Peter N. Robinson

ORCID: 0000-0002-0736-9199
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About
Contact & Profiles
Research Areas
  • Genomics and Rare Diseases
  • Biomedical Text Mining and Ontologies
  • Bioinformatics and Genomic Networks
  • Connective tissue disorders research
  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Cancer Genomics and Diagnostics
  • Genomic variations and chromosomal abnormalities
  • Aortic Disease and Treatment Approaches
  • Cardiac Valve Diseases and Treatments
  • Genomics and Phylogenetic Studies
  • Semantic Web and Ontologies
  • RNA Research and Splicing
  • Gene expression and cancer classification
  • Genomics and Chromatin Dynamics
  • RNA modifications and cancer
  • Metabolism and Genetic Disorders
  • Genetics, Bioinformatics, and Biomedical Research
  • Genetic Associations and Epidemiology
  • COVID-19 Clinical Research Studies
  • Topic Modeling
  • Aortic aneurysm repair treatments
  • Long-Term Effects of COVID-19
  • RNA and protein synthesis mechanisms
  • Biochemical and Molecular Research

Jackson Laboratory
2016-2025

Berlin Institute of Health at Charité - Universitätsmedizin Berlin
2011-2025

University of Connecticut
2016-2025

Charité - Universitätsmedizin Berlin
2011-2024

Enable Biosciences (United States)
2020-2024

Monarch Media (United States)
2024

Inserm
2023

The JAX Cancer Center
2023

University of Virginia
2023

UConn Health
2021-2022

10.1016/j.ajhg.2008.02.013 article EN publisher-specific-oa The American Journal of Human Genetics 2008-04-01

Abstract The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard describe and computationally analyze phenotypic abnormalities found human disease. HPO is now worldwide for phenotype exchange. has grown steadily since its inception due considerable contributions from clinical experts researchers diverse range of disciplines. Here, we present recent major extensions the neurology, nephrology, immunology, pulmonology, newborn...

10.1093/nar/gkaa1043 article EN cc-by Nucleic Acids Research 2020-11-16

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% all using terms from ontologies anatomy, cell types, function, embryology, pathology other domains. This allows interoperability with several resources, especially...

10.1093/nar/gkt1026 article EN cc-by Nucleic Acids Research 2013-11-11

The Human Phenotype Ontology (HPO)—a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases—is used by thousands researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions clinical computable disease definitions have made HPO de facto standard for deep phenotyping in field rare disease. HPO's interoperability other ontologies has enabled it to be improve diagnostic accuracy incorporating model organism...

10.1093/nar/gky1105 article EN cc-by Nucleic Acids Research 2018-10-25

Abstract Summary: The Ontologizer is a Java application that can be used to perform statistical analysis for overrepresentation of Gene Ontology (GO) terms in sets genes or proteins derived from an experiment. implements the standard approach based on one-sided Fisher's exact test, novel parent–child method, as well topology-based algorithms. A number multiple-testing correction procedures are provided. allows users visualize data graph including all significantly overrepresented GO and...

10.1093/bioinformatics/btn250 article EN Bioinformatics 2008-05-29

Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical are abundant, these largely inaccessible to outside researchers. Statistical, machine learning, causal analyses most successful with large-scale beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level from many centers.The...

10.1093/jamia/ocaa196 article EN cc-by-nc Journal of the American Medical Informatics Association 2020-08-14

The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants be genes that have been characterized, model organisms recapitulate human or veterinary filling evolutionary gaps difficult, many resources must queried to find potentially significant genotype–phenotype associations. Non-human proven instrumental revealing...

10.1093/nar/gkw1128 article EN cc-by Nucleic Acids Research 2016-11-02

There are few better examples of the need for data sharing than in rare disease community, where patients, physicians, and researchers must search "the needle a haystack" to uncover rare, novel causes within genome. Impeding pace discovery has been existence many small siloed datasets individual research or clinical laboratory databases and/or disease-specific organizations, hoping serendipitous occasions when two distant investigators happen learn they have phenotype common can "match"...

10.1002/humu.22858 article EN Human Mutation 2015-08-13

Provision of a molecularly confirmed diagnosis in timely manner for children and adults with rare genetic diseases shortens their "diagnostic odyssey," improves disease management, fosters counseling respect to recurrence risks while assuring reproductive choices. In general clinical genetics setting, the current diagnostic rate is approximately 50%, but those who do not receive molecular after initial evaluation, that much lower. Diagnostic success these more challenging affected...

10.1016/j.ajhg.2017.04.003 article EN cc-by The American Journal of Human Genetics 2017-05-01

Abstract Motivation: High-throughput experiments such as microarray hybridizations often yield long lists of genes found to share a certain characteristic differential expression. Exploring Gene Ontology (GO) annotations for has become widespread practice get first insights into the potential biological meaning experiment. The standard statistical approach measuring overrepresentation GO terms cannot cope with dependencies resulting from structure because they analyze each term in isolation....

10.1093/bioinformatics/btm440 article EN cc-by-nc Bioinformatics 2007-09-11

Numerous new disease-gene associations have been identified by whole-exome sequencing studies in the last few years. However, many cases remain unsolved due to sheer number of candidate variants remaining after common filtering strategies such as removing low quality and those deemed unlikely be pathogenic. The observation that each our genomes contains about 100 genuine loss-of-function makes identification causative mutation problematic when using these alone. We propose wealth genotype...

10.1101/gr.160325.113 article EN cc-by Genome Research 2013-10-25
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