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What are artificial neural networks?

Nature Biotechnology volume 26, pages 195–197 (2008)Cite this article

Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for?

When it comes to tasks other than number crunching, the human brain possesses many advantages over a digital computer. We can quickly recognize a face, even when seen from the side in bad lighting in a room full of other objects. We can easily understand speech, even that of an unknown person in a noisy room. Despite years of focused research, computers are far from performing at this level. The brain is also remarkably robust; it does not stop working just because a few cells die. Compare this to a computer, which will not normally survive any degradation of the CPU (central processing unit). But perhaps the most fascinating aspect of the brain is that it can learn. No programming is necessary; we do not need a software upgrade, just because we want to learn to ride a bicycle.

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Figure 1: Artificial neural networks.

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  1. Department of Biology and Biotech Research and Innovation Centre, Anders Krogh is at the Bioinformatics Centre, University of Copenhagen, Ole Maaloes Vej 5, DK-2200 Copenhagen, Denmark. krogh@binf.ku.dk,

    Anders Krogh

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  1. Anders Krogh
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Krogh, A. What are artificial neural networks?. Nat Biotechnol 26, 195–197 (2008). https://doi.org/10.1038/nbt1386

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  • DOI: https://doi.org/10.1038/nbt1386

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