.

  7. (October 2016) Pedja to give a talk at the NIPS workshop on Challenges in Machine Learning.

  8. (September 2016) Sujun's paper accepted to the Journal of Proteome Research; available here.

  9. (September 2016) CAFA2 paper officially published, with Yuxiang being the first author; available here.

  10. (September 2016) We have pre-computed MutPred scores for about 80 million possible human variants; available here.

  11. (August 2016) Shantanu's paper accepted to NIPS 2016; pre-print available on arXiv.

  12. (August 2016) Jose's paper on the functional significance of disease mutations accepted to PLoS Computational Biology.

  13. (July 2016) Krishna Reddy's paper (U South Florida) with Vikas and me as coauthors accepted to Journal of Biomolecular Structure and Dynamics.

  14. (July 2016) Our review paper, with Burkhard Rost (TUM) and Yana Bromberg (Rutgers) on protein function, machine learning and precision medicine accepted to FEBS Letters.

  15. (July 2016) Kym gave a talk at ISMB's VarI-SIG in Orlando, Florida. Jose, Vikas, Ruiyu and Yuxiang all attended ISMB.

  16. (June 2016) Vikas's paper in top-10 most cited papers in Protein Science among all papers published in 2014-2015.

Center Affiliations:

Center for Algorithms and Machine Learning (CAML)

Center for Bioinformatics Research (CBR)

Research Interests:

Bioinformatics and Computational Biology

 Protein structure and function; method development and evaluation for function prediction

 Post-translational modifications (PTMs)

 Mass spectrometry (MS) and MS/MS proteomics


Biomedical Informatics and Applications to Human Health

 Development of computational models for understanding and predicting molecular mechanisms of disease

 Candidate gene prioritization and biomarker discovery

 Genome interpretation and precision medicine


Machine Learning

 Supervised and semi-supervised learning: learning from positive and unlabeled data; learning from biased data

 Structured-output learning and evaluation; extreme classification

 Kernel-based inference on sequences, time-series, and graphs


Last modified: January 14, 2017