Cancer Informatics and Big Data
A section of Cancers (ISSN 2072-6694).
Section Information
The availability of large cancer- and health-related data sets offers promise for understanding the genetic basis as well as the mechanisms of the initiation and progression of cancer. However, to optimally use and exploit large databases, optimal informatics and data analytics methods and tools, as well as other resources for developing novel cancer therapies and improving cancer care, must be applied to the sequencing and molecular data. The unavailability of appropriate analytics or prediction tools is often a challenge. The accessible computing power has drastically increased in recent years, requiring further development or replacement of software originally designed for much more limited resources and data. In this section of Cancers, we invite the submission of original research papers as well as timely review articles related to these challenges and opportunities. Topics of interest include, but are not limited to, all areas of cancer informatics and big data analytics, for example:
- Artificial intelligence
- Cancer immunology methods
- Data storage and sharing
- Deep learning
- Drug discovery, drug re-purposing, drug-resistance
- Image processing and analysis
- Next-generation sequencing
- Precision medicine and clinical decision-making
- Single-cell data analytics
- Statistical methods
- Visualization of large data sets
Editorial Board
Topical Advisory Panel
Special Issues
Following special issues within this section are currently open for submissions:
- Biomedical Informatics and Cancer (Deadline: 31 March 2024)
- Computational Pathology for Breast Cancer and Gynecologic Cancer (Deadline: 31 March 2024)
- Long-Read Sequencing in Cancer (Deadline: 19 April 2024)
- Advances in Cancer Data and Statistics (Deadline: 26 April 2024)
- Oncogenomic and Multi-Omic Data Science and Data Engineering (Deadline: 25 May 2024)
- Next Generation Sequencing for Cancer Diagnostics (Deadline: 31 May 2024)
- Recent Advances of Deep Learning for Cancer Diagnosis and Prognosis (Deadline: 30 June 2024)
- Artificial Intelligence in Cancer Research: Knowledge Representation and Data Perspectives (Deadline: 15 August 2024)
- Novel Approaches to Machine Learning and Artificial Intelligence in Cancer Research and Care (Deadline: 30 September 2024)
- Graph Neural Networks in Cancer Research (Deadline: 31 December 2024)
- Integrative Histopathology-Molecular and Computational Analysis of Primary Brain Tumors (Deadline: 31 July 2025)
Topical Collection
Following topical collection within this section is currently open for submissions: