Neural Networks and Deep Learning for Biosciences

Dear Colleagues,

Biosciences are becoming increasingly data-centric and data intensive. Diagnostics and related methodologies that once exclusively relied on experts to characterize cells, tissues, and medical information are now using big data computational techniques for decision making. Deep learning encompasses machine learning algorithms that combine a network of successive processing layers of data representation. Modern deep learning can expand to tens or hundreds of layers depending on the complexity of the raw data and the learning success of the layered representations. The whole process is achieved via models that are called neural networks, inspired by the processing of information in the brain.

Deep learning has shown remarkable success in numerous life sciences disciplines, but amid concerns for lack of biological context. Nevertheless, as the field of biosciences rapidly evolves, so do the data and the computational resources available to researchers. Thus, the emerging combination of deep learning with biosciences, although challenging, can lead to high-impact goals in healthcare analytics, biomedical diagnosis, research in biology (including biophysics and biochemistry), personalized medicine, and pharmaceutical development.

This Special Issue is open for innovative contributions related to the above-mentioned topics. Manuscripts discussing the ethical considerations of deep learning in healthcare are also welcome.

Dr. Nikolaos Kourkoumelis
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Biosciences is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• neural networks
• deep learning
• biomedical diagnosis
• artificial intelligence in biosciences
• image analysis
• biomedical signal processing
• precision medicine
• omics
• computer-aided drug design
• healthcare data analytics