Novel Bioinformatics and Machine Learning Applications in Cancer

Dear Colleagues,

For a number of decades, cancer biology has been transformed by technological advancements that have made it a data-rich field. Reductions in per-sample cost for sequencing, sample indexing, and improvements in microfluidic technologies that allow single-cell-level measurements have all contributed to this deluge of data. These data provide insight into cellular processes, biological heterogeneities, and sensitivities to external perturbation and allow new hypotheses to be generated and/or tested. For information to be derived from these data, bioinformatic approaches including machine learning and artificial intelligence tools are required.

This Special Issue aims to provide a snapshot of some of the current bioinformatics and machine learning method developments with a focus on translational and application efforts in cancer biology. Contributions must shed light on novel developments that facilitate the identification of the heterogeneity of mutations found in a specific gene; explore genotype–phenotype correlations; characterize model systems reflecting the emergence of genetic pathology, diagnostic biomarkers, pathophysiological mechanisms, genome-wide association studies (GWAS) and novel pharmacogenomic approaches. To progress our knowledge of such intricate issues, we invite contributions in the form of research manuscripts and critical reviews.

Dr. Tobias K. Karakach
Dr. Arvind Mer
Guest Editors

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. Genes is an international peer-reviewed open access monthly 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 2600 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.

• bioinformatics
• machine learning
• cancer
• artificial intelligence
• software