Advancements in Artificial Intelligence (AI) for Cancer Genomics and Genetics

Dear Colleagues,

The progress made through the application of computational approaches to biology and medicine requires a broad expertise for the management, processing, analysis, and interpretation of the results produced using very heterogeneous data. Inter-disciplinary collaborations and resources are key because large amounts of information cannot be handled by single scientists working in their specialized fields. Data need to be collected, reviewed, processed, and analyzed in order to create models aimed at understanding diseases at the molecular level, allowing the basis for personalized medicine to be established. Research regarding the neoplastic transformation will significantly benefit from this progress as well, and the use of Artificial Intelligence (AI) to leverage large datasets is expected to become more and more important.

Cancer is a multistep and complex disease; its onset is influenced by several factors including—but not limited to—the genetic background of patients, their lifestyle, the environment in which they live, and multiple interactions among these factors. Moreso than before, cancer characterization cannot be limited to the evaluation of cytological/histological features and the testing of a few biomarkers. An integrated approach and the use of AI appear necessary, involving not only high-throughput data analysis, but also its contextualization in order to identify the best tools for diagnosis, prognosis, and treatment. 

We are pleased to invite you to submit your contribution, with the goal of understanding and characterizing human cancer in terms of all the aforementioned aspects. Comprehensive reviews, illustrating the state of the art in the use of AI in cancer genetics/genomics, are equally welcome.

Research areas may include (but are not limited to) the following: (i) the use of AI to collect, filter, and/or analyze large datasets for cancer characterization; (ii) the use of genetics and genomics approaches in cancer; (iii) the response of genes to complex environmental insults; (iv) studies based on cancer transcriptomics; ad (v) new approaches for the early diagnosis and personalized treatment of cancer, as well as related topics.

We are looking forward to receiving your contribution.

Dr. Roberto Piergentili
Guest Editor

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• artificial intelligence
• cancer
• genetics
• epigenetics
• genomics
• epigenomics
• gene-environment interaction
• cancer diagnosis and prognosis
• personalized medicine
• drug discovery