Computational tools are essential components of modern biological research. For example, BLAST searches can be used to identify related proteins based on sequence homology, or when a new genome is sequenced, prediction models can be used to annotate functional sites such as transcription start sites, translation initiation sites and polyadenylation sites and to predict protein localization. Here we present Sirius Prediction Systems Builder (PSB), a new computational tool for sequence analysis, classification and searching. Sirius PSB has four main operations: (1) Building a classifier, (2) Deploying a classifier, (3) Search for proteins similar to query proteins, (4) Preliminary and post-prediction analysis. Sirius PSB supports all these operations via a simple and interactive graphical user interface. Besides being a convenient tool, Sirius PSB has also introduced two novelties in sequence analysis. Firstly, genetic algorithm is used to identify interesting features in the feature space. Secondly, instead of the conventional method of searching for similar proteins via sequence similarity, we introduced searching via features' similarity. To demonstrate the capabilities of Sirius PSB, we have built two prediction models -one for the recognition of Arabidopsis polyadenylation sites and another for the subcellular localization of proteins. Both systems are competitive against current state-of-the-art models based on evaluation of public datasets. More notably, the time and effort required to build each model is greatly reduced with the assistance of Sirius PSB. Furthermore, we show that under certain conditions when BLAST is unable to find related proteins, Sirius PSB can identify functionally related proteins based on their biophysical similarities. Sirius PSB and its related supplements are available at: http://compbio.ddns.comp.nus.edu.sg/∼sirius

Abstract. There has been a growing interest in integrating vegetation into the built environment in order to ameliorate the negative effects of increasing urbanisation. In Singapore, government policies encourage the inclusion of skyrise greenery into new and existing buildings. To further streamline workflows, statutory BIM (Building Information Modelling) submissions in architecture, engineering and construction (AEC) industries have been mandated. However, landscape plans are still excluded from these BIM submissions due to the lack of a centralised vegetation database and the absence of a standardised BIM format for landscape architectural submissions. This paper presents a streamlined methodology for creating and using a centralised vegetation library for landscape architects. The workflow leverages off the Industry Foundation Classes (IFC) standard for data exchange regardless of the BIM authoring software used and provides a framework of four operational modules: an expandable and low-maintenance species-level vegetation library, a BIM authoring workflow that allows inclusion of vegetation objects, an IFC interface, and a lightweight 3D vegetation model generator. This paper also showcases a use-case of embedding information-enriched 3D vegetation objects into a simulated landscape plan. The proposed workflow, when adopted in AEC industries, will enable governing agencies to track diverse greening efforts by the industry and to potentially include other measurements such as cooling performance or maintainability.