Phenotype informatics

Chapter Four - The Neurobehavior Ontology: An Ontology for Annotation and Integration of Behavior and Behavioral Phenotypes

Applied Ontology Phenotype informatics Ontology engineering

Year: 2012 Venue: Bioinformatics of Behavior: Part 1 Authors: Georgios V. Gkoutos, Paul N. Schofield, Robert Hoehndorf DOI: 10.1016/B978-0-12-388408-4.00004-6 Abstract Abstract In recent years, considerable advances have been made toward our understanding of the genetic architecture of behavior and the physical, mental, and environmental influences that underpin behavioral processes. The provision of a method for recording behavior-related phenomena is necessary to enable integrative and comparative analyses of data and knowledge about behavior. The neurobehavior ontology facilitates the

Ontology-based cross-species integration and analysis of Saccharomyces cerevisiae phenotypes

Applied Ontology Phenotype informatics

Year: 2011 Venue: Proceedings of the 3rd Workshop for Ontologies in Biomedicine and Life sciences (OBML) Authors: Georgios V. Gkoutos, Robert Hoehndorf Abstract Ontologies are widely used in the biomedical community for annotation and integration of databases. Formal definitions can relate classes from different ontologies and thereby integrate data across different levels of granularity, domains and species. We have applied this methodology to the Ascomycete Phenotype Ontology (APO), enabling the reuse of various orthogonal ontologies and we have converted the phenotype associated data found

Towards Improving Phenotype Representation in OWL

Applied Ontology Phenotype informatics

Year: 2011 Venue: Proceedings of the 3rd Workshop for Ontologies in Biomedicine and Life sciences (OBML) Authors: Frank Loebe, Frank Stumpf, Robert Hoehndorf, Heinrich Herre Abstract Phenotype ontologies are used in species-specific databases for the annotation of mutagenesis experiments and to characterize hu- man diseases. The Entity-Quality (EQ) formalism is a means to describe complex phenotypes based on one or more affected en- tities and a quality. EQ-based definitions have been developed for many phenotype ontologies, including the Human and Mammalian Phenotype ontologies. We analyze

Quantitative comparison of mapping methods between Human and Mammalian Phenotype Ontology

Phenotype informatics Semantic similarity

Year: 2011 Venue: Proceedings of the 3rd Workshop for Ontologies in Biomedicine and Life sciences (OBML) Authors: Anika Oellrich, Robert Hoehndorf, Georgios V. Gkoutos, Dietrich Rebholz-Schuhmann Abstract Researchers use animal studies to better understand human diseases. In recent years, large-scale phenotype studies such as Phenoscape and EuroPhenome have been initiated to identify genetic causes of a species phenome. Species-specific phenotype ontologies are required to capture and report about all findings and to automatically infer results relevant to human diseases. The integration of

Semantic integration of physiology phenotypes with an application to the Cellular Phenotype Ontology

Applied Ontology Phenotype informatics Ontology engineering

Year: 2012 Venue: Bioinformatics Authors: Robert Hoehndorf, Midori A. Harris, Heinrich Herre, Gabriella Rustici, Georgios V. Gkoutos DOI: 10.1093/bioinformatics/bts250 Abstract Motivation: The systematic observation of phenotypes has become a crucial tool of functional genomics, and several large international projects are currently underway to identify and characterize the phenotypes that are associated with genotypes in several species. To integrate phenotype descriptions within and across species, phenotype ontologies have been developed. Applying ontologies to unify phenotype descriptions

Mouse genetic and phenotypic resources for human genetics

Rare disease Phenotype informatics

Venue: Human Mutation Authors: Paul N. Schofield, Robert Hoehndorf, Georgios V. Gkoutos Abstract The use of model organisms to provide information on gene function has proved to be a powerful approach to our understanding of both human disease and fundamental mammalian biology. Large-scale community projects using mice, based on forward and reverse genetics, and now the pan-genomic phenotyping efforts of the International Mouse Phenotyping Consortium (IMPC), are generating resources on an unprecedented scale which will be extremely valuable to human genetics and medicine. We discuss the nature

New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models

Applied Ontology Phenotype informatics Rare disease

Venue: Briefings in Functional Genomics Authors: Paul N. Schofield, John P. Sundberg, Robert Hoehndorf, Georgios V. Gkoutos Abstract The systematic investigation of the phenotypes associated with genotypes in model organisms holds the promise of revealing genotype–phenotype relations directly and without additional, intermediate inferences. Large-scale projects are now underway to catalog the complete phenome of a species, notably the mouse. With the increasing amount of phenotype information becoming available, a major challenge that biology faces today is the systematic analysis of this

PhenomeNET: a whole-phenome approach to disease gene discovery

Rare disease Semantic similarity Phenotype informatics

Venue: Nucleic Acids Research Authors: Robert Hoehndorf, Paul N. Schofield, Georgios V. Gkoutos Abstract Phenotypes are investigated in model organisms to understand and reveal the molecular mechanisms underlying disease. Phenotype ontologies were developed to capture and compare phenotypes within the context of a single species. Recently, these ontologies were augmented with formal class definitions that may be utilized to integrate phenotypic data and enable the direct comparison of phenotypes between different species. We have developed a method to transform phenotype ontologies into a

Interoperability between phenotype and anatomy ontologies

Applied Ontology Ontology engineering Phenotype informatics

Venue: Bioinformatics Authors: Robert Hoehndorf, Anika Oellrich, Dietrich Rebholz-Schuhmann Abstract Motivation: Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore

Taxon and trait recognition from digitized herbarium specimens using deep convolutional neural networks

Phenotype informatics Biomedical Informatics

Year: 2018 Venue: Botany Letters Authors: Sohaib Younis, Claus Weiland, Robert Hoehndorf, Stefan Dressler, Thomas Hickler, Bernhard Seeger, Marco Schmidt Abstract Herbaria worldwide are housing a treasure of hundreds of millions of herbarium specimens, which are increasingly being digitized and thereby more accessible to the scientific community. At the same time, deep-learning algorithms are rapidly improving pattern recognition from images and these techniques are more and more being applied to biological objects. In this study, we are using digital images of herbarium specimens in order to

Improved characterisation of clinical text through ontology-based vocabulary expansion

Biomedical Informatics Phenotype informatics

Year: 2021 Venue: Journal of Biomedical Semantics Authors: Luke T. Slater, William Bradlow, Simon Ball, Robert Hoehndorf, Georgios V Gkoutos DOI: 10.1186/s13326-021-00241-5 Abstract Ontology-based phenotype profiles have been utilised for the purpose of differential diagnosis of rare genetic diseases, and for decision support in specific disease domains. Particularly, semantic similarity facilitates diagnostic hypothesis generation through comparison with disease phenotype profiles. However, the approach has not been applied for differential diagnosis of common diseases, or generalised

Towards similarity-based differential diagnostics for common diseases

Biomedical Informatics Phenotype informatics

Year: 2021 Venue: Computers in Biology and Medicine Authors: Luke T. Slater, Andreas Karwath, John A. Williams, Sophie Russell, Silver Makepeace, Alexander Carberry, Robert Hoehndorf, Georgios V. Gkoutos DOI: 10.1016/j.compbiomed.2021.104360 Abstract Ontology-based phenotype profiles have been utilised for the purpose of differential diagnosis of rare genetic diseases, and for decision support in specific disease domains. Particularly, semantic similarity facilitates diagnostic hypothesis generation through comparison with disease phenotype profiles. However, the approach has not been applied

Multi-faceted semantic clustering with text-derived phenotypes

Biomedical Informatics Phenotype informatics

Year: 2021 Venue: Computers in Biology and Medicine Authors: Luke T. Slater, John A. Williams, Andreas Karwath, Hilary Fanning, Simon Ball, Paul N. Schofield, Robert Hoehndorf, Georgios V. Gkoutos DOI: 10.1016/j.compbiomed.2021.104904 Abstract Identification of ontology concepts in clinical narrative text enables the creation of phenotype profiles that can be associated with clinical entities, such as patients or drugs. Constructing patient phenotype profiles using formal ontologies enables their analysis via semantic similarity, in turn enabling the use of background knowledge in clustering

Ontology-based validation and identification of regulatory phenotypes

Applied Ontology Phenotype informatics

Year: 2018 Venue: Bioinformatics Authors: Maxat Kulmanov, Paul N Schofield, Georgios V Gkoutos, Robert Hoehndorf Abstract Motivation: Function annotations of gene products, and phenotype annotations of genotypes, provide valuable information about molecular mechanisms that can be utilized by computational methods to identify functional and phenotypic relatedness, improve our understanding of disease and pathobiology, and lead to discovery of drug targets. Identifying functions and phenotypes commonly requires experiments which are time-consuming and expensive to carry out; creating the

The anatomy of phenotype ontologies: principles, properties and applications

Applied Ontology Phenotype informatics

Year: 2018 Venue: Briefings in Bioinformatics Authors: Georgios V. Gkoutos, Paul N. Schofield, Robert Hoehndorf DOI: https://doi.org/10.1093/bib/bbx035 Abstract The past decade has seen an explosion in the collection of genotype data in domains as diverse as medicine, ecology, livestock and plant breeding. Along with this comes the challenge of dealing with the related phenotype data, which is not only large but also highly multidimensional. Computational analysis of phenotypes has therefore become critical for our ability to understand the biological meaning of genomic data in the biological

An ontology approach to comparative phenomics in plants

Applied Ontology Phenotype informatics

Year: 2015 Venue: Plant Methods Authors: Anika Oellrich, Ramona Walls, Ethalinda Cannon, Steven Cannon, Laurel Cooper, Jack Gardiner, Georgios Gkoutos, Lisa Harper, Mingze He, Robert Hoehndorf, Pankaj Jaiswal, Scott Kalberer, John Lloyd, David Meinke, Naama Menda, Laura Moore, Rex Nelson, Anuradha Pujar, Carolyn Lawrence, Eva Huala DOI: 10.1186/s13007-015-0053-y Abstract BACKGROUND:Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and

Nail abnormalities identified in an ageing study of 30 inbred mouse strains

Phenotype informatics

Year: 2019 Venue: Experimental Dermatology Authors: Sarah C. Linn, Allison M. Mustonen, Kathleen A. Silva, Victoria E. Kennedy, Beth A. Sundberg, Lesley S. Bechtold, Sarah M. Alghamdi, Robert Hoehndorf, Paul N. Schofield, John P. Sundberg DOI: 10.1111/exd.13759 Abstract In a large-scale ageing study, 30 inbred mouse strains were systematically screened for histologic evidence of lesions in all organ systems. Ten strains were diagnosed with similar nail abnormalities. The highest frequency was noted in NON/ShiLtJ mice. Lesions identified fell into two main categories: acute to chronic

The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants

Applied Ontology Phenotype informatics

Year: 2016 Venue: Journal of Biomedical Semantics Authors: Robert Hoehndorf, Mona Alshahrani, Georgios V. Gkoutos, George Gosline, Quentin Groom, Thomas Hamann, Jens Kattge, Sylvia Mota de Oliveira, Marco Schmidt, Soraya Sierra, Erik Smets, Rutger A. Vos, Claus Weiland DOI: 10.1186/s13326-016-0107-8 Abstract The systematic analysis of a large number of comparable plant trait data can support investigations into phylogenetics and ecological adaptation, with broad applications in evolutionary biology, agriculture, conservation, and the functioning of ecosystems. Floras, i.e., books collecting

DermO; an ontology for the description of dermatologic disease

Applied Ontology Phenotype informatics

Year: 2016 Venue: Journal of Biomedical Semantics Authors: Hannah M. Fisher, Robert Hoehndorf, Bruno S. Bazelato, Soheil S. Dadras, Lloyd E. King, Georgios V. Gkoutos, John P. Sundberg, Paul N. Schofield DOI: 10.1186/s13326-016-0085-x Abstract There have been repeated initiatives to produce standard nosologies and terminologies for cutaneous disease, some dedicated to the domain and some part of bigger terminologies such as ICD-10. Recently, formally structured terminologies, ontologies, have been widely developed in many areas of biomedical research. Primarily, these address the aim of

Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics

Phenotype informatics Biomedical Informatics

Year: 2015 Venue: Nature Genetics Authors: Martin Hrab\ve de Angelis, George Nicholson, Mohammed Selloum, Jacqueline K White, Hugh Morgan, Ramiro Ramirez-Solis, Tania Sorg, Sara Wells, Helmut Fuchs, Martin Fray, David J Adams, Niels C Adams, Thure Adler, Antonio Aguilar-Pimentel, Dalila Ali-Hadji, Gregory Amann, Philippe Andr\'e, Sarah Atkins, Aurelie Auburtin, Abdel Ayadi, Julien Becker, Lore Becker, Elodie Bedu, Raffi Bekeredjian, Marie-Christine Birling, Andrew Blake, Joanna Bottomley, Michael R Bowl, V\'eronique Brault, Dirk H Busch, James N Bussell, Julia Calzada-Wack, Heather Cater

Hyaline Arteriolosclerosis in 30 Strains of Aged Inbred Mice

Phenotype informatics Biomedical Informatics

Year: 2019 Venue: Veterinary Pathology Authors: Timothy K. Cooper, Kathleen A. Silva, Victoria E. Kennedy, Sarah M. Alghamdi, Robert Hoehndorf, Beth A. Sundberg, Paul N. Schofield, John P. Sundberg DOI: 10.1177/0300985819844822 Abstract During a screen for vascular phenotypes in aged laboratory mice, a unique discrete phenotype of hyaline arteriolosclerosis of the intertubular arteries and arterioles of the testes was identified in several inbred strains. Lesions were limited to the testes and did not occur as part of any renal, systemic, or pulmonary arteriopathy or vasculitis phenotype

Best behaviour? Ontologies and the formal description of animal behaviour

Applied Ontology Phenotype informatics

Year: 2015 Venue: Mammalian Genome Authors: Georgios V Gkoutos, Robert Hoehndorf, Loukia Tsaprouni, Paul N Schofield DOI: 10.1007/s00335-015-9590-y Abstract The development of ontologies for describing animal behavior has proved to be one of the most difficult of all scientific knowledge domains. Ranging from neurological processes to human emotions the range and scope needed for such ontologies is highly challenging, but if data integration and computational tools such as automated reasoning are to be fully applied in this important area the underlying principles of these ontologies need to

CAGI6 ID panel challenge: assessment of phenotype and variant predictions in 415 children with neurodevelopmental disorders (NDDs)

Rare disease Phenotype informatics

Year: 2025 Venue: Human Genetics Authors: Maria Cristina Aspromonte, Alessio Del Conte, Shaowen Zhu, Wuwei Tan, Yang Shen, Yexian Zhang, Qi Li, Maggie Haitian Wang, Giulia Babbi, Samuele Bovo, Pier Luigi Martelli, Rita Casadio, Azza Althagafi, Sumyyah Toonsi, Maxat Kulmanov, Robert Hoehndorf, Panagiotis Katsonis, Amanda Williams, Olivier Lichtarge, Su Xian, Wesley Surento, Vikas Pejaver, Sean D. Mooney, Uma Sunderam, Rajgopal Srinivasan, Alessandra Murgia, Damiano Piovesan, Silvio C. E. Tosatto, Emanuela Leonardi DOI: 10.1007/s00439-024-02722-w Abstract Abstract The Genetics of

Contribution of model organism phenotypes to the computational identification of human disease genes

Rare disease Phenotype informatics Semantic similarity

Year: 2022 Venue: Disease Models & Mechanisms Authors: Sarah Alghamdi, Paul N. Schofield, Robert Hoehndorf DOI: 10.1242/dmm.049441 Abstract Computing phenotypic similarity helps identify new disease genes and diagnose rare diseases. Genotype-phenotype data from orthologous genes in model organisms can compensate for lack of human data and increase genome coverage. In the past decade, cross-species phenotype comparisons have proven valuble, and several ontologies have been developed for this purpose. The relative contribution of different model organisms to computational identification of

DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier

Rare disease Phenotype informatics Neuro-Symbolic AI

Year: 2020 Venue: PLOS Computational Biology Authors: Maxat Kulmanov, Robert Hoehndorf DOI: 10.1371/journal.pcbi.1008453 Abstract Author summary Gene–phenotype associations can help to understand the underlying mechanisms of many genetic diseases. However, experimental identification, often involving animal models, is time consuming and expensive. Computational methods that predict gene–phenotype associations can be used instead. We developed DeepPheno, a novel approach for predicting the phenotypes resulting from a loss of function of a single gene. We use gene functions and gene expression

Phenotype informatics

Phenotypes are the observable consequences of genotype, environment, and their interaction, and they remain the principal currency by which disease is recognised, model organisms are characterised, and plant traits are catalogued. Our work develops the informatics infrastructure that makes phenotype data computable across species and clinical settings: the phenotype ontologies themselves, the cross-species crosswalks that link them, the tools that capture and standardise phenotype descriptions from text and images, and the computational pipelines that connect phenotype evidence back to genes

DeepViral

Rare disease Phenotype informatics genomics

Predicts virus–host protein-protein interactions from sequence and infectious-disease phenotypes; trained jointly across coronaviruses, influenza, and other RNA viruses. Get it GitHub: https://github.com/bio-ontology-research-group/DeepViral ★ 12 Developed in projects CompleX: Variant Prioritization in Complex Disease Category: Variant and Disease Prioritization

predCAN

Rare disease Phenotype informatics genomics

Ontology-based prediction of cancer driver genes by integrating phenotype, pathway and function knowledge with somatic-variant features. Get it GitHub: https://github.com/bio-ontology-research-group/predCAN ★ 5 Developed in projects CompleX: Variant Prioritization in Complex Disease Category: Variant and Disease Prioritization

GenomeLinter

Rare disease Phenotype informatics genomics

AI-powered clinical decision-support tool that ingests annotated VCFs and synthesises diagnostic interpretations for rare-disease patients without requiring deep bioinformatics expertise. Get it GitHub: https://github.com/bio-ontology-research-group/genome-linter Category: Variant and Disease Prioritization

INDIGENA

Rare disease Phenotype informatics genomics

Inductive prediction of disease–gene associations from phenotype ontologies; generalises to unseen diseases via ontology-aware embeddings. Get it GitHub: https://github.com/bio-ontology-research-group/indigena ★ 1 Developed in projects CompleX: Variant Prioritization in Complex Disease Category: Variant and Disease Prioritization

STARVar

Rare disease Phenotype informatics genomics

Symptom-based tool for automatic ranking of variants using evidence from the biomedical literature and population genomes; combines text mining with phenotype matching. Get it GitHub: https://github.com/bio-ontology-research-group/STARVar ★ 7 Developed in projects CompleX: Variant Prioritization in Complex Disease Category: Variant and Disease Prioritization

EmbedPVP

Rare disease Phenotype informatics genomics

Embedding-based phenotype-aware variant predictor that ranks candidate causative variants using joint sequence- and phenotype-derived representations. Get it GitHub: https://github.com/bio-ontology-research-group/EmbedPVP ★ 8 Developed in projects CompleX: Variant Prioritization in Complex Disease Category: Variant and Disease Prioritization

DeepSVP

Rare disease Phenotype informatics genomics

Prioritizes structural and copy-number variants by combining patient phenotype with gene-function similarity learned from biomedical ontologies. Get it GitHub: https://github.com/bio-ontology-research-group/DeepSVP ★ 18 Developed in projects CompleX: Variant Prioritization in Complex Disease A public Saudi pangenome as reference for genomics in the Middle East Category: Variant and Disease Prioritization

PhenomeNET-VP

Rare disease Phenotype informatics genomics

Phenotype-driven variant prioritization for whole-exome and whole-genome sequencing data; widely used implementation of the phenotype-aware variant ranking approach. Get it GitHub: https://github.com/bio-ontology-research-group/phenomenet-vp ★ 43 Developed in projects CompleX: Variant Prioritization in Complex Disease Category: Variant and Disease Prioritization