Call for papers: Semantic-Based Approaches for Analysis of Biological Data
23 January 2014
 IEEE/ACM Transactions on Computational Biology and Bioinformatics

Special Section on:

Semantic-Based Approaches for Analysis of Biological Data

The integration of biological (e.g. omics) data with biological knowledge is
a recent trend in Bioinformatics. A lot of biological information is available
and is spread on different sources and encoded in different ontologies
(e.g. Gene Ontology, as well as in many others hosted by the Open
Biomedical Ontologies Foundry).
Biological information is associated with biological concept in a process
known as annotation. Annotating existing protein data with biological
information may enable the use (and the development) of algorithms that
use biological ontologies as a framework to mine annotated data.
Recently many methodologies and algorithms that use ontologies to
extract knowledge from data, as well as to analyse ontologies themselves
have been proposed and applied to other fields. Conversely, the use of
such annotations for the analysis of protein data is a relatively novel
research area that is currently becoming more and more important
in research. As shown in literature there is a positive trend in the use
of biological information in the analysis of protein data.
Proposed approaches span from the definition of the similarity among
genes and proteins on the basis of the annotating terms, to the definition
of novel algorithms that use such similarities for mining protein data on a
system-level scale.
This special section will focus on novel approaches of such analysis such as
novel semantic similarity measures as well as novel algorithms focusing on
applications on biological problems. In particular interdisciplinary works
with clear implication and impact on wet lab biology are welcome. Finally
systematic discussion and critical comparison of main approaches may be
hosted. Remaining challenges, as well as possible future directions of
research may be highlighted.
Consequently topics include but are not limited to:
● Semantics approaches for Biomolecular network modeling
● Ontology Aware Function prediction from biomolecular networks
● Network motif analysis using semantics
● Definition of Domain Specific Ontologies
● Definition of semantic-based data mining algorithms
• Querying and retrieval of annotated data
● Integration of genome, proteome and interactome data using Semantics
● Semantic analysis of interactome and biomolecular data
● Definition of tailored Semantic Similarity Measures
● High Performance Computing for Semantic Analysis
Submission: 30 -November 2014
Revision: 30 March 2015
Guest Editors:
Pietro Hiram Guzzi University “Magna Graecia” of Catanzaro
Young-Rae Cho Baylor University of Texas
Marco Mina FBK Bruno Kessler Fundation
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