In this paper, we develop a conceptual framework for organizing emerging analytic activities involving educational data that can fall under broad and often loosely defined categories, including Academic/Institutional Analytics, Learning Analytics/Educational Data Mining, Learner Analytics/Personalization, and Systemic Instructional Improvement. While our approach is substantially informed by both higher education and K-12 settings, this framework is developed to apply across all educational contexts where digital data are used to inform learners and the management of learning. Although we can identify movements that are relatively independent of each other today, we believe they will in all cases expand from their current margins to encompass larger domains and increasingly overlap. The growth in these analytic activities leads to the need to find ways to synthesize understandings, find common language, and develop frames of reference to help these movements develop into a field.

Manuscript Central is an interactive online system for authors, editors, reviewers and publishers of journals. The system is maintained and developed by ScholarOne Inc of Charlottesville, Virginia (http://www.scholarone.com) and is owned by the Thomson Corporation. The system is used by 170 different organizations to publish the impressive number of 2170 journals. Earlier this year (in April and June, respectively), Briefings in Bioinformatics and Briefings in Functional Genomics and Proteomics launched their own online submission sites on Manuscript Central. The system is customized to meet the needs of the specific journal and is organized according to the roles of the participating users. The BIB Manuscript Central Site has the following functionality: Author Centre for submissions; Reviewer Centre for reports; Editor Centre, Book Review Editor Centre and Managing Editor Centre for the decision making processes; Administration Centre for the administrative processes; Production Centre for the publisher. The benefits have been immediate, with increased efficiency in handling manuscripts at all stages. Editors have greatly improved control over the processing of manuscripts with an instant overview of all the manuscripts being processed with reminders to referees about overdue reports. As Managing Editor, one has a complete overview of all manuscripts in the system, including those that have been guest edited. This makes the final checking and signing off as approved by the Managing Editor very straightforward. In this issue, Bergman and Quesneville discuss the effects of transposable elements on genome structure and evolution including the development of new conceptual representations for transposable element annotation. Montana and Hoggart discuss the disease risk in populations that are recently derived from different ancestral populations and are therefore more heterogeneous than populations that are largely a single race. For a disease, in which the prevalence in the ancestral populations is very different, the variants responsible for the differences may be mapped by admixture linkage disequilibrium. Three publicly available computer programs to do this are discussed and compared. Meyer gives an introduction to the complex subject of RNA gene prediction that has become increasingly important, as many more such gene products have been recognized recently. There are many different types of RNA genes that perform diverse functions and differ considerably. The most powerful approach at present is to use similarity to find new representatives of gene families. Gregory et al. gives detailed worked examples of how to use the Affymetrix soybean chip to investigate differential expression of mRNAs. They show, with real data, how implementation of functions in R and Bioconductor successfully identified differentially expressed genes that may play a role in soybean resistance to a fungal pathogen Phakopsora pachyrhizi. Liu and Karimi discuss high-throughput modeling and analysis of protein structural dynamics. Their review describes the use of iGNM, an efficient web-based system for querying, computing and visualizing protein dynamics. Pavlidis discusses the role of informatics in neuroscience, showing how informatics is being used to study the nervous system at multiple levels, spanning scales from molecules to behavior. The importance of collaborative work and standards for data exchange is stressed. Cattley and Arthur discuss the use of BioManager, a web-based bioinformatics application integrating a variety of common bioinformatics tools for teaching purposes at the undergraduate level. They discuss some of the constraints that arise from using a bioinformatics resource primarily created for research in an undergraduate teaching environment.

A set of programs has been written to quantify the similarities between large numbers of cDNA sequences. This information is used to cluster similar sequences together. The main program can cluster thousands of cDNA sequences per day using a novel, computationally inexpensive algorithm. The clustering information is kept in a small index file so that disk storage requirements are negligible. Using this index file, subsidiary programs create various views and statistical summaries of the entire cDNA sequence collection.

This paper presents an overview of computing and networking facilities developed by the Medical Research Council to provide online computing support to the Human Genome Mapping Project (HGMP) in the UK. The facility is connected to a number of other computing facilities in various centres of genetics and molecular biology research excellence, either directly via high-speed links or through national and international wide-area networks. The paper describes the design and implementation of the current system, a 'client/server' network of Sun, IBM, DEC and Apple servers, gateways and workstations. A short outline of online computing services currently delivered by this system to the UK human genetics research community is also provided. More information about the services and their availability could be obtained by a direct approach to the UK HGMP-RC.

Nucleic acid and protein sequences contain a wealth of information of interest to molecular biologists. The advent of molecular sequence databases provides a unique opportunity for the computer analysis of all available sequences. Sequence databases serve two main functions: (i) to facilitate comparisons with newly determined sequences, and (ii) to act as a source of data for the generation and testing of hypotheses concerning molecular sequence organisation and evolution. The large amounts of sequence data now becoming available require that algorithms for database searching be fast and efficient and considerable progress is being made in this area.