Rise and Demise of Bioinformatics? Promise and Progress

The field of bioinformatics and computational biology has gone through a number of transformations during the past 15 years, establishing itself as a key component of new biology. This spectacular growth has been challenged by a number of disruptive changes in science and technology. Despite the apparent fatigue of the linguistic use of the term itself, bioinformatics has grown perhaps to a point beyond recognition. We explore both historical aspects and future trends and argue that as the field expands, key questions remain unanswered and acquire new meaning while at the same time the range of applications is widening to cover an ever increasing number of biological disciplines. These trends appear to be pointing to a redefinition of certain objectives, milestones, and possibly the field itself

Synthetic Gene Circuits: Design with Directed Evolution

Synthetic circuits offer great promise for generating insights into nature's underlying design principles or forward engineering novel biotechnology applications. However, construction of these circuits is not straightforward. Synthetic circuits generally consist of components optimized to function in their natural context, not in the context of the synthetic circuit. Combining mathematical modeling with directed evolution offers one promising means for addressing this problem. Modeling identifies mutational targets and limits the evolutionary search space for directed evolution, which alters circuit performance without the need for detailed biophysical information. This review examines strategies for integrating modeling and directed evolution and discusses the utility and limitations of available methods

Quantum Technology: The Second Quantum Revolution

We are currently in the midst of a second quantum revolution. The first quantum revolution gave us new rules that govern physical reality. The second quantum revolution will take these rules and use them to develop new technologies. In this review we discuss the principles upon which quantum technology is based and the tools required to develop it. We discuss a number of examples of research programs that could deliver quantum technologies in coming decades including; quantum information technology, quantum electromechanical systems, coherent quantum electronics, quantum optics and coherent matter technology.Comment: 24 pages and 6 figure

Heterotic Computing Examples with Optics, Bacteria, and Chemicals

Unconventional computers can perform embodied computation that can directly exploit the natural dynamics of the substrate. But such in materio devices are often limited, special purpose machines. To be practically useful, unconventional devices are usually be combined with classical computers or control systems. However, there is currently no established way to do this, or to combine different unconventional devices. In this position paper we describe heterotic unconventional computation, an approach that focusses on combinations of unconventional devices. This will need a sound semantic framework defining how diverse unconventional computational devices can be combined in a way that respects the intrinsic computational power of each, whilst yielding a hybrid device that is capable of more than the sum of its parts. We also describe a suite of diverse physical implementations of heterotic unconventional computers, comprising computation performed by bacteria hosted in chemically built material, sensed and controlled optically and chemically.Ministerio de Ciencia e Innovación TIN2009–13192Ministerio de Ciencia e Innovación JCI-2010-0653

Emerging Era of Biomolecular Membrane Simulations: Automated Physically-Justified Force Field Development and Quality-Evaluated Databanks

Peer reviewe

Emerging Era of Biomolecular Membrane Simulations: Automated Physically-Justified Force Field Development and Quality-Evaluated Databanks

Peer reviewe

Design Environments for Complex Systems

The paper describes an approach for modeling complex systems by hiding as much formal details as possible from the user, still allowing verification and simulation of the model. The interface is based on UML to make the environment available to the largest audience. To carry out analysis, verification and simulation we automatically extract process algebras specifications from UML models. The results of the analysis is then reflected back in the UML model by annotating diagrams. The formal model includes stochastic information to handle quantitative parameters. We present here the stochastic -calculus and we discuss the implementation of its probabilistic support that allows simulation of processes. We exploit the benefits of our approach in two applicative domains: global computing and systems biology