98%
921
2 minutes
20
Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.
Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.
Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864930 | PMC |
http://dx.doi.org/10.1186/s13059-019-1835-8 | DOI Listing |
Microorganisms
August 2025
Multidisciplinary Department of Medical-Surgical and Odontostomatological Specialties, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy.
Periodontal diseases in pediatric subjects represent a challenging and relatively underexplored area compared to the extensive data available about periodontal diseases in adults. The present narrative review aims to explore the periodontal status and the related subgingival and/or salivary microbial profiles in pediatric subjects (≤18 years), focusing also on the state of health or systemic diseases. In healthy periodontium, early colonizers, such as and spp.
View Article and Find Full Text PDFSci Rep
February 2025
Departamento de Ciencias de la Construcción, Facultad de Ciencias de la Construcción Ordenamiento Territorial, Universidad Tecnológica Metropolitana, Santiago, Chile.
The optimization of metakaolin (MK) in pre-cured geopolymer concrete involves developing predictive models to capture the interplay of various influencing factors and guide mix design for improved compressive strength and sustainability. Ensemble methods and symbolic regression are promising approaches for this task due to their complementary strengths and solving challenges associated with repeated experiments in the laboratory. Choosing machine learning predictions over repeated, expensive, and time-consuming experiments in research projects, such as optimizing the utilization of metakaolin in pre-cured geopolymer concrete, presents a paradigm shift in how data-driven insights can revolutionize material development.
View Article and Find Full Text PDFSensors (Basel)
December 2024
State Grid Tianjin Electric Power Research Institute, Tianjin 300180, China.
Large oil-immersed transformers have metal-enclosed shells, making it difficult to visually inspect the internal insulation condition. Visual inspection of internal defects is carried out using a self-developed micro-robot in this work. Carbon trace is the main visual characteristic of internal insulation defects.
View Article and Find Full Text PDFClin Transl Allergy
January 2025
Department of Otorhinolaryngology & Clinical Allergy Center, The First Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Background: Digital health, digital medicine, and digital therapeutics integrate advanced computer technologies into healthcare, aiming to improve efficiency and patient outcomes. These technologies offer innovative solutions for the management of allergic diseases, which affect a significant proportion of the global population and are increasing in prevalence. BODY: This review examines the current progress and future potential of digital health in allergic disease management.
View Article and Find Full Text PDFProtein Sci
June 2024
Biological Data Science Lab, Department of Computer Engineering, Hacettepe University, Ankara, Turkey.
Identifying unknown functional properties of proteins is essential for understanding their roles in both health and disease states. The domain composition of a protein can reveal critical information in this context, as domains are structural and functional units that dictate how the protein should act at the molecular level. The expensive and time-consuming nature of wet-lab experimental approaches prompted researchers to develop computational strategies for predicting the functions of proteins.
View Article and Find Full Text PDF