The 10th International Workshop on Biological Knowledge Discovery from Big Data (BIOKDD'19)

Held in conjunction with
The 30th International Conference on Database and Expert Systems Applications (DEXA’19)
Linz, Austria August 26 - 29, 2019

In the recent years, there has been a rapid development of biological technologies producing more and more biological data, i.e., data related to biological macromolecules (DNA, RNA and proteins). The rise of Next Generation Sequencing (NGS) technologies, also known as high-throughput sequencing technologies, has contributed actively to the deluge of these data. In general, these data are big, heterogeneous, complex, and distributed in all over the world in databases. Analyzing biological big data is a challenging task, not only, because of its complexity and its multiple and numerous correlated factors, but also, because of the continuous evolution of our understanding of the biological mechanisms. Classical approaches of biological data analysis are no longer efficient and produce only a very limited amount of information, compared to the numerous and complex biological mechanisms under study. From here comes the necessity to adopt new computer tools and develop new in silico high performance approaches to support us in the analysis of biological big data and, hence, to help us in our understanding of the correlations that exist between, on one hand, structures and functional patterns in biological macromolecules and, on the other hand, genetic and biochemical mechanisms. Biological Knowledge Discovery from Big Data (BIOKDD) is a response to these new trends.

Topics of BIOKDD’19 workshop includes, but not limited to:

Data Preprocessing: Biological Big Data Storage, Representation and Management (data warehouses, databases, sequences, trees, graphs, biological networks and pathways, …), Biological Big Data Cleaning (errors removal, redundant data removal, completion of missing data, …), Feature Extraction (motifs, subgraphs, …), Feature Selection (filter approaches, wrapper approaches, hybrid approaches, embedded approaches, …).

Data Mining: Biological Big Data Regression (regression of biological sequences…), Biological Big Data Clustering/Biclustering (microarray data biclustering, clustering/biclustering of biological sequences, …), Biological Big Data Classification (classification of biological sequences…), Association Rules Learning from Biological Big Data, Text mining and Application to Biological Sequences, Web mining and Application to Biological Big Data, Parallel, Cloud and Grid Computing for Biological Big Data Mining.

Data Postprocessing: Biological Nuggets of Knowledge Filtering, Biological Nuggets of Knowledge Representation and Visualization, Biological Nuggets of Knowledge Evaluation (calculation of the classification error rate, evaluation of the association rules via numerical indicators, e.g. measurements of interest, … ), Biological Nuggets of Knowledge Integration



Authors are invited to submit electronically original contributions in English. Submitted papers should not exceed 5 pages in Springer CCIS format. All accepted papers will be published by Springer in "Communications in Computer and Information Science.". One of the authors of an accepted paper must register to DEXA’19 conference and present the paper at BIOKDD’19 workshop. For paper registration and electronic submission see starting from January 2019.


  • Submission of abstracts: March 11, 2019  
  • Submission of full papers: March 18, 2019  
  • Notification of acceptance: May 18, 2019  
  • Camera-ready copies due: June 08, 2019


  • Mourad Elloumi, LaTICE, University of Tunis, Tunisia (PC Chair)
  • Davide Verzotto, University of Pisa, Italy
  • Emanuel Weitschek, Uninettuno University, Rome, Italy
  • Haider Banka, India Institute of Technology, Dhanbad, India
  • Suresh Dara, B V Raju Institute of Technology, Hyderabad, India
  • Daisuke Kihara, Purdue University, West Lafayette, USA
  • Bhaskar DasGupta, University of Illinois at Chicago, Chicago, USA
  • Robert Harrison, Georgia State University, Atlanta, Georgia, USA
  • Jérémie Bourdon, University of Nantes, France
  • Abdelhalim Larhlimi, University of Nantes, France
  • Dominique Lavenier, GenScale, IRISA-CNRS, Rennes, France
  • Malik Yousef, Zefat Academic College, Zefat, Israel
  • Giuseppe Lancia, University of Udine, Italy
  • Farhana Zulkernine, School of Computing Queen’s University Kingston, Ontario, Canada
  • Vladimir Makarenkov, University of Québec, Montréal, Canada
  • P. Ch. J. Srinivasa Rao, Koneru Lakshmaiah University, Vijayawada, India
  • Matteo Comin, University of Padova, Padova, Italy
  • Adrien Goëffon, University of Angers, France
  • Maad Shatnawi, Higher colleges of Technology, Abu Dhabi, UAE
  • Mirto Musci, University of Pavia, Pavia, Italy
  • Tomas Flouri, University College London, UK
  • Solon Pissis, Centrum Wiskunde & Informatica, Amsterdam, Netherlands
  • Jamal Al Qundus, Free University of Berlin, Berlin, Germany