13 papers · ranked by Valyu relevance
Chen Huang, Keliang Cen, Yang Zhang, Bo Liu + 2 more
Prior studies have suggested close associations between miRNAs and diseases. Correct prediction of potential miRNA-disease pairs by computational methods is able to greatly accelerate the experimental process in biomedical research. However, many methods cannot effectively learn the complex information in the…
Jiayou Zhang, Zhirui Wang, Shizhuo Zhang, Megh Manoj Bhalerao + 3 more
Biomedical entity normalization unifies the language across biomedical experiments and studies, and further enables us to obtain a holistic view of life sciences. Current approaches mainly study the normalization of more standardized entities such as diseases and drugs, while disregarding the more ambiguous but crucial…
Tiffany J. Callahan, Ignacio J. Tripodi, Lawrence E. Hunter, William A. Baumgartner
Although knowledge graphs (KGs) are used extensively in biomedical research to model complex phenomena, many KG construction methods remain largely unable to account for the use of different standardized terminologies or vocabularies, are often difficult to use, and perform poorly as the size of the KG increases in…
Ilya Levin
This article describes Amorpha, a software package based on new concept of exact graph-based linguistic analysis. Analytical capabilities of Amorpha are demonstrated using analysis of scientific abstracts on clinical trials from PubMed. Current trends in therapy of breast cancer and psoriatic arthritis were analyzed…
Charles Tapley Hoyt, Klas Karis, Benjamin M. Gyori
Hundreds of resources assign identifiers to biomedical concepts including genes, small molecules, biological processes, diseases, and cell types. Often, these resources overlap by assigning identifiers to the same or related concepts. This creates a data interoperability bottleneck, as integrating data sets and…
Rita T. Sousa, Sara Silva, Catia Pesquita
Semantic similarity between concepts in knowledge graphs is essential for several bioinformatics applications, including the prediction of protein-protein interactions and the discovery of associations between diseases and genes. Although knowledge graphs describe entities in terms of several perspectives (or semantic…
Tom C. Freeman, Sebastian Horsewell, Anirudh Patir, Josh Harling-Lee + 5 more
Quantitative and qualitative data derived from the analysis of genomes, genes, proteins or metabolites from tissue or cells are currently generated in huge volumes during biomedical research. Graphia is an open-source platform created for the graph-based analysis of such complex data, e.g. transcriptomics, proteomics…
Jaesik Kim, Dokyoon Kim, Kyung-Ah Sohn
Knowledge manipulation of gene ontology (GO) and gene ontology annotation (GOA) can be done primarily by using vector representation of GO terms and genes for versatile applications such as deep learning. Previous studies have represented GO terms and genes or gene products to measure their semantic similarity using…
Vignesh Prabhakar, Chau Vu, Jennifer Crawford, Joseph Waite + 1 more
Generating knowledge graph embeddings (KGEs) to represent entities (nodes) and relations (edges) in large scale knowledge graph datasets has been a challenging problem in representation learning. This is primarily because the embeddings / vector representations that are required to encode the full scope of data in a…
Favour James, Christopher Churas, Dexter Pratt, Augustin Luna
Knowledge graphs (KGs) are powerful tools for structuring and analyzing biological information due to their ability to represent data and improve queries across heterogeneous datasets. However, constructing KGs from unstructured literature remains challenging due to the cost and expertise required for manual curation.…
Evangelos Karatzas, Fotis A. Baltoumas, Nikolaos A. Panayiotou, Reinhard Schneider + 1 more
Efficient integration and visualization of heterogeneous biomedical information in a single view is a key challenge. In this study, we present Arena3D^web^, the first, fully interactive and dependency-free, web application which allows the visualization of multilayered graphs in 3D space. With Arena3D^web^, users can…
Samuel Barton, Zoe Broad, Daniel Ortiz-Barrientos, Diane Donovan + 1 more
Multidisciplinary approaches can significantly advance our understanding of complex systems. For instance, gene co-expression networks align prior knowledge of biological systems with studies in graph theory, emphasising pairwise gene to gene interactions. In this paper, we extend these ideas, promoting hypergraphs as…
Luca Menestrina, Maurizio Recanatini
In this study, we present PATHOS (PATHologies of HOmo Sapiens), a semantically rich knowledge graph constructed by integrating diverse datasets spanning multiple biomedical entity types. PATHOS provides a comprehensive resource for representing and exploring the intricate relationships underlying human diseases. To…