Background: Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized.
Results: This work describes an application programming interface (API) that provides a framework for developing an effective biological knowledge ontology for Java-based software projects. The API provides a robust framework for the data acquisition and management needs of an ontology implementation. In addition, the API contains classes to assist in creating GUIs to represent this data visually.
Conclusions: The Knowledge Discovery Object Model (KDOM) API is particularly useful for medium to large applications, or for a number of smaller software projects with common characteristics or objectives. KDOM can be coupled effectively with other biologically relevant APIs and classes. Source code, libraries, documentation and examples are available at http://www.bcgsc.ca/bioinfo/software.
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http://dx.doi.org/10.1186/1471-2105-4-51 | DOI Listing |
Ann Bot
January 2025
Research Centre for Ecosystem Resilience, Botanic Gardens of Sydney, Sydney, NSW, 2000, Australia.
The importance of conserving plant genetic diversity has been recognised since the 1980's, but genetic research tools for improving conservation remain largely absent from standard planning. Using an Australian case study framework of the New South Wales Government's Saving our Species program, we outline the costs and benefits associated with conducting genomic analysis within a conservation strategy to inform for example, taxonomic resolution, targeted monitoring, translocations and ex situ collections. Despite a reported sentiment that costs are prohibitive, our study identified that where genetics reports have been provided (32 to date), the cost of genetic sampling, analysis and advice is less than 10% of the total Government investment (SoS program) and will continue decreasing proportionally throughout the years as other management occurs.
View Article and Find Full Text PDFLarge-scale gene expression profiling generates or integrates massive data of gene expression under drug induction and employs artificial intelligence algorithms for pattern matching and association analysis. This approach facilitates the identification of complex relationships and functional networks between drugs, genes, and diseases, thereby significantly advancing drug research. Traditional Chinese medicine(TCM), with its characteristic multi-component, multi-target, and multi-pathway mechanisms, poses challenges to conventional methodologies in the comprehensive elucidation of its biological effects.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Computer Science, Yonsei University, Yonsei-ro 50, Seodaemun-gu, 03722, Seoul, Republic of Korea.
Identifying new compounds that interact with a target is a crucial time-limiting step in the initial phases of drug discovery. Compound-protein complex structure-based affinity prediction models can expedite this process; however, their dependence on high-quality three-dimensional (3D) complex structures limits their practical application. Prediction models that do not require 3D complex structures for binding-affinity estimation offer a theoretically attractive alternative; however, accurately predicting affinity without interaction information presents significant challenges.
View Article and Find Full Text PDFHortic Res
January 2025
Metabolic engineering and Synthetic Biology Laboratory, Department of Natural Products, National Institute of Pharmaceutical Education and Research, S.A.S Nagar 160062, Punjab, India.
Triterpene (C30 isoprene compounds) represents the most structurally diverse class of natural products and has been extensively exploited in the food, medicine, and industrial sectors. Decades of research on medicinal triterpene biosynthetic pathways have revealed their roles in stress tolerance and shaping microbiota. However, the biological function and mechanism of triterpenes are not fully identified.
View Article and Find Full Text PDFACS Mater Au
January 2025
Institute for Advanced Materials and Manufacturing, Department of Materials Science and Engineering, Knoxville, Tennessee 37996, United States.
Halide perovskites (HPs) are emerging as key materials in the fight against global warming with well recognized applications, such as photovoltaics, and emergent opportunities, such as photocatalysis for methane removal and environmental remediation. These current and emergent applications are enabled by a unique combination of high absorption coefficients, tunable band gaps, and long carrier diffusion lengths, making them highly efficient for solar energy conversion. To address the challenge of discovery and optimization of HPs in huge chemical and compositional spaces of possible candidates, this perspective discusses a comprehensive strategy for screening HPs through automated high-throughput and combinatorial synthesis techniques.
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