Workflow management systems (WfMSs) have been used to support various types of business processes for more than a decade now. In workflows for e-commerce and Web-services applications, suppliers and customers define a binding agreement or contract between the two parties, specifying Quality of Service (QoS) items such as products or services to be delivered, deadlines, quality of products, and cost of services. The management of QoS metrics directly impacts the success of organizations participating in e-commerce. Therefore, when services or products are created or managed using workflows, the underlying workflow system must accept the specifications and be able to estimate, monitor, and control the QoS rendered to customers. In this paper, we present a predictive QoS model that makes it possible to compute the quality of service for workflows automatically based on atomic task QoS attributes. To this end, we present a model that specifies QoS and describe an algorithm and a simulation system in order to compute, analyze and monitor workflow QoS metrics.

Workflow management systems (WfMSs) have been used to support various types of business processes for more than a decade now. In workflows for e-commerce and Web-services applications, suppliers and customers define a binding agreement or contract between the two parties, specifying Quality of Service (QoS) items such as products or services to be delivered, deadlines, quality of products, and cost of services. The management of QoS metrics directly impacts the success of organizations participating in e-commerce. Therefore, when services or products are created or managed using workflows, the underlying workflow system must accept the specifications and be able to estimate, monitor, and control the QoS rendered to customers. In this paper, we present a predictive QoS model that makes it possible to compute the quality of service for workflows automatically based on atomic task QoS attributes. To this end, we present a model that specifies QoS and describe an algorithm and a simulation system in order to compute, analyze and monitor workflow QoS metrics.

Abstract-In recent years, there has been a explosion in the amount of text data from a variety of sources. This volume of text is an invaluable source of information and knowledge which needs to be effectively summarized to be useful. Text summarization is the task of shortening a text document into a condensed version keeping all the important information and content of the original document. In this review, the main approaches to automatic text summarization are described. We review the different processes for summarization and describe the effectiveness and shortcomings of the different methods.

Protein phosphorylation by eukaryotic protein kinases (ePKs) is a fundamental mechanism of cell signaling in all organisms. In model vertebrates, ~10% of ePKs are classified as pseudokinases, which have amino acid changes within the catalytic machinery of the kinase domain that distinguish them from their canonical kinase counterparts. However, pseudokinases still regulate various signaling pathways, usually doing so in the absence of their own catalytic output. To investigate the prevalence, evolutionary relationships, and biological diversity of these pseudoenzymes, we performed a comprehensive analysis of putative pseudokinase sequences in available eukaryotic, bacterial, and archaeal proteomes. We found that pseudokinases are present across all domains of life, and we classified nearly 30,000 eukaryotic, 1500 bacterial, and 20 archaeal pseudokinase sequences into 86 pseudokinase families, including ~30 families that were previously unknown. We uncovered a rich variety of pseudokinases with notable expansions not only in animals but also in plants, fungi, and bacteria, where pseudokinases have previously received cursory attention. These expansions are accompanied by domain shuffling, which suggests roles for pseudokinases in plant innate immunity, plant-fungal interactions, and bacterial signaling. Mechanistically, the ancestral kinase fold has diverged in many distinct ways through the enrichment of unique sequence motifs to generate new families of pseudokinases in which the kinase domain is repurposed for noncanonical nucleotide binding or to stabilize unique, inactive kinase conformations. We further provide a collection of annotated pseudokinase sequences in the Protein Kinase Ontology (ProKinO) as a new mineable resource for the signaling community.

Abstract. Complex relationships, frequently referred to as semantic associations, are the essence of the Semantic Web. Query and retrieval of semantic associations has been an important task in many analytical and scientific activities, such as detecting money laundering and querying for metabolic pathways in biochemistry. We believe that support for semantic path queries should be an integral component of RDF query languages. In this paper, we present SPARQLeR, a novel extension of the SPARQL query language which adds the support for semantic path queries. The proposed extension fits seamlessly within the overall syntax and semantics of SPARQL and allows easy and natural formulation of queries involving a wide variety of regular path patterns in RDF graphs. SPARQLeR's path patterns can capture many low-level details of the queried associations. We also present an implementation of SPARQLeR and its initial performance results. Our implementation is built over BRAHMS, our own RDF storage system.