UNLABELLED: GOSLING is a web-based protein function annotator that uses a decision tree-derived rule set to quickly predict Gene Ontology terms for a protein. A score is assigned to each term prediction that is indicative of the accuracy of the prediction. Due to its speed and accuracy GOSLING is ideally suited for high-throughput annotation tasks. AVAILABILITY: https://www.sapac.edu.au/gosling

BACKGROUND: Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO) sequence database (GOSeqLite). This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences. RESULTS: We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006) at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS) had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS) had an estimated error rate of 49%. CONCLUSION: While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.

BACKGROUND: With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with high accuracy. Our aim is to demonstrate how accuracy benchmarking can be used in a decision-making process evaluating competing designs of biological function predictors. We utilise the Gene Ontology, GO, a directed acyclic graph of functional terms, to annotate sequences with functional information describing their biological context. Initially we examine the effect on accuracy scores of increasing the allowed distance between predicted and a test set of curator assigned terms. Next we evaluate several annotator methods using accuracy benchmarking. Given an unannotated sequence we use the Basic Local Alignment Search Tool, BLAST, to find similar sequences that have already been assigned GO terms by curators. A number of methods were developed that utilise terms associated with the best five matching sequences. These methods were compared against a benchmark method of simply using terms associated with the best BLAST-matched sequence (best BLAST approach). RESULTS: The precision and recall of estimates increases rapidly as the amount of distance permitted between a predicted term and a correct term assignment increases. Accuracy benchmarking allows a comparison of annotation methods. A covering graph approach performs poorly, except where the term assignment rate is high. A term distance concordance approach has a similar accuracy to the best BLAST approach, demonstrating lower precision but higher recall. However, a discriminant function method has higher precision and recall than the best BLAST approach and other methods shown here. CONCLUSION: Allowing term predictions to be counted correct if closely related to a correct term decreases the reliability of the accuracy score. As such we recommend using accuracy measures that require exact matching of predicted terms with curator assigned terms. Furthermore, we conclude that competing designs of BLAST-based GO term annotators can be effectively compared using an accuracy benchmarking approach. The most accurate annotation method was developed using data mining techniques. As such we recommend that designers of term annotators utilise accuracy benchmarking and data mining to ensure newly developed annotators are of high quality.

Polymorphicabstraction provides the ability to write programs that are independent of the form of the data over which they operate.There are a number of different categories of polymorphic expression-ad hoc and umversal, which includes parametric and inclusion-all of which have many advantages in terms of code reuse and software economics.It has proved difficult to provide efficient implementations of polymorphism.Here, we address this problem and describe a new technique that can implement all forms of polymorphism, use a conventional machine architecture, and support nonuniform data representations.Furthermore, the method ensures that any extra cost of implementation applies to polymorphic forms only, and allows such polymorphic forms to persist over program invocations.

In this paper we are concerned with addressing techniques for statically typed languages with multiple inheritance. The addressing techniques are responsible for the efficient implementation of record field selection. In object-oriented languages, this record selection is equivalent to the access of methods. Thus, the efficiency of these techniques greatly affects the overall performance of an object-oriented language. We will demonstrate that addresses, in such systems, cannot always be calculated statically and show how symbol tables have been used as address maps at run time. The essence of the paper is a new addressing technique that can statically calculate either the address of a field or the address of the address of the field. This technique is powerful enough to support an efficient implementation of multiple inheritance with implicit subtyping as described by Cardelli.

The need to examine data structures often occurs in programming language and database management systems. In this paper we describe how a browser for a strongly type programming language (PS-algol) may be written in a type-secure manner in a closed persistent environment. This is achieved without resorting to magic or having to break the type rules of the language by exploiting a compiler that is an object with full civil rights in the environment. The use and impact of such an object is discussed.

Abstract The facilities of the PS‐algol programming language are described in this paper to show how they may be used to provide an integrated programming support environment. The persistent store mechanism and the secure transaction facilities provide the basic environment in which an integrated system may be implemented. In particular the paper makes use of the data type picture of PS‐algol to show how such an environment may be built for a graphics system ideal for use with a medium range computer workstation. An implementation of a picture editor on the ICL PERQ workstation is described to show the utility of the system.