IJFIPM 2013 - IJFIPM 2013 : Int. J. of Functional Informatics and Personalised Medicine - Special Issue on: Bioinformatics

Special Issue on: "Bioinformatics"
Guest Editor:
Hamid Alinejad-Rokny, University of Newcastle, Australia
One of principal tasks of data mining is to discover sequential patterns which have diverse applications. Using data mining techniques in the discovery of biological data and biomarkers is one of the crucial issues attracting researchers' concerns. Applying pattern mining algorithms in bioinformatics and medicine applications such as biomarker discovery, gene expression, motif discovery (e.g. transcription factor mining, transcription factor binding sites mining, promoter mining, DNA binding sites discovery, etc.) has been addressed by researchers recently.
Today, with the increasing development of new diseases, it is crucial to develop new methods to diagnose these diseases and new medicines to cure them. Biological data and biomarker discovery contributes to a better understanding of proteins and molecule structures and behaviours, and helps to diagnose and cure diseases to a large degree.
The primary goal of this special issue is to exchange the latest fundamental advances in biomarker discovery and the practice of pattern-mining algorithms and related areas. We are interested not only in papers with strong algorithmic and modelling innovations, but also in works that have biological models, application-oriented experimental implementations and evaluations.
The research presented in this special issue will be applicable for medical institutions, corporations developing medicines and any other parties involved in curing diseases.
Subject Coverage
Suitable topics include but are not limited to:
Fundamentals of biomarker discovery
Computational biomarker discovery in proteomics
Clinical bioinformatics and translational medicine
Applying pattern-mining algorithms to biological problems
Synthetic biology
Cancer prediction
Biomarkers in clinical drug development
Safety biomarkers
Methodologies for genome-wide association studies
Computational techniques for patient cohort stratification and segmentation
Deep sequencing
High-throughput technologies
Supercomputing to identify biomarkers
Mathematical methods for diagnostic classifiers
Biological network analysis
Network-based and pathway-aware biomarker strategies
Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper was not originally copyrighted and if it has been completely re-written).
All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page.