Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems. Recently, simple molecular-scale autonomous programmable computers were demonstrated allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for 'logical' control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.

GeneCards (Rebhan et al., 1998) has made innovative strides: (a). regular updates and enhancements incorporating new genes enriched with sequences, genomic locations, cDNA assemblies, orthologies, medical information, 3D protein structures, gene expression, and focused SNP summaries; (b). restructured software using object-oriented Perl, migration to schema-driven XML, and (c). pilot studies, introducing methods to produce cards for novel and predicted genes.

GeneCards TM (http://bioinfo.weizmann.ac.il/cards/) is an automated, integrated database of human genes, genomic maps, proteins, and diseases, with software that retrieves, consolidates, searches, and displays human genome information [1,2]. Over the past few years, the system has consistently added new features including sequence accessions, genomic locations, cDNA assemblies, orthologies, medical information, 3D protein structures, SNP summaries, and gene expression. In parallel, its infrastructure is being upgraded to use object-oriented Perl [3] to produce, display, and search data that is formatted in Extensible Markup Language (XML -(http://www.w3.org/XML), providing a basis for schemadriven display code and context-specific searches.