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Cancer Informatics

Synopsis: An open access, peer reviewed electronic journal that covers the role of computational biology and bioinformatics in cancer treatment.


Indexing: 8 major databases including Pubmed.

Processing time: Decision in 3 weeks for 95% of papers.

Visibility: Most popular article read 2700+ times.

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About this journal

Aims and scope:

We live in a time when it is widely recognized that scientific collaborations across traditional disciplines can yield exponential gains through synergy. Cancer research is currently benefiting from advances in many fields, including biology (genomics and proteomics), physical chemistry (mass spectrometry and radio imaging), computer science and biostatistics (machine learning, artificial intelligence), and many others.

There exists a bewildering diversity of scientific journals in which new applications of these advances toward discovery in cancer research is reported. Leveraging these advances into new medicines and medical practices for the early detection, prevention and treatment of cancer is made difficult by the broad diffusion this literature. Bioinformatics and computational biology appear to play a central role at each nexus, in part because novel technologies lead to immense leaps in the amount and granularity of data from patients and patient samples.

A number of important journals exist that focus on a wide breadth of foci within bioinformatics. Medical informatics is a field nearly as wide that includes patient information systems and related critical components of information management in the information age.

Editorial standards and procedures:

Submissions, excluding editorials, letters to the editor and dedications, will be peer reviewed by two reviewers.  Reviewers are required to provide fair, balanced and constructive reports.  

Under our Fairness in Peer Review Policy authors may appeal against reviewers' recommendations which are ill-founded, unobjective or unfair.  Appeals are considered by the Editor in Chief or Associate Editor.

Papers are not sent to peer reviewers following submission of a revised manuscript. Editorial decisions on re-submitted papers are based on the author's response to the initial peer review report.

Indexing:

This journal is indexed by:

  • Pubmed
  • Pubmed Central
  • CAS
  • DOAJ
  • EMBase
  • Scopus
  • Google Scholar

SPARC Europe Seal award winner:

This journal has been awarded a SPARC Europe Seal. The Seal is an initiative of SPARC Europe (Scholarly Publishing and Academic Resources Coalition) and the Directory of Open Access Journals (DOAJ) which is awarded to journals applying a Creative Commons CC-BY copyright license and that make journal metadata accessible to DOAJ.  

Amongst other important services DOAJ makes metadata OAI-compliant.  This in turn enhances the visibility of papers and allows OAI-harvesters to include the details of journal articles in their services. We encourage readers to make use of this valuable resource.  The DOAJ search page is available here.

National Institutes of Health Public Access Policy compliant:

As of April 7 2008, the US NIH Public Access Policy requires that all peer reviewed articles resulting from research carried out with NIH funding be deposited in the Pubmed Central archive.

If you are an NIH employee or grantee Libertas Academica will ensure that you comply with the policy by depositing your paper at Pubmed Central on your behalf. 

ISSN: 1176-9351


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Editor in Chief: Igor Jurisica

Dr. Igor Jurisica is a Canada Research Chair in Integrative Computational Biology, a Scientist at the Ontario Cancer Institute, University Health Network since 2000, Associate Professor in the Departments of Computer Science and Medical Biophysics, University of Toronto, Adjunct Professor at School of Computing Science, Queen's University, and a Visiting Scientist at the IBM Centre for Advanced Studies. He earned his Dipl. Ing.
degree in Computer Science and Engineering from the Slovak Technical University in 1991, M.Sc. and Ph.D. in Computer Science from the University of Toronto in 1993 and 1998 respectively.

Dr. Jurisica's research focuses on computational biology, and representation, analysis and visualization of high dimensional data generated by high-throughput biology experiments. Of particular interest is the use of comparative analysis for the mining of integrated datasets such as protein-protein interaction, gene expression profiling, and high-throughput screens for protein crystallization.