[Protein-analysis] CALL FOR CHAPTERS on Biological Data Mining in Protein Interaction Networks

Simon via proteins%40net.bio.net (by proteininteraction from gmail.com)
Thu Jan 17 04:31:30 EST 2008

Biological Data Mining in Protein Interaction Networks
A book edited by X.-L. Li and S.-K. Ng, Institute for Infocomm
Research, Singapore

The cellular machinery is a complex system with a multitude of bio-
molecular interactions.  Most of the cellular processes are mediated
by protein-protein interactions (PPIs).  Recently, high-throughput
methods for detecting PPIs have revealed global pictures of protein
interactions on a genomic scale, making it possible to interrogate the
interplay of the bio-molecules in carrying out critical life processes
at the networked co-operative level. As a result, modern biology's
focus has shifted from scrutinizing single molecules to analyzing
large complex networks.

The Overall Objective of the Book
Genome-wide screenings of PPIs can be represented as large protein
interaction networks (PINs) in which the nodes represent individual
proteins, and the links represent the existence of biological
interactions between the corresponding pairs of proteins. In this
book, we will present bioinformatics methods that are designed for the
computational analyses of the PINs to better understand critical life
processes such as the cellular signaling, molecular trafficking, and
gene regulatory pathways. Each of the chapters will serve as a
tutorial for network-based computational analysis PINs.  The objective
of this book is to disseminate the research results and best practice
from researchers and practitioners working on bioinformatics, data
mining, and proteomics.  We aim to present the various methodologies
in an accessible way to our inter-disciplinary audience, through which
we hope to bring better awareness of this interesting and c!
hallenging problem to inspire new solutions and applications.

The Target Audience
The book is aimed at three overlapping audiences:
(1) Researchers in the areas of bioinformatics, data mining, machine
learning and data structure;
(2) Practitioners in the industry in these areas;
(3) Instructors and postgraduate students in colleges and

This book will be an essential resource for professionals and
researchers who wish to learn about the application of advanced data
mining techniques in protein interaction networks. In addition, it can
be used as a reference for Masters and Ph.D. students studying

Recommended topics include, but are not limited to, the following:
Understanding the Properties of a Protein Interaction Network
Protein Interactions: Importance and Detection
Protein Interactions: In Silico Prediction
Interacting Domain Prediction and Usage
 Interacting Motif: Prediction and Usage
Lethal Proteins: Roles and Identification
Protein Function: Classification and Annotation
Protein Complexes: Construction via Computational Means
Functional Module: Detection and Biological Significance
Network Motif: Detection and Biological Relevance
Network Cleansing: Reliable Interaction Network
Conserved Network: Data Mining Across Species
PPI and Diseases: Mining Disease Genes from Protein Interaction
Computational Analysis for Cell Signaling
 Computational Analysis for Molecular Trafficking
 Computational Analysis for Receptor Applications
Integrating Protein Interaction Network with Other Biological

Submission Procedure
Researchers and practitioners are invited to submit on or before March
31, 2008, a 2-5 page manuscript proposal clearly explaining the
mission and concerns of the proposed chapter. Authors of accepted
proposals will be notified by April 10, 2008 about the status of their
proposals and sent chapter organizational guidelines. Full chapters
are expected to be submitted by May 31, 2008. All submitted chapters
will be reviewed on a double-blind review basis.

The book is scheduled to be published by IGI Global, www.igi-global.com,
publisher of the IGI Publishing (formerly Idea Group Publishing),
Information Science Publishing, IRM Press, CyberTech Publishing,
Information Science Reference (formerly Idea Group Reference), and
Medical Information Science Reference imprints.

Inquiries and submissions can be forwarded electronically (Word
document) or by mail to:

Dr. Xiao-Li Li
Data Mining Department
Institute for Infocomm Research
21 Heng Mui Keng Terrace, Singapore 119613
Tel: 65 68748452  *  Fax: 65 67768109
E-mail: xlli from i2r.a-star.edu.sg
Website: http://www1.i2r.a-star.edu.sg/~xlli/PPI_BOOK.html

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