Associated Edited Volume
Some researchers contributing presentations to the Workshop, the invited speakers and some further researchers will be asked if they wish to prepare and submit chapters for an associated edited volume. This volume will be entitled Cancer Bioinformatics. A well known academic publisher has expressed a keen interest in publishing this volume with final formal consideration given once the author list and content is finalised.
Purpose of the book:
Many types of data are being generated within cancer research and maximal effective use of these datasets draws on mathematical and computational skills from areas such as statistics, machine learning and bioinformatics. In this volume we will present a methodology-oriented approach, outlining contemporary data analysis methods applicable to this domain and novel methods which improve data interpretation. Many relevant contributions are scattered across statistics, machine learning and bioinformatics journals: thus we hope to present a cohesive approach to the subject.
The intended readership would be:
- Bioinformaticians associated with cancer research groups
- Researchers from areas such as machine learning, statistics, bioinformatics and computer science who may have an interest in analysing these or related datasets or have in interest in originating novel data analysis methods in this context.
- Cancer researchers who have an interest in bioinformatics and wish to understand the subject further.
The subject material of the book is therefore inherently multi-disciplinary and thus it is important to ensure that each chapter can be largely understood by readers outside the immediate mathematical or computational approach familiar to the author(s).Thus to enhance accessibility each contributed chapter should ideally contain two main parts:
- a section which is didactic in nature and oriented towards concepts rather than detail. It should give a substantive literature survey and avoid, as far as possible, technical hinderances to understanding such as complex equations,
- a later section in which the authors present their own research contribution: this section would have no restriction on technical content (equations can be presented and a higher level of technical understanding assumed).
For Section (b) authors should present their own research material. This material should be of their own origin but can be recently published or submitted for publication elsewhere. Again, to enhance understanding, the authors should include more detailed explanation than would be expected in a journal paper.
Prior to the Workshop we will contact the invited speakers to ask if they wish to prepare a chapter for the book. If you should be interested we would be grateful for a provisional title, author list (including institutions) and an abstract for the contributed chapter.
Following acceptance of a submission to the Workshop we will be contacting various potential authors about submitted chapters. If you should be interested we would be grateful for a provisional title, author list (including institutions) and extended abstract (with any supporting material) describing the contributed chapter. The abstract could be an update of your submission to the Call for Papers.
Prospective authors should not start preparing chapter material until the title, author and abstract list has been approved by the publisher. We will notify you when this outcome is agreed.
Chapters will be prepared in Latex with figures is eps or other Latex-compatible formats. An appropriate Latex style file will be made available. To maintain consistency of notation we have prepared a notation sheet downloadable here. If authors note any contexts in which an additional common notation is desirable please contact Colin Campbell (C.Campbell@bris.ac.uk) to update the common notation file. To avoid possible overlap of content between chapters we will use the software Subversion so that authors can view the current contents of other chapters. Chapters contributed by authors would be grouped under several themes such as Predicting disease progression and genetic predisposition to cancer, Novel methods for data integration, Pathway modeling and network inference, for example. These titles for subdivision of the book will be notified and discussed with authors nearer the deadline for finalising the book.