The best books at the intersection of Bioinformatics and Systems Biology

This book vindicates my long-held view that biological objects do not act in isolation but interact with other things to make a living whole. It confirms my opinion that genes are not the master controllers of living things.

Furthermore, it showed me that systems occur at different physical scales (molecules, cells, organs, organisms, populations), that the systems at these scales influence each other, and that no scale is dominant. To understand biological/medical phenomena, including human consciousness, one must look at the (multi-scale) systems, not their individual components, in isolation. 

Finally, I found it a lot of fun to read because it uses hypothetical stories to illustrate points. For example, silicon-based aliens visit Earth but fail to understand why certain things and people behave the way that they do.

Of the various books available on this subject, I very much prefer this one because it makes it far easier to do systems biology.

First, it shows you how to view biological regulatory processes as a set of interacting components and their effect on each other. This alone can give clues to the behaviour of the system under different circumstances. However, it then goes on to show how these processes can be defined mathematically, which then enables us to get a quantitative view of what is going on.

When the predicted and observed numbers don’t match, we know that there is a gap in our knowledge and, hence, the place to discover new biology. Using this approach, I have.

This book turns on its head what I was taught about what controls metabolite flow through a pathway. It covers highly remarkable discoveries concerning which steps control changes in metabolite levels: those at the end rather than the start of pathways. This is amazing because it explains why decades of effort by bioengineers to overproduce particular metabolites was unsuccessful.

In response to a request from such a project, I explained how to block the inhibitory regulation by the early pathway step but added that, according to metabolic control theory, this would leave the end-product levels unchanged. I was correct on both counts! When my group later provided results from using a systems biology approach, they achieved their production target levels.

This is one of my most valued reference books, and I have referred to it many times.

With some explanatory text, it consists of a set of maps of biochemical pathways, differentiating between organism kingdoms, and includes how specific metabolites regulate the activity of particular enzymes. The pathways are very easy to find and easy to interpret. In contrast, the online equivalents can be difficult to interpret for a variety of reasons.

The book has the added advantage that it does not need a power supply or an internet connection and can be used in a far wider range of temperatures than computer hardware.

This book has been a companion for almost three decades.

Any bona fide bioinformatician will write some program scripts if only to reformat data in new and useful ways. Perl is not the most efficient or widespread scripting language, but it has the advantage of being highly flexible. It offers many ways to write a program to carry out a given task, so even computationally naive programmers can generate effective code.

Even though I am no longer actively developing software, I still have occasions when it is quicker to script something in Perl than do battle with larger apps.