I probably wouldn't be the only person to recommend Uri Alon's "An Introduction to Systems Biology: Design Principles of Biological Circuits" which is something of a classic text.

Kitano is a pretty good authority on systems biology. And he has a very good writing style. Here is a basic overview which you may have already come across:

http://www.sciencemag.org/cgi/content/full/295/5560/1662

EDIT:

Bernhard Palsson is the principal author on this protocol for network construction covering pretty much all bases:

http://www.nature.com/nprot/journal/v5/n1/full/nprot.2009.203.html

I just found out that the "Bioinformatics for Systems Biology" is available freely for an online read (PDFs for each chapter) here.

The book claims to cover the common grounds for systems biology and bioinformatics (and so not be only focused on the Bioinformatics part), and with chapters such as "Genomic Tools for Analyzing Transcriptional Regulatory Networks", "Statistical Tools for Gene Expression Analysis and Systems Biology and Related Web Resources" and "Methods for Structural Inference and Functional Module Identification in Intracellular Networks" (and that is only 3 out of 32 chapters), it seems to be of some relevance.

There are several types of biological networks that include(but not limited to) Gene Regulatory Networks, Protein-Protein Interaction(PPI) Networks, Metabolic Networks and Signal Transduction Networks.

Uri Alon's book focuses on Regulatory and Transcriptional Networks. Network Motif is a powerful concept that was first introduced by Uri Alon to understand the design principles of biological networks. You can find Alon's motif finder software here.

I am not aware of any book on Network Biology but Barbasi's this Nature Review article is a very good introduction to the topic and all the terminology that you might come across in Network Biology papers.

This review paper by Yang and Su not only covers Network Biology concepts but also lists a set of algorithms for module discovery. The paper also has nice a "Application" section which discusses how the framework of networks and modules helps in understanding cellular behavior under different biological contexts.

Biological Networks can be built based on several types of data...:

1. PPI from -Two Hybrid Assays, Mass Spec(protein complexes)
2. Regulatory and Transcriptional from - ChIP-on-Chip, ChIP-Seq
3. Metabolic Networks - eg KEGG PATHWAY database - from manual collection of metabolic reactions
4. Human Disease Networks - based on known disease-gene associations

Except for Alon's book mentioned above, I can recommend "System Modeling in Cellular Biology" by Szallasi and co-authors. I have only skimmed or read parts of both, but from this, it seems that while Alon's book captures the general ideas of regulation networks, this book is more of a collection of relevant methods and modelling approaches in Systems biology. I found the topics practical and interesting (There's even a list of recommended software tools available online).

I have been doing this course now and collected some of the resources

• http://bitesizebio.com/webinars/?post_status=publish
• http://tv.funet.fi/medar/showDirectory.do?directory=/metadata/fi/csc/courses/cytoscape&lang=en&page=1
• http://www.csc.fi/english/csc/courses/archive/bioc2008s
• http://edu.isb-sib.ch/course/view.php?id=48

All lectures and practical materials are available which will facilitate in learning system biology.

In my library I have the book Introduction to Systems Biology which should be a good starting point.

It's great that you're diving into systems biology! After building networks, there's still more to explore. To understand what comes next, you can consider pursuing an Online Masters in Biology. It can provide you with advanced knowledge in systems biology and related topics like statistical analysis, finding hubs and modules, and the types of data needed for network construction. Data can include expression or protein-protein interaction (PPI) data. Keep learning and exploring, and things will become clearer.