Current day networked intelligent agent based systems have limited capability of adaptability, self-repair, adaptation, and self-reconfiguration under changing external conditions. In past, evolutionary algorithms have experimented with random mutation and heuristic selection based evolution for self-adaptation. However, little research has been done to explore dynamic adaptive control to take care of sudden external stress and events at systemic response level. This work introduces a new message based biological model of intelligent multiagent based systems that represents agents as self-correcting dynamically modifiable genes - a reconfigurable set of dynamically regulated built-in functions, and system of agents as dynamically adaptable event-trigger controlled interacting pathways that can be altered and reconfigured in response to external stress and events. The model supports the integration of message, code, trigger, and belief states, and supports interchangeability of message, code, and trigger to provide dynamic adaptive control. The model and its implementation have been described.

This paper describes an automated technique to predict integrated pathways and refine existing metabolic pathways using the information of automatically derived, functionally similar gene-groups and orthologs (functionally equivalent genes) derived by the comparison of complete microbial genomes archived in GenBank. The described method integrates automatically derived orthologous and homologous gene-groups (http://www.mcs.kent.edu//spl sim/arvind/orthos.html) with the biochemical pathway template available at the KEGG database (http://www.genome.ad.jp), the enzyme information derived from the SwissProt enzyme database (http:// expasys.hcuge.ch/), and the Ligand database (http://www.genome.ad.jp). The technique refines existing pathways (based upon the network of reactions of enzymes) by associating corresponding nonenzymatic and regulatory proteins to enzymes and operons and by identifying substituting homologs. The technique is suitable for building and refining integrated pathways using evolutionary diverse organisms. A methodology and the corresponding algorithm are presented. The technique is illustrated by comparing the genomes of E coli and B. subtilis with M. tuberculosis. The findings about integrated pathways are briefly discussed.

This paper extends previously described automated techniques by automatically integrating the information about automatically derived co-transcribed gene-groups, functionally similar gene-groups derived using automated pair-wise genome comparisons and automatically derived orthologs (functionally equivalent genes) to derive microbial metabolic pathways. The method integrates automatically derived co-transcribed gene-groups with orthologous and homologous gene-groups (http://www.mcs.kent.edu//spl sim/arvind/orthos.html), the biochemical pathway template available at the KEGG database. (http://www.genome.ad.jp), the enzyme information derived from the SwissProt enzyme database (http://expasy.hcuge.ch/) and Ligand database (http://www.genome.ad.jp). The technique refines existing pathways (based upon network of reactions of enzymes) by associating corresponding non-enzymatic, regulatory, and cotranscribed proteins to enzymes. The technique has been illustrated by deriving a major pathway of M. tuberculosis by comparison with seven microbial genomes including E coli and B. subtilis - two microbes well explored in wet laboratories.

Describes a framework for the automated reconstruction of metabolic pathways using information about orthologous and homologous gene groups derived by the automated comparison of whole genomes archived in GenBank. The method integrates automatically derived orthologs, orthologous and homologous gene groups (), the biochemical pathway template available in the Kegg database (), and enzyme information derived from the SwissProt enzyme database () and the Ligand database (). The technique is useful to identify refined metabolic pathways based on operons, and to derive the non-enzymatic genes within a group of enzymes. The technique has been illustrated by a comparison between the E. coli and B. subtilis genomes.

The paper describes a knowledge-based scalable multimedia environment for graph based modeling and the design of complex objects over the Internet. A complex object is modeled as a directed hierarchical graph with each sub-component abstracted as a node and the shared parameters between two components as an edge. The knowledge base archives and retrieves reusable components, and integrates multiple simultaneous distributed numeric simulations of components over the Internet. The tool exploits heterogeneous associative logic programming and has been implemented using CORBA to exploit heterogeneity and user transparent distributed object-based computing. Java has been used for an architecture independent graphical user interface accessible via the World Wide Web. The design is visualized using XML extended to visualize graph-based multimedia objects over the Internet.

MOTIVATION: As sequenced genomes become larger and sequencing becomes faster, there is a need to develop accurate automated genome comparison techniques and databases to facilitate derivation of genome functionality; identification of enzymes, putative operons and metabolic pathways; and to derive phylogenetic classification of microbes. RESULTS: This paper extends an automated pair-wise genome comparison technique (Bansal et al., Math. Model. Sci. Comput., 9, 1-23, 1998, Bansal and Bork, in First International Workshop of Declarative Languages, Springer, pp. 275-289, 1999) used to identify orthologs and gene groups to derive orthologous genes in a group of genomes and to identify genes with conserved functionality. Seventeen microbial genomes archived at ftp://ncbi.nlm.nih.gov/genbank/genomes have been compared using the automated technique. Data related to orthologs, gene groups, gene duplication, gene fusion, orthologs with conserved functionality, and genes specifically orthologous to Escherichia coli and pathogens has been presented and analyzed. AVAILABILITY: A prototype database is available at ftp://www.mcs.kent.edu/arvind/intellibio / orthos.html. The software is free for academic research under an academic license. The detailed database for every microbial genome in NCBI is commercially available through intellibio software and consultancy corporation (Web site: http://www.mcs.kent.edu/årvind/intellibio . html). CONTACT: [email protected].

This paper describes a distributed implementation of a scalable heterogeneous associative logic programming model, and describes an abstract instruction set for the distributed version of the model. Associative computation exploits data parallel computation. The implementation uses PVM for architecture independence, and uses object oriented programming for modularity and portability. Performance results on a cluster of IBM RS 6000 are presented.

Associative computation is characterized by the intertwining of search by content and data parallel computation. This intertwining facilitates the integration of knowledge retrieval and data parallel computation. The paper describes a formal set of architecture independent rules for an associative model of logic programming, and an abstract instruction set. The model integrates knowledge retrieval, data parallel computation, and rule based reasoning within logic programming paradigm. An example of abstract instructions has been presented through the compilations of illustrative programs. Benchmark results have been presented. Benchmark result shows that tight integration of rule based reasoning and data parallel computation has reduced overhead on high performance supercomputers.>

An associative data-parallel compilation model of logic programs capable of answering queries with unspecified relations concerning the given objects is described. The model benefits from the synergy resulting from associative search, data-parallelism during goal reduction, and the use of low-level code to invoke the subgoals and savings in data-transfers resulting from the presence of global registers. The use of associative tables extends the power of logic programming to answer a large class of queries and derive unspecified relation-names for the given objects. In contrast to the interpretation based on a pure data parallel model, this model does not suffer from data sequentiality caused by the presence of multiple-occurrence variables in the goals. The model also handles variable aliasing in the clauses efficiently using the associative data-parallel search and data-parallel assignment property.>