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Machine Learning and Artificial Intelligence in Bioinformatics

Section edited by Jean-Philippe Vert

This section covers recent advances in machine learning and artificial intelligence methods, including their applications to problems in bioinformatics. It considers manuscripts describing novel computational techniques to analyse high throughput data such as sequences and gene/protein expressions, as well as machine learning techniques such as graphical models, neural networks or kernel methods.

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  1. Automatic extraction of chemical-disease relations (CDR) from unstructured text is of essential importance for disease treatment and drug development. Meanwhile, biomedical experts have built many highly-struc...

    Authors: Huiwei Zhou, Chengkun Lang, Zhuang Liu, Shixian Ning, Yingyu Lin and Lei Du

    Citation: BMC Bioinformatics 2019 20:260

    Content type: Research article

    Published on:

  2. Computational approaches for the determination of biologically-active/native three-dimensional structures of proteins with novel sequences have to handle several challenges. The (conformation) space of possibl...

    Authors: Ahmed Bin Zaman and Amarda Shehu

    Citation: BMC Bioinformatics 2019 20:211

    Content type: Research article

    Published on:

  3. Long non-coding RNAs play an important role in human complex diseases. Identification of lncRNA-disease associations will gain insight into disease-related lncRNAs and benefit disease diagnoses and treatment. ...

    Authors: Xiao-Nan Fan, Shao-Wu Zhang, Song-Yao Zhang, Kunju Zhu and Songjian Lu

    Citation: BMC Bioinformatics 2019 20:87

    Content type: Research article

    Published on:

2019 Journal Metrics

  • Citation Impact
    3.242 - 2-year Impact Factor
    3.213 - 5-year Impact Factor
    1.156 - Source Normalized Impact per Paper (SNIP)
    1.626 - SCImago Journal Rank (SJR)

    Usage 
    4,058,323 downloads

    Social Media Impact
    6067 mentions