During the past decades, we have witnessed the thriving development of new mathematical, computational and theoretical approaches such as bioinformatics and neuroinformatics to tackle some fundamental issues in biology. These scientific approaches focus no longer on individual units, such as nerve cells or genes, but rather on the emerging dynamic patterns of interactions between them. These concentrate on the interplay between the local dynamics and activity transmissions on one side and the global structure of the underlying connection scheme on the other hand.
In this light, the concept of a network emerges as a powerful and stimulating research paradigm in mathematics, physics and computer science, and demonstrates a very lively interaction between experimental findings, simulation studies, and theoretical investigations that then in turn lead to new experimental questions.
This volume explores this concept in full and features contributions from a truly global set of contributors, many of whom are pre-eminent in their respective fields.
Bioinformatics is the hottest topic in computer science. Each leading computer science department in UK has a group specialising in Bioinformatics or Computational Biology (system biology). The most important journal (according to impact factor) in computer science is "Bioinformatics" (~6). In Warwick, the University contributed £2.5 million to set up a System Biology Centre and is applying to BBSRC for £8.5 million in funding.
At the moment, we have accumulated a huge body of data about single variables (genes, proteins, neurons etc), but we are still far away from being clear about holistic issues arising from metabolic networks, gene networks, protein networks and neuronal networks. Progress is made by collecting, visualizing, and analyzing data using disparate fields such as image processing, database design and machine learning, and then modelling networks and predicting network outcomes based upon this data.
This book brings together leading scientists (computer scientists, applied mathematicians, and biologists) from Germany, China, USA and UK to discuss and present the most up-to-date results in the area.
Jianfeng Feng
Mathematica algorithms bioinformatics biology computer computer science genes genome mathematics networks patterns physiology protein simulation statistics