The evolution of genomics

Bio-inspired computing tissues: towards machines that evolve, grow, and learn

Biological inspiration in the design of computing machines could allow the creation of new machines with promising characteristics such as fault-tolerance, self-replication or cloning, reproduction, evolution, adaptation and learning, and growth. The aim of this paper is to introduce bio-inspired computing tissues that might constitute a key concept for the implementation of 'living' machines. We first present a general overview of bio-inspired systems and the POE model that classifies bio-inspired machines along three axes. The Embryonics project--inspired by some of the basic processes of molecular biology--is described by means of the BioWatch application, a fault-tolerant and self-repairable watch. The main characteristics of the Embryonics project are the multicellular organization, the cellular differentiation, and the self-repair capabilities. The BioWall is intended as a reconfigurable computing tissue, capable of interacting with its environment by means of a large number of touch-sensitive elements coupled with a color display. For illustrative purposes, a large-scale implementation of the BioWatch on the BioWall's computational tissue is presented. We conclude the paper with a description of bio-inspired computing tissues and POEtic machines.

Paralogous genes encoding transport proteins in microbial genomes

The largest superfamilies of prokaryotic genes encode transport proteins, but many transporters are encoded by orphan genes or those that comprise very small families. We have analyzed eighteen completely sequenced prokaryotic genomes for paralogous transport systems and have thereby identified 76 permease families. In this short review, we present and discuss the paralogues in some of these families and interpret the most prominent results, particularly those relevant to the largest permease superfamilies.

Routine DNA sequencing of 1000 bases in less than one hour by capillary electrophoresis with replaceable linear polyacrylamide solutions

Long, accurate reads are an important factor for high-throughput de novo DNA sequencing. In previous work from this laboratory, a separation matrix of high-weight-average molecular mass (HMM) linear polyacrylamide (LPA) at a concentration of 2% (w/w) was used to separate 1000 bases of DNA sequence in 80 min with an accuracy close to 97% (Carrilho, E.; et al. Anal. Chem. 1996, 68, 3305-3313). In the present work, significantly improved speed and sequencing accuracy have been achieved by further optimization of factors affecting electrophoretic separation and data processing. A replaceable matrix containing a mixture of 2.0% (w/w) HMM (9 MDa) and 0.5% (w/w) low-weight-average molecular mass (50 kDa) LPA was employed to enhance the separation of DNA sequencing fragments in CE. Experimental conditions, such as electric field strength and column temperature, as well as internal diameter of the capillary column, have been optimized for this mixed separation matrix. Under these conditions, in combination with energy-transfer (BigDye) dye-labeled primers for high signal-to-noise ratio and a newly developed expert system for base calling, the electrophoretic separation of 1000 DNA sequencing fragments of both standard (M13mp18) and cloned single-stranded templates from human chromosome 17 could be routinely achieved in less than 55 min, with a base-calling accuracy between 98 and 99%. Identical read length, accuracy, and migration time were achieved in more than 300 consecutive runs in a single column.