Phenotype informatics

The informatics of developmental phenotypes

Year: 2025 Venue: Kaufman’s Atlas of Mouse Development Supplement Authors: Paul N. Schofield, Robert Hoehndorf, Georgios V. Gkoutos, Cynthia L. Smith DOI: 10.1016/b978-0-443-23739-3.00012-2 Topics Phenotype informatics · Biomedical informatics

Phenotype-driven discovery of digenic variants in personal genome sequences

Year: 2017 Venue: Proceedings of VarI-SIG Authors: Imane Boudellioua, Maxat Kulmanov, Paul N Schofield, Georgios V Gkoutos, Robert Hoehndorf Abstract Identification of variants associated with inherited diseases is a major challenge, in particular in the analysis of clinical sequence data from individual patients. An increasing number of Mendelian diseases have been identified in which two or more variants in multiple genes are required to cause the disease, or significantly modify its severity or phenotype. It is difficult to discover such interactions using existing approaches. Information

Integrating phenotype ontologies with PhenomeNET

Year: 2016 Venue: Proceedings of Ontology Matching Workshop 2016 Authors: Miguel Rodriguez-Garcia, Georgios V. Gkoutos, Paul N. Schofield, Robert Hoehndorf Abstract PhenomeNET is a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Here, we apply the PhenomeNET to identify related classes from four phenotype and

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

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

Towards similarity-based differential diagnostics for common diseases

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

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

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

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

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

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

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

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

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

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

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)

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

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

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 recognized, model organisms are characterized, and plant traits are cataloged. 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 standardize phenotype descriptions from text and images, and the computational pipelines that connect phenotype evidence back to genes

DeepViral

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

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

AI-powered clinical decision-support tool that ingests annotated VCFs and synthesizes diagnostic interpretations for rare-disease patients without requiring deep bioinformatics expertise. Get it GitHub: https://github.com/bio-ontology-research-group/genome-linter Developed in projects Improvement of genetic variant prioritization technology Category: Variant and Disease Prioritization

INDIGENA

Inductive prediction of disease–gene associations from phenotype ontologies; generalizes 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

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

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

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

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 Sequencing and computational analysis of MRSA samples Category: Variant and Disease Prioritization