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 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 2017

  • Leite D et al. Computational Prediction of Host-Pathogen Interactions Through Omics Data Analysis and Machine Learning, IWBBIO 2017; Bioinformatics and Biomedical Engineering pp 360-371, 2017.
  • Mungloo Z et al. A Meta-Review of Feature Selection Techniques in the Context of Microarray Data, IWBBIO 2017; Bioinformatics and Biomedical Engineering pp 33-49, 2017.
  • Despraz J et al. Towards a Better Understanding of Deep Neural Networks Representations using Deep Generative Networks. IJCCI 2017.

Find out more about the Group’s activities

Members

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

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Domains of activity:

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

Domains of application:

  • Agriculture
  • Medicine and health

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