Frédérique Lisacek

BACKGROUND: Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. RESULTS: With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. CONCLUSIONS: pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss) creates, maintains and disseminates a portfolio of reliable and state-of-the-art bioinformatics services and resources for the storage, analysis and interpretation of biological data. Through Expasy (https://www.expasy.org), the Swiss Bioinformatics Resource Portal, the scientific community worldwide, freely accesses more than 160 SIB resources supporting a wide range of life science and biomedical research areas. In 2020, Expasy was redesigned through a user-centric approach, known as User-Centred Design (UCD), whose aim is to create user interfaces that are easy-to-use, efficient and targeting the intended community. This approach, widely used in other fields such as marketing, e-commerce, and design of mobile applications, is still scarcely explored in bioinformatics. In total, around 50 people were actively involved, including internal stakeholders and end-users. In addition to an optimised interface that meets users' needs and expectations, the new version of Expasy provides an up-to-date and accurate description of high-quality resources based on a standardised ontology, allowing to connect functionally-related resources.

The Symbol Nomenclature for Glycans (SNFG) is a community-curated standard for the depiction of monosaccharides and complex glycans using various colored-coded, geometric shapes, along with defined text additions. It is hosted by the National Center for Biotechnology Information (NCBI) at the NCBI-Glycans Page (www.ncbi.nlm.nih.gov/glycans/snfg.html). Several changes have been made to the SNFG page in the past year to update the rules for depicting glycans using the SNFG, to include more examples of use, particularly for non-mammalian organisms, and to provide guidelines for the depiction of ambiguous glycan structures. This Glycoforum article summarizes these recent changes.

Animal production and health (APH) is an important sector in the world economy, representing a large proportion of the budget of all member states in the European Union and in other continents. APH is a highly competitive sector with a strong emphasis on innovation and, albeit with country to country variations, on scientific research. Proteomics (the study of all proteins present in a given tissue or fluid - i.e. the proteome) has an enormous potential when applied to APH. Nevertheless, for a variety of reasons and in contrast to disciplines such as plant sciences or human biomedicine, such potential is only now being tapped. To counter such limited usage, 6 years ago we created a consortium dedicated to the applications of Proteomics to APH, specifically in the form of a Cooperation in Science and Technology (COST) Action, termed FA1002--Proteomics in Farm Animals: www.cost-faproteomics.org. In 4 years, the consortium quickly enlarged to a total of 31 countries in Europe, as well as Israel, Argentina, Australia and New Zealand. This article has a triple purpose. First, we aim to provide clear examples on the applications and benefits of the use of proteomics in all aspects related to APH. Second, we provide insights and possibilities on the new trends and objectives for APH proteomics applications and technologies for the years to come. Finally, we provide an overview and balance of the major activities and accomplishments of the COST Action on Farm Animal Proteomics. These include activities such as the organization of seminars, workshops and major scientific conferences, organization of summer schools, financing Short-Term Scientific Missions (STSMs) and the generation of scientific literature. Overall, the Action has attained all of the proposed objectives and has made considerable difference by putting proteomics on the global map for animal and veterinary researchers in general and by contributing significantly to reduce the East-West and North-South gaps existing in the European farm animal research. Future activities of significance in the field of scientific research, involving members of the action, as well as others, will likely be established in the future.