scholarly journals Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Jean-Philippe F Gourdine ◽  
Matthew H Brush ◽  
Nicole A Vasilevsky ◽  
Kent Shefchek ◽  
Sebastian Köhler ◽  
...  
Keyword(s):  
Rare Diseases ◽  
Semantic Analysis ◽  
Model Organism ◽  
Disease Diagnosis ◽  
Knowledge Bases ◽  
Phenotype Ontology ◽  
Human Phenotype ◽  
Biological Ontologies ◽  
Phenotype Data ◽  
Structuring Knowledge

Abstract While abnormalities related to carbohydrates (glycans) are frequent for patients with rare and undiagnosed diseases as well as in many common diseases, these glycan-related phenotypes (glycophenotypes) are not well represented in knowledge bases (KBs). If glycan-related diseases were more robustly represented and curated with glycophenotypes, these could be used for molecular phenotyping to help to realize the goals of precision medicine. Diagnosis of rare diseases by computational cross-species comparison of genotype–phenotype data has been facilitated by leveraging ontological representations of clinical phenotypes, using Human Phenotype Ontology (HPO), and model organism ontologies such as Mammalian Phenotype Ontology (MP) in the context of the Monarch Initiative. In this article, we discuss the importance and complexity of glycobiology and review the structure of glycan-related content from existing KBs and biological ontologies. We show how semantically structuring knowledge about the annotation of glycophenotypes could enhance disease diagnosis, and propose a solution to integrate glycophenotypes and related diseases into the Unified Phenotype Ontology (uPheno), HPO, Monarch and other KBs. We encourage the community to practice good identifier hygiene for glycans in support of semantic analysis, and clinicians to add glycomics to their diagnostic analyses of rare diseases.

scholarly journals RDmap: A Map for Exploring Rare Diseases

2021 ◽  
Author(s):  
Jian Yang ◽  
Cong Dong ◽  
Huilong Duan ◽  
Qiang Shu ◽  
Haomin Li
Keyword(s):  
Rare Disease ◽  
Rare Diseases ◽  
Genetic Diseases ◽  
Distance Matrix ◽  
Disease Diagnosis ◽  
Human Phenotype ◽  
Pathogenic Genes ◽  
Disease Information ◽  
Rare Genetic Diseases ◽  
Interactive Map

Abstract Background: The complexity of the phenotypic characteristics and molecular bases of many rare human genetic diseases makes the diagnosis of such diseases a challenge for clinicians. A map for visualizing, locating and navigating rare diseases based on similarity will help clinicians and researchers understand and easily explore these diseases. Methods: A distance matrix of rare diseases included in Orphanet was measured by calculating the quantitative distance among phenotypes and pathogenic genes based on Human Phenotype Ontology (HPO) and Gene Ontology (GO), and each disease was mapped into Euclidean space. A rare disease map, enhanced by clustering classes and disease information, was developed based on ECharts. Results: A rare disease map called RDmap was published at http://rdmap.nbscn.org. Total 3,287 rare diseases are included in the phenotype-based map, and 3,789 rare genetic diseases are included in the gene-based map; 1,718 overlapping diseases are connected between two maps. RDmap works similarly to the widely used Google Map service and supports zooming and panning. The phenotype similarity base disease location function performed better than traditional keyword searches in an in silico evaluation, and 20 published cases of rare diseases also demonstrated that RDmap can assist clinicians in seeking the rare disease diagnosis. Conclusion: RDmap is the first user-interactive map-style rare disease knowledgebase. It will help clinicians and researchers explore the increasingly complicated realm of rare genetic diseases.

scholarly journals RDmap: a map for exploring rare diseases

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Jian Yang ◽  
Cong Dong ◽  
Huilong Duan ◽  
Qiang Shu ◽  
Haomin Li
Keyword(s):  
Rare Disease ◽  
Rare Diseases ◽  
Genetic Diseases ◽  
Distance Matrix ◽  
Disease Diagnosis ◽  
Human Phenotype ◽  
Pathogenic Genes ◽  
Disease Information ◽  
Rare Genetic Diseases ◽  
Interactive Map

Abstract Background The complexity of the phenotypic characteristics and molecular bases of many rare human genetic diseases makes the diagnosis of such diseases a challenge for clinicians. A map for visualizing, locating and navigating rare diseases based on similarity will help clinicians and researchers understand and easily explore these diseases. Methods A distance matrix of rare diseases included in Orphanet was measured by calculating the quantitative distance among phenotypes and pathogenic genes based on Human Phenotype Ontology (HPO) and Gene Ontology (GO), and each disease was mapped into Euclidean space. A rare disease map, enhanced by clustering classes and disease information, was developed based on ECharts. Results A rare disease map called RDmap was published at http://rdmap.nbscn.org. Total 3287 rare diseases are included in the phenotype-based map, and 3789 rare genetic diseases are included in the gene-based map; 1718 overlapping diseases are connected between two maps. RDmap works similarly to the widely used Google Map service and supports zooming and panning. The phenotype similarity base disease location function performed better than traditional keyword searches in an in silico evaluation, and 20 published cases of rare diseases also demonstrated that RDmap can assist clinicians in seeking the rare disease diagnosis. Conclusion RDmap is the first user-interactive map-style rare disease knowledgebase. It will help clinicians and researchers explore the increasingly complicated realm of rare genetic diseases.

scholarly journals Identification of HOX Signatures Contributing to Oral Cancer Phenotype

2021 ◽  
Author(s):  
Kanaka Padam ◽  
Richard Morgan ◽  
Keith Hunter ◽  
Sanjiban Chakrabarty ◽  
Naveena Kumar ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Semantic Analysis ◽  
Tumor Development ◽  
Interaction Network ◽  
R Package ◽  
Tumor Formation ◽  
Phenotype Ontology ◽  
Cell Cycle Regulators ◽  
Human Phenotype ◽  
Cancer Phenotype

Abstract Purpose: Evolutionarily conserved homeobox-containing HOX genes as transcriptional regulators in the developmental specification of organisms is well known. The contribution of HOX genes involvement in oral cancer phenotype has yet to be fully ascertained.Methods: GEO datasets (GSE72627, GSE30784, GSE37991) were accessed and analyzed using GEO2R. TCGA-HNSC HTSeq-counts and clinical data were retrieved from the GDC portal for oral cavity neoplasms. Differential HOX gene expression was profiled using the DESeq2 R package with a log2 fold change cut-off (-1 and +1) and Benjamini-Hochberg p-adjusted value at <0.01. Gene set over-representation analysis and semantic analysis associated with the disease ontology were performed using ClusterProfiler R package and pathway over-representation analysis was performed using IMPaLa. HOX protein interaction network was constructed using the Pathfind R package. HOX phenotype associations were performed using Mammalian Phenotype Ontology, Human Phenotype Ontology, PhenGenI associations, Jensen tissues, and OMIM entries. Drug connectivity mapping was carried out with Dr. Insight R Package.Results: HOXB2 and HOXA5 genes were upregulated in oral dysplasia but silenced during tumor progression. Loss of HOXB2 expression was consistent through potentially malignant dysplastic oral lesions (PMOL) to primary tumor formation. HOXA10, HOXB7, HOXC6, HOXC10 and HOXD10 showed consistent upregulation from premalignancy to malignancy and were notably associated with risk factors. Overrepresentation analysis suggested HOXA10 was involved in the transcriptional misregulation leading to oral cancer phenotype. HOX subnetwork analysis showed crucial interactions with cell cycle regulators, growth responsive elements, and proto-oncogenes.Conclusion: Phenotype associations specific to the oral region involving HOX genes provide intrinsic cues to tumor development. The 5’ HOX genes were aberrantly deregulated which reflects their posterior prevalence during oral carcinogenesis.

scholarly journals The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

2013 ◽  
Vol 42 (D1) ◽  
pp. D966-D974 ◽  
Author(s):  
Sebastian Köhler ◽  
Sandra C. Doelken ◽  
Christopher J. Mungall ◽  
Sebastian Bauer ◽  
Helen V. Firth ◽  
...  
Keyword(s):  
Molecular Biology ◽  
Human Phenotype Ontology ◽  
Phenotype Ontology ◽  
Human Phenotype ◽  
Phenotype Data

scholarly journals Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research

F1000Research ◽  
2014 ◽  
Vol 2 ◽  
pp. 30 ◽  
Author(s):  
Sebastian Köhler ◽  
Sandra C Doelken ◽  
Barbara J Ruef ◽  
Sebastian Bauer ◽  
Nicole Washington ◽  
...  
Keyword(s):  
Generation Process ◽  
Tissue Formation ◽  
Phenotype Ontology ◽  
Data Generation ◽  
Gene Set Enrichment ◽  
Human Phenotype ◽  
Research Activities ◽  
Annotation Data ◽  
Human Genes ◽  
Phenotype Data

Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species.We have generated a cross-species phenotype ontology for human, mouse and zebrafish that contains classes from the Human Phenotype Ontology, Mammalian Phenotype Ontology, and generated classes for zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases.This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained from http://purl.obolibrary.org/obo/hp/uberpheno/.

scholarly journals The Xenopus Phenotype Ontology: bridging model organism phenotype data to human health and development.

2021 ◽  
Author(s):  
Malcolm E Fisher ◽  
Erik J Segerdell ◽  
Nicolas Matentzoglu ◽  
Mardi J Nenni ◽  
Joshua D Fortriede ◽  
...  
Keyword(s):  
Design Patterns ◽  
Model Organism ◽  
Model Organisms ◽  
Phenotype Ontology ◽  
Phenotypic Data ◽  
Anatomy Ontology ◽  
Ontology Language ◽  
Phenotype Data ◽  
Vertebrate Model ◽  
Research Continuum

Background: Ontologies of precisely defined, controlled vocabularies are essential to curate the results of biological experiments such that the data are machine searchable, can be computationally analyzed, and are interoperable across the biomedical research continuum. There is also an increasing need for methods to interrelate phenotypic data easily and accurately from experiments in animal models with human development and disease. Results: Here we present the Xenopus Phenotype Ontology (XPO) to annotate phenotypic data from experiments in Xenopus, one of the major vertebrate model organisms used to study gene function in development and disease. The XPO implements design patterns from the Unified Phenotype Ontology (uPheno), and the principles outlined by the Open Biological and Biomedical Ontologies (OBO Foundry) to maximize interoperability with other species and facilitate ongoing ontology management. Constructed in Web Ontology Language (OWL) the XPO combines the existing uPheno library of ontology design patterns with additional terms from the Xenopus Anatomy Ontology (XAO), the Phenotype and Trait Ontology (PATO) and the Gene Ontology (GO). The integration of these different ontologies into the XPO enables rich phenotypic curation, whilst the uPheno bridging axioms allows phenotypic data from Xenopus experiments to be related to phenotype data from other model organisms and human disease. Moreover, the simple post-composed uPheno design patterns facilitate ongoing XPO development as the generation of new terms and classes of terms can be substantially automated. Conclusions: The XPO serves as an example of current best practices to help overcome many of the inherent challenges in harmonizing phenotype data between different species. The XPO currently consists of approximately 22,000 terms and is being used to curate phenotypes by Xenbase, the Xenopus Model Organism Knowledgebase, forming a standardized corpus of genotype-phenotype data that can be directly related to other uPheno compliant resources.

scholarly journals Phenopolis: an open platform for harmonization and analysis of sequencing and phenotype data

2016 ◽  
Author(s):  
Nikolas Pontikos ◽  
Jing Yu ◽  
Fiona Blanco-Kelly ◽  
Tom Vulliamy ◽  
Tsz Lun Wong ◽  
...  
Keyword(s):  
Supplementary Information ◽  
Phenotype Ontology ◽  
Human Phenotype ◽  
Open Platform ◽  
Link Type ◽  
Variant Filtering ◽  
Phenotype Data ◽  
Supplementary Material ◽  
Intuitive Interface ◽  
Gene Prioritisation

AbstractSummaryPhenopolis is an open-source web server which provides an intuitive interface to genetic and phenotypic databases. It integrates analysis tools which include variant filtering and gene prioritisation based on phenotype. The Phenopolis platform will accelerate clinical diagnosis, gene discovery and encourage wider adoption of the Human Phenotype Ontology in the study of rare disease.Availability and ImplementationA demo of the website is available at http://phenopolis.github.io (username: demo, password: demo123). If you wish to install a local copy, souce code and installation instruction are available at https://github.com/pontikos/phenopolis. The software is implemented using Python, MongoDB, HTML/Javascript and various bash shell [email protected] informationhttp://phenopolis.github.io

Predicting genes from phenotypes using Human Phenotype Ontology (HPO) terms

2021 ◽  
Vol 132 ◽  
pp. S149
Author(s):  
Anne Slavotinek ◽  
Hannah Prasad ◽  
Hannah Hoban ◽  
Tiffany Yip ◽  
Shannon Rego ◽  
...  
Keyword(s):  
Human Phenotype Ontology ◽  
Phenotype Ontology ◽  
Human Phenotype

scholarly journals Worm Phenotype Ontology: Integrating phenotype data within and beyond the C. elegans community

2011 ◽  
Vol 12 (1) ◽  
pp. 32 ◽  
Author(s):  
Gary Schindelman ◽  
Jolene S Fernandes ◽  
Carol A Bastiani ◽  
Karen Yook ◽  
Paul W Sternberg
Keyword(s):  
Phenotype Ontology ◽  
C Elegans ◽  
Phenotype Data

Logical aspects of experimental design and analysis

2020 ◽  
pp. 142-151
Author(s):  
Валерий Иванович Хабаров
Keyword(s):  
Model Theory ◽  
Semantic Analysis ◽  
Linear Models ◽  
Intelligent System ◽  
Knowledge Bases ◽  
Object Identification ◽  
Point Of View ◽  
Applied Theory ◽  
Formal Representation ◽  
Active Object

Предложена схема формализации задач активной идентификации объекта с использованием аппарата теории моделей - современного раздела математической логики. Теория моделей позволяет погрузить предмет “планирование и анализ эксперимента” в контекст семантического анализа. Семантический анализ понимается как установление соответствия между миром и его формальным представлением. С этой точки зрения представления об исследуемом объекте выражаются в некоторой прикладной теории. Предложен вывод модели для данной теории как процесс интерпретации, в котором ключевая роль отводится “экспериментатору”. Полученные результаты могут быть использованы при проектировании архитектур интеллектуальных систем для экспериментальных исследований, для построения онтологии эксперимента, создания баз знаний Purpose. The purpose of this work is to formalize the tasks of active object identification based on the apparatus of model theory - a modern section of mathematical logic. Model theory allows putting the subject “planning and analysis of an experiment” in the context of semantic analysis. Semantic analysis is understood as establishing a correspondence between the world and its formal representation. From this point of view, the concept of the object under study is expressed in some applied theory, which allows applying formal methods of model theory to it. Methods. It is assumed that the model is derived for this theory as an interpretation process, in which the key role is assigned to the experimenter. As a research method, it is proposed to use commutative diagrams that reflect the process of interpretation and extension of communication diagrams for the so-called equipped theories of planning and analysis of experiments. Results. The properties of the proposed models are proved and examples for planning a regression experiment are presented as an illustration. It is proved that for linear models it is possible to construct a finitely axiomatization capable theory. Findings, originality. The obtained results can be used in the design of architectures for an intelligent system in experimental research, building an experiment ontology and creation of knowledge bases. These studies will allow using logical programming to implement images of the presented commutative diagrams for equipped theories as applied systems for planning and interpreting the experiment

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