Principles of Computational Cell Biology

From Protein Complexes to Cellular Networks

Volkhard Helms

• Publisher: Wiley-VCH
• Year: 2018
• ISBN:
  9783527810321
• Edition: 2
• Topic: Medicine
• Subtopic: Biostatistics

Computational cell biology courses are increasingly obligatory for biology students around the world but of course also a must for mathematics and informatics students specializing in bioinformatics. This book, now in its second edition is geared towards both audiences. The author, Volkhard Helms, has, in addition to extensive teaching experience, a strong background in biology and informatics and knows exactly what the key points are in making the book accessible for students while still conveying in depth knowledge of the subject.About 50% of new content has been added for the new edition. Much more room is now given to statistical methods, and several new chapters address protein-DNA interactions, epigenetic modifications, and microRNAs.

Preface of the Second Edition ¹

About 10 years after the publication of the first edition, I finally managed to prepare this expanded second edition of this book. Its main spirit remained the same: it is designed as a textbook, placing emphasis on transmitting the main ideas of a problem, outlining algorithmic strategies for solving these, and describing possible complications or connections to other parts of the book. Because of the feedback from colleagues, I have reordered the content, starting now in Chapter 2 with an introduction into the structures of protein–protein complexes before we enter into the world of protein interaction networks. I refrain from listing all the rearrangements here. Usually, I tried to keep subsections intact and simply shifted them around. A few sections were removed from the text because I now felt that they were too specialized. About 50% of new content has been added. In terms of mathematical methods, much more room is now given to statistical methods. In terms of biology, several new chapters now address protein–DNA interactions, epigenetic modifications, and microRNAs. Still not covered are biophysical topics related to intracellular transport, cytoskeletal dynamics, and processes taking place at and across biological membranes. Maybe, there will be a need for a third edition eventually?

In addition to those who contributed to the first edition, the author is very grateful to Thorsten Will and Maryam Nazarieh for solved examples and problems for this book. The following coworkers from Saarbrücken and elsewhere have provided valuable suggestions on different portions of the text: Mohamed Hamed Fahmy, Dania Humaidan, Olga Kalinina, Heiko Rieger, and Thorsten Will. I thank my group members of the past years with whom I had the privilege to work on exciting research projects related to the content of this book and I thank our secretary Kerstin Gronow‐Pudelek for technical assistance.

April 2018

Volkhard Helms

Center for Bioinformatics

Saarland University

Saarbrücken, Germany

Note

¹ Problems: To really absorb the content of this textbook, it is advisable to also try to solve some of the problems enclosed.

1
Networks in Biological Cells

Modern molecular and cell biology has worked out many important cellular processes in more detail, although some other areas are known to a lesser extent. It often remains to understand how the individual parts are connected, and this is exactly the focus of this book. Figure 1.1 displays a cartoon of a cell as a highly viscous soup containing a complicated mixture of many particles. Certainly, several important details are left out here that introduce a partial order, such as the cytoskeleton and organelles of eukaryotic cells. Figure 1.1 reminds us that there is a myriad of biomolecular interactions taking place in biological cells at all times and that it is pretty amazing how a considerable order is achieved in many cellular processes that are all based on pairwise molecular interactions.

Figure 1.1Is this how we should view a biological cell? The point of this schematic picture is that about 30% of the volume of a biological cell is taken up my millions of individual proteins. Therefore, biological cells are really “full.” However, of course, such pictures do not tell us much about the organization of biological processes. As we will see later in this book, there are many different hierarchies of order in such a cell.

The focus of this book is placed on presenting mathematical descriptions developed in recent years to describe various levels of cellular networks. We will learn that many biological processes are tightly interconnected, and this is exactly where many links still need to be discovered in further experimental studies. Many researchers in the field of molecular biology believe that only combined efforts of modern experimental techniques, mathematical modeling, and bioinformatics analysis will be able to arrive at a sufficient understanding of the biological networks of cells and organisms.

In this chapter, we will start with some principles of mathematical networks and their relationship with biological networks. Then, we will briefly look at several biological key players to be used in the rest of this book (cells, compartments, proteins, and pathways). Without going into any further detail, we will directly move into the field of network theory with the amazing “small‐world phenomenon.”

1.1 Some Basics About Networks

Network theory is a branch of applied mathematics and more of physics that uses the concepts of graph theory. Its developments are led by application to real‐world examples in the areas of social networks (such as networks of acquaintances or among scientists having joint publications), technological networks (such as the World Wide Web that is a network of web pages and the Internet that is a network of computers and routers or power grids), and biological networks (such as neural networks and metabolic networks).

1.1.1 Random Networks

In a random network, every p...