What we do

With the advent of high-throughput technologies and clinical information systems, the life sciences and clinical sciences now produce very large amounts of data (big data). Our goal at CI4CB is to uncover hidden patterns in these data, as well as build data-driven models as tools to discover biomarkers and assist clinicians in their decisions. Our projects encompass the fields of transcriptomics, systems biology, and clinical bioinformatics & analytics.

Main publications 2018

  • Gomez S et al.
    Improving neural network interpretability via rule extraction.
    International Conference of Artificial Neural Networks (ICANN)
  • Despraz J et al.
    Exploring internal representations of deep neural networks.
    Studies in Comp Intel. Springer, https://doi.org/10.1007/978-3-030-16469-0_7
  • Leite D et al.
    Computational prediction of inter-species relationships through omics data analysis and machine learning.
    BMC Bioinfo, doi: 10.1186/s12859-018-2388-7

Find out more about the Group’s activities



Carlos-Andrés Peña-Reyes
Computational Intelligence for Computational Biology (CI4CB)
HEIG-VD, Yverdon-Les-Bains
Group Webpage

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Domain(s) of activity:

  • Text mining and machine learning
  • Systems biology
  • Biomarkers
  • Data mining
  • Machine learning
  • Metagenomics
  • Software engineering

Domain(s) of application:

  • Agriculture
  • Medicine and health
  • Ecology