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The aim of this workshop called Bioinformatics and Artificial Intelligence (BAI) is to bring together active scholars and practionners in the frontier of Artificial Intelligence (AI) and Bioinformatics. AI holds a tremendous repertoire of algorithms and methods that constitute the core of different topics of bioinformatics and computational biology research. BAI goals are twofolds : How can AI techniques contribute to bioinformatics research ?, and How can bioinformatics research raise new fundamental questions in AI ? Contributions will clearly point out answers to one of these goals focusing on AI techniques as well as focusing on biological problems.

Important dates:

  • Deadline for Paper Submission: April 18th April 30th, 2016
  • Author Notification: May 30th, 2016
  • Camera Ready Deadline: June 10th, 2016
  • Workshop: July 11th, 2016

Useful links:

The workshop program is available here !

The workshop proceedings will be published on CEUR by August 1st 2016. However unedited version of the papers can be download here.

List of Accepted papers :

César Aguilar and Olga Acosta. Design of a Extraction System for Definitional Contexts from Biomedical Corpora.
Michael Benedikt, Rodrigo Lopez-Serrano and Efthymia Tsamoura. Biological Web Services: Integration, Optimization, and Reasoning.
Sylvester Olubolu Orimaye, Jojo Sze-Meng Wong and Judyanne Sharmini Gilbert Fernandez. Deep-Deep Neural Network Language Models for Predicting Mild Cognitive Impairment.
Sidak Pal Singh, Sopan Khosla, Sajal Rustagi, Manisha Patel and Dhaval Patel. SL-FII: Syntactic and Lexical Constraints with Frequency based Iterative Improvement for Disease Mention Recognition in News Headlines.
Samuel Sloate, Vincent Hsiao, Nina Charness, Ethan Lowman, Christopher J. Maxey, Sam Guannan Ren, Nathan Fields and Leora Morgenstern. Extracting Protein-Reaction Information from Tables of Unpredictable Format and Content in the Molecular Biology Literature.
Ricardo Souza Jacomini, David Correa Martins-Jr, Felipe Leno Da Silva and Anna Helena Reali Costa. A Framework for Scalable Inference of Temporal Gene Regulatory Networks based on Clustering and Multivariate Analysis.

Highlight paper :

Sabeur Aridhi, Haitham Sghaier, Manel Zoghlami, Mondher Maddouri and Engelbert Mephu Nguifo. Prediction of ionizing radiation resistance in bacteria using a multiple instance learning model.