Peter Robinson

Peter Robinson
Jackson Laboratory for Genomic Medicine, Farmington CT, United States

MD, MSc., Dr. med., Dr. habil.

About

494
Publications
84,304
Reads
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19,478
Citations
Additional affiliations
August 2016 - August 2026
Jackson Laboratory for Genomic Medicine, Farmington CT, United States
Position
  • Professor
January 2013 - July 2016
Freie Universität Berlin
Position
  • Professor
Description
  • Professor of bioinformatics
February 2001 - present
Charité Universitätsmedizin Berlin
Position
  • Professor (Associate)

Publications

Publications (494)
Preprint
Full-text available
Common data models solve many challenges of standardizing electronic health record (EHR) data, but are unable to semantically integrate the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide semantically computable representations of biological knowledge and enable the integration of a va...
Preprint
Full-text available
Background With the continuing COVID-19 pandemic, identifying medications that improve COVID-19 outcomes is crucial. Studies suggest that use of metformin, an oral antihyperglycemic, is associated with reduced COVID-19 severity in individuals with diabetes compared to other antihyperglycemic medications. Some patients without diabetes, including th...
Article
The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, an...
Article
A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient...
Article
Full-text available
Dyskeratosis congenita (DC) is an inherited bone-marrow-failure disorder characterized by a triad of mucocutaneous features that include abnormal skin pigmentation, nail dystrophy, and oral leucoplakia. Despite the identification of several genetic variants that cause DC, a significant proportion of probands remain without a molecular diagnosis. In...
Article
Technological advances in both genome sequencing and prenatal imaging are increasing our ability to accurately recognize and diagnose Mendelian conditions prenatally. Phenotype‐driven early genetic diagnosis of fetal genetic disease can help to strategize treatment options and clinical preventive measures during the perinatal period, to plan in ute...
Preprint
Acute COVID-19 infection can be followed by persistent or newly diagnosed manifestations in many different organ systems, referred to as Post Acute Sequelae of SARS-CoV2 Infection (PASC). Numerous studies have shown an increased risk of being diagnosed with new-onset psychiatric disease in the first 21-120 days following a diagnosis of acute COVID-...
Chapter
In the context of Genomic and Precision Medicine, prediction problems are often characterized by a high imbalance between classes and Big Data. This requires specialized tools, as traditional Machine Learning approaches may struggle with big datasets and often fail to predict the minority class with unbalanced classification problems. In this work...
Article
Full-text available
While great advances in predicting the effects of coding variants have been made, the assessment of non-coding variants remains challenging. This is especially problematic for variants within promoter regions which can lead to over-expression of a gene or reduce or even abolish its expression. The binding of transcription factors to the DNA can be...
Preprint
Accurate stratification of patients with Post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies and could enable more focussed investigation of the molecular pathogenetic mechanisms of this disease. However, the natural history of long COVID is incompletely understood and characterized...
Article
Full-text available
Yuan et al. recently described an independent evaluation of several phenotype-driven gene prioritization methods for Mendelian disease on two separate, clinical datasets. Although they attempted to use default settings for each tool, we describe three key differences from those we currently recommend for our Exomiser and PhenIX tools. These influen...
Article
Full-text available
Background Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COV...
Article
Full-text available
Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to sequencing technology limitations. Long-read sequencing enables comprehensive detection of SVs, but approaches for prioritization of candidate SVs are needed. Structural variant Annotation and analysis (SvAnna) asses...
Preprint
There are thousands of distinct disease entities and concepts, each of which are known by different and sometimes contradictory names. The lack of a unified system for managing these entities poses a major challenge for both machines and humans that need to harmonize information to better predict causes and treatments for disease. The Mondo Disease...
Article
Rare disease diagnostics and disease gene discovery have been revolutionized by whole exome and genome sequencing but identifying the causative variant(s) from the millions in each individual remains challenging. Use of deep phenotyping of patients and reference genotype‐phenotype knowledge, alongside variant data such as allele frequency, segregat...
Article
Purpose Genomic test results, regardless of laboratory variant classification, require clinical practitioners to judge the applicability of a variant for medical decisions. Teaching and standardizing clinical interpretation of genomic variation calls for a methodology or tool. Methods To generate such a tool, we distilled the Clinical Genome Resou...
Article
Importance: Prior observational studies suggest that aspirin use may be associated with reduced mortality in high-risk hospitalized patients with COVID-19, but aspirin's efficacy in patients with moderate COVID-19 is not well studied. Objective: To assess whether early aspirin use is associated with lower odds of in-hospital mortality in patient...
Article
The study aims at developing a neural network model to improve the performance of Human Phenotype Ontology (HPO) concept recognition tools. We used the terms, definitions, and comments about the phenotypic concepts in the HPO database to train our model. The document to be analyzed is first split into sentences and annotated with a base method to g...
Article
Full-text available
Viruses can subvert a number of cellular processes including splicing in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 publ...
Preprint
Full-text available
Background: COVID-19 has been shown to increase the risk of adverse mental health consequences. A recent electronic health record (EHR)-based observational study showed an almost two-fold increased risk of new-onset mental illness in the first 90 days following a diagnosis of acute COVID-19. Methods: We used the National COVID Cohort Collaborative,...
Article
Full-text available
Background COVID-19 has been shown to increase the risk of adverse mental health consequences. A recent electronic health record (EHR)-based observational study showed an almost two-fold increased risk of new-onset mental illness in the first 90 days following a diagnosis of acute COVID-19. Methods We used the National COVID Cohort Collaborative, a...
Article
Full-text available
Background Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or “long COVID”), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the nat...
Article
Full-text available
The aim of this retrospective study is to assess any association between abdominal CT findings and the radiological stage of COVID-19 pneumonia, pulmonary embolism and patient outcomes. We included 158 adult hospitalized COVID-19 patients between 1 March 2020 and 1 March 2021 who underwent 206 abdominal CTs. Two radiologists reviewed all CT images....
Article
BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the na...
Preprint
Full-text available
Despite great strides in the development and wide acceptance of standards for exchanging structured information about genomic variants, there is no corresponding standard for exchanging phenotypic data, and this has impeded the sharing of phenotypic information for computational analysis. Here, we introduce the Global Alliance for Genomics and Heal...
Article
Full-text available
A critical challenge in genetic diagnostics is the computational assessment of candidate splice variants, specifically the interpretation of nucleotide changes located outside of the highly conserved dinucleotide sequences at the 5 0 and 3 0 ends of introns. To address this gap, we developed the Super Quick Information-content Random-forest Learnin...
Article
Full-text available
Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable an...
Preprint
Full-text available
Graph Representation Learning methods have enabled a wide range of learning problems to be addressed for data that can be represented in graph form. Nevertheless, several real world problems in economy, biology, medicine and other fields raised relevant scaling problems with existing methods and their software implementation, due to the size of rea...
Article
Full-text available
Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of >530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learni...
Preprint
Full-text available
Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to limitations of existing technology. Recent technological advances such as long-read sequencing (LRS) enable more comprehensive detection of SVs, but approaches for clinical prioritization of candidate SVs are needed....
Article
Full-text available
A critical challenge in genetic diagnostics is the computational assessment of candidate splice variants, specifically the interpretation of nucleotide changes located outside of the highly conserved dinucleotide sequences at the 5' and 3' ends of introns. To address this gap, we developed the Super Quick Information-content Random-forest Learning...
Article
Full-text available
Motivation: Automated protein function prediction is a complex multi-class, multi-label, structured classification problem in which protein functions are organized in a controlled vocabulary, according to the Gene Ontology (GO). "Hierarchy-unaware" classifiers, also known as "flat" methods, predict GO terms without exploiting the inherent structur...
Preprint
Full-text available
Viruses can subvert a number of cellular processes in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental...
Preprint
Full-text available
Importance: Since late 2019, the novel coronavirus SARS-CoV-2 has given rise to a global pandemic and introduced many health challenges with economic, social, and political consequences. In addition to a complex acute presentation that can affect multiple organ systems, there is mounting evidence of various persistent long-term sequelae. The worldw...
Article
Full-text available
Importance Since late 2019, the novel coronavirus SARS-CoV-2 has given rise to a global pandemic and introduced many health challenges with economic, social, and political consequences. In addition to a complex acute presentation that can affect multiple organ systems, there is mounting evidence of various persistent long-term sequelae. The worldwi...
Preprint
Full-text available
Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of more than 530 PKs have been targeted by FDA-approved medications and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machin...
Article
Full-text available
In mouse development, long-term silencing by CpG island DNA methylation is specifically targeted to germline genes; however, the molecular mechanisms of this specificity remain unclear. Here, we demonstrate that the transcription factor E2F6, a member of the polycomb repressive complex 1.6 (PRC1.6), is critical to target and initiate epigenetic sil...
Preprint
Objective Models of Gene Regulatory Networks (GRNs) capture the dynamics of the regulatory processes that occur within the cell as a means to understand the variability observed in gene expression between different conditions. Possibly the simplest mathematical construct used for modeling is the Boolean network, which dictates a set of logical rule...
Article
Full-text available
Objective: The clinical features of epilepsy determine how it is defined, which in turn guides management. Therefore, consideration of the fundamental clinical entities that comprise an epilepsy is essential in the study of causes, trajectories, and treatment responses. The Human Phenotype Ontology (HPO) is used widely in clinical and research gen...
Article
Full-text available
BACKGROUND Accurate, detailed and standardized phenotypic descriptions are essential to support diagnostic interpretation of genetic variants and to discover new diseases. The Human Phenotype Ontology (HPO), extensively used in rare disease research, provides a rich collection of vocabulary with standardized phenotypic descriptions in a hierarchica...
Preprint
Full-text available
BACKGROUND Cyclooxygenase (COX) inhibitors including non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community acquired pneumonia and other respiratory tract infections (RTIs). Conclusive data are not available about potential beneficial or adver...
Preprint
Full-text available
Since late 2019, the novel coronavirus SARS-CoV-2 has introduced a wide array of health challenges globally. In addition to a complex acute presentation that can affect multiple organ systems, increasing evidence points to long-term sequelae being common and impactful. As the worldwide scientific community forges ahead with efforts to characterize...
Article
Full-text available
Andrea Esposito,1 Elena Casiraghi,2 Francesca Chiaraviglio,1 Alice Scarabelli,3 Elvira Stellato,3 Guido Plensich,3 Giulia Lastella,1 Letizia Di Meglio,3 Stefano Fusco,3 Emanuele Avola,3 Alessandro Jachetti,4 Caterina Giannitto,5 Dario Malchiodi,2 Marco Frasca,2 Afshin Beheshti,6,7 Peter N Robinson,8,9 Giorgio Valentini,2 Laura Forzenigo,1 Gianpaolo...
Preprint
Full-text available
A critical challenge in genetic diagnostics is the computational assessment of candidate splice variants, specifically the interpretation of nucleotide changes located outside of the highly conserved dinucleotide sequences at the 5′ and 3′ ends of introns. To address this gap, we developed the Super Quick Information-content Random-forest Learning...
Article
Motivation Automatic phenotype concept recognition from unstructured text remains a challenging task in biomedical text mining research. Previous works that address the task typically use dictionary-based matching methods, which can achieve high precision but suffer from lower recall. Recently, machine learning-based methods have been proposed to i...
Preprint
Full-text available
Maximizing the personal, public, research, and clinical value of genomic information will require that clinicians, researchers, and testing laboratories exchange genetic variation data reliably. Developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the...
Article
Full-text available
Significance Inherited GPI-anchor biosynthesis deficiencies (IGDs) explain many cases of syndromic intellectual disability. Although diagnostic methods are improving, the pathophysiology underlying the disease remains unclear. Furthermore, we lack rodent models suitable for characterizing cognitive and social disabilities. To address this issue, we...
Preprint
Full-text available
We introduce a set of algorithms (Het-node2vec) that extend the original node2vec node-neighborhood sampling method to heterogeneous multigraphs, i.e. networks characterized by multiple types of nodes and edges. The resulting random walk samples capture both the structural characteristics of the graph and the semantics of the different types of nod...
Article
Full-text available
The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions...
Article
Full-text available
Background: Defects in the glycosylphosphatidylinositol (GPI) biosynthesis pathway can result in a group of congenital disorders of glycosylation known as the inherited GPI deficiencies (IGDs). To date, defects in 22 of the 29 genes in the GPI biosynthesis pathway have been identified in IGDs. The early phase of the biosynthetic pathway assembles...
Article
Full-text available
Between January and October of 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has infected more than 34 million persons in a worldwide pandemic leading to over one million deaths worldwide (data from the Johns Hopkins University). Since the virus begun to spread, emergency departments were busy with COVID-19 patients f...
Article
Full-text available
Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time-consuming, since much of it is in siloed databas...
Preprint
Automatic phenotype concept recognition from unstructured text remains a challenging task in biomedical text mining research. Previous works that address the task typically use dictionary-based matching methods, which can achieve high precision but suffer from lower recall. Recently, machine learning-based methods have been proposed to identify bio...
Article
An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate...
Article
Full-text available
The premise of Open Science is that research and medical management will progress faster if data and knowledge are openly shared. The value of Open Science is nowhere more important and appreciated than in the rare disease (RD) community. Research into RDs has been limited by insufficient patient data and resources, a paucity of trained disease exp...
Preprint
Full-text available
Integrated, up-to-date data about SARS-CoV-2 and coronavirus disease 2019 (COVID-19) is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time consuming, since much...
Article
Full-text available
Objective: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available i...