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basicml

brca_cancersubtype

dep

Prediction of Disease-Enhancer Associations

drivergene

A workflow for identification and analysis of driver genes

graomicdrp

graphdrp

hdr

linkpred

Easy link prediction tool

ml4gwas

rwdisenh

rwrmtn

spectralgraph

ufo

Background: Biomedical ontologies have been growing quickly and proven to be useful in many biomedical applications. The use of these data is mainly based on semantic similarity calculation between ontology terms and between annotated biomedical entities. In addition, they are also used in enrichment analyses. Many semantic similarity calculation and enrichment analysis methods have been proposed for such the tasks. A number of tools have been developed on different platforms for semantic similarity calculation, enrichment analysis and ontology visualization. However, these tools have implemented a small number of the semantic similarity calculation and enrichment analysis methods for a certain type of biomedical ontology. Note that, the methods can be applied to all types of biomedical ontologies. In addition, each methods is dominant in different biomedical applications. Results In this study, we developed a Cytoscape app, named UFO, which unifies most of the semantic similarity measures for similarity calculation for all types of biomedical ontologies. Based on the similarity calculation, UFO can calculate the similarity between two sets of entities and weigh imported entity networks as well as generate functional similarity networks. In addition, it can perform enrichment analysis of a set of entities by different methods. Moreover, UFO can visualize structural relationships between ontology terms, annotating relationships between entities and terms, and functional similarity between entities. Finally, we demonstrated the ability of UFO through a number of case studies on finding best semantic similarity measures for assessing similarity between human disease phenotypes and on constructing gene and protein complex similarity networks for predicting disease-associated biomarkers. Conclusions Taken together, UFO is expected to be a tool where biomedical ontologies can be exploited for various biomedical applications.

umsubtyping

Uveal melanoma (UM) is a comparatively rare cancer but requires significant consideration since patients with developing metastatic diagnosis survive only for about 6-12 months. Fortunately, increasingly large multi-omics databases allow us to further understand cancer initiation and development. Moreover, previous studies have observed that the association between copy number aberrations (CNA) and methylation (MET) has affected these processes. From that, we decided to explore the effect of this association on a case study of UM. Also, the current subtypes of UM display its weak association with biological phenotypes and its lack of therapy suggestions. Therefore, the re-identification of molecular subtype is essential for UM patients. This repository provides data and source code for the task.