Book Chapters


  • Hauschild, A-C, Pastrello, C, Kotlyar, M and Jurisica, I. Protein-protein interaction data, their quality, and major public databases. Ed. N. Przulj. Analyzing Network Data in Biology and Medicine, An Interdisciplinary Textbook for Biological, Medical and Computational Scientists, Cambridge University Press, Cambridge, UK, pp.151-192, 2019. ISBN 978-1-108-43223-8. DOI: 10.1017/978110837770
  • Wong, S., Pastrello, C., Kotlyar, M., Faloutsos, C., Jurisica, I. SDREGION: Fast spotting of changing communities in biological networks. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 867-875, 2018.
  • Kotlyar, M., Pastrello, C., Rossos, A., Jurisica, I. Protein-protein interaction databases. In: Ranganathan, S., Nakai, K., Schönbach C. and Gribskov, M. (eds.), Encyclopedia of Bioinformatics and Computational Biology, vol. 1, pp. 988–996. Oxford: Elsevier, 2018.
  • Rahmati, S., Pastrello, C., Rossos, A., Jurisica, I. Two Decades of Biological Pathway Databases: Results and Challenges, In: Ranganathan, S., Nakai, K., Schönbach C. and Gribskov, M. (eds.), Encyclopedia of Bioinformatics and Computational Biology, vol. 1, pp. 1071–1084. Oxford: Elsevier, 2018.
  • Hauschild, AC, Pastrello, C., Rossos, A., Jurisica, I. Visualization of Biomedical Networks, In: Ranganathan, S., Nakai, K., Schönbach C. and Gribskov, M. (eds.), Encyclopedia of Bioinformatics and Computational Biology, vol. 1, pp. 1016–1035. Oxford: Elsevier, 2018.
  • Jeanquartier, F., Jean-Quartier, C., Kotlyar, M., Tokar, T., Hauschild, A.-C., Jurisica, I., Holzinger, A., Machine Learning for In Silico Modeling of Tumor Growth, Machine Learning for Health Informatics, State-of-the-Art and Future Challenges, LNAI 9605, Springer: 415-434, 2016.
  • Larsen, S.J., Alkaersig, F.G., Ditzel, L.J., Jurisica, I., Alcaraz, N., Baumbach, J. A Simulated Annealing Algorithm for Maximum Common Edge Subgraph Detection in Biological Networks, GECCO, ACM Press, 341-348, 2016.
  • Veillette, C. J. H. and I. Jurisica. Precision Medicine for Osteoarthritis. Osteoarthritis. Pathogenesis, Diagnosis, Available Treatments, Drug Safety, Regenerative and Precision Medicine. Eds. M. Kapoor and N. Mahomed, Springer: 257-270, 2015.
  • Holzinger, A., Dehmer M., Jurisica, I. Knowledge Discovery and Data Mining in Biomedical Informatics: The Future Is in Integrative, Interactive Machine Learning Solutions, Eds. Holzinger, A., Jurisica, I., Interactive Knowledge Discovery and Data Mining: State-of-the-Art and Future Challenges in Biomedical Informatics, Volume 8401, LNCS, SOTA, Springer, 1-18, 2014.
  • Otasek, D., Pastrello, C., Holzinger, A., Jurisica, I., Visual data mining: Effective exploration of the biological universe; Eds. Holzinger, A., Jurisica, I., Interactive Knowledge Discovery and Data Mining: State-of-the-Art and Future Challenges in Biomedical Informatics, Volume 8401, LNCS, SOTA, Springer, 19-33, 2014.
  • Ponzielli R., Tu W.B., Jurisica I., Penn L.Z., Identifying myc interactors. Methods Mol Biol. 1012:51-64. 2013.
  • Andritsos, P., Jurisica, I., and Glasgow, J. Case-Based Reasoning for Biomedical Informatics and Medicine, 2013.
  • Heifets, A., Jurisica, I. Construction of new medicines via game proof search.26th American Association for Artificial Intelligence Conference on Artificial Intelligence (AAAI-12), AAAI Press, Menlo Park, 1564-1570, 2012.
  • Wong, S., Cercone, N., Jurisica, I. Characterizing healthy and disease states by systematically comparing differential correlation networks in lung. Advances in Health Informatics, Toronto, ON, 2012. [Best student paper award]
  • Otasek, D., Pastrello, C., Jurisica, I. Scalable, integrative analysis and visualization of protein interactions, Protein-Protein Interactions - Computational and Experimental Tools, WeiboCai and Hao Hong (Ed.), ISBN: 978-953-51-0397-4, InTech, pp 457-472, 2012.
  • King, A. D., Przulj, N., Jurisica, I. Protein Complex Prediction with RNSC, Bacterial Molecular Networks, Series: Methods in Molecular Biology, Editors: Jacques van Helden, Ariane Toussaint, Denis Thieffry, Humana Press, Vol. 804, 297-312, 2012.
  • Geraci, J., Liu, G., Jurisica, I. Algorithms for systematic identification of small sub-graphs, Bacterial Molecular Networks, Series: Methods in Molecular Biology, Editors: Jacques van Helden, Ariane Toussaint, Denis Thieffry, Humana Press, Vol. 804, 219-244, 2012.
  • Xia, E., Jurisica, I., J. Waterhouse, V. Sloan. Runtime estimation using the case-based reasoning approach for scheduling in a grid environment. Eds. I. Bichindaritz and S. Montani, Case-Based Reasoning Research and Development, ICCBR-10, LNAI-6176, 525-539, 2010.
  • Chaudhri, V.K., Jurisica, I., Koubarakis, M., Plexousakis, D., Topaloglou, T.The KBMS project and beyond. In Borgida, A. T. et al., (Eds.), Conceptual Modeling: Foundations and Applications, LNCS 5600, Springer, 466-483, 2009
  • Niu, Y. and I. Jurisica, Detecting protein-protein interaction sentences using a mixture model, in Natural Language and Information Systems (NLDB'08), Lecture Notes in Computer Science, E. Kapetanios, V. Sugumaran, and M. Spiliopoulou, Editors, Springer Verlag, Berlin, 352-354, 2008.
  • Barrios-Rodiles, M., A. Viloria-Petit, K. R. Brown, I. Jurisica, and J. L. Wrana. High-throughput screening of protein interaction networks in the TGFb interactome: understanding the signaling mechanisms driving tumor progression. Cancer Drug Discovery and Development: Transforming Growth Factor-b in Cancer Therapy, Vol2: Cancer Treatment and Therapy, Edited by Sonia B. Jakowlew, Humana Press Inc., Totowa, N.J., pp. 265-285, 2007.
  • Yan, R., P. C. Boutros, L.Z. Penn, I. Jurisica. Comparison of machine learning and pattern discovery algorithms for the prediction of human single nucleotide polymorphisms. IEEE International Conference on Granular Computing, IEEE, 2007.
  • Xia, E., I. Jurisica, J. Waterhouse, V. Sloan. The impact of runtime estimation in accuracy on scheduler performance, IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS 2007), 351-356, November 19-21, Cambridge, MA, 2007.

  • Other Publications


    Invited papers, reviews, correspondence

  • Zhu, C.Q., Pintilie, M., John, T., Strumpf, D., Shepherd, F.A., Der, S.D., Jurisica, I., Tsao, M.-S., Understanding Prognostic Gene Expression Signatures in Lung Cancer, Clin Lung Cancer, 10(5): 331-340, 2009
  • Dong, J., Kislinger, T., Jurisica, I., Wigle, D. A. Lung cancer: Developmental networks gone awry? Cancer BiolTher, 8(4), 2009.
  • Jurisicova, A., I. Jurisica, T. Kislinger. Advances in ovarian cancer proteomics: The quest for biomarkers and improved therapeutic interventions, Expert Review of Proteomics, 5(4): 551-560, 2008.
  • Wigle, D. A. and I. Jurisica. Cancer as a system failure. Cancer Informatics. Systems Biology Special Issue editorial, 3(2): 10-18, 2007
  • Evangelou, A., L. Gortzak-Uzan, I. Jurisica and T. Kislinger. Mass spectrometry, proteomics, data mining and their applications in infectious disease research, Anti-Infective Agents in Medicinal Chemistry, 6(2):89-105, 2007

  • Editorials

  • Hoeng J, Peitsch MC, Meyer, P. and Jurisica, I. Where are we at regarding species translation? A review of the sbv IMPROVER Challenge, Bioinformatics, 31(4):451-452, 2015.
  • Holzinger, A., Jurisica, I. Interactive Knowledge Discovery and Data Mining Methods in Biomedical Informatics: The future is in Integrative Machine Learning! Ed. Holzinger, A. and Jurisica, I. Interactive Knowledge Discovery and Data Mining: State-of-the-Art and Future Challenges in Biomedical Informatics, Volume 8401, LNCS, SOTA, Springer, 2014.
  • Holzinger, A., Dehmer, M. Jurisica, I. Interactive knowledge discovery and data mining in bioinformatics-State-of-the-art, future challenges and research directions, Special issue BMC Bioinf, 15 Suppl 6, I1, 2014.
  • Yakhini, Z. and Jurisica, I. Cancer computational biology, BMC Bioinf. 12(1): 120, 2011. Commentaries
  • Mills, G. B., Jurisica, I., Yarden, Y., Norman, J. C. Genomic amplicons target vesicle recycling in breast cancer. J Clin Invest, 19(8): 2123-7, 2009. Letters to Editor
  • Boutros, P.C., Pintilie, M., John, T., Starmans, M.H.W., Der, S.D., Shepherd, F.A., Tsao, M.S., Jurisica, I. Re: Gene expression-based prognostic signatures in lung cancer: Ready for clinical use?, J Nat Cancer Inst, 102(21): 1677-8, 2010.

  • All contents copyright Jurisica Lab, Krembil Research Institute, UHN. Last modified February 2019