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1. The Gene Ontology knowledgebase in 2023

Author

Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Buitrago, Diana Luna, Erdol, Meltem N, Gage, Matthew C, Kadhum, Mohamed Ali, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D’Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, and Berardini, Tanya Z

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, 1.1 Normal biological development and functioning, Underpinning research, Gene Ontology, Proteins, Molecular Sequence Annotation, Databases, Genetic, Computational Biology, gene annotation, gene function, knowledgebase, knowledge graphs, Gene Ontology Consortium, Developmental Biology, Biochemistry and cell biology
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023

2. Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO).

Author

Ramsey, Jolene, McIntosh, Brenley, Renfro, Daniel, Aleksander, Suzanne A, LaBonte, Sandra, Ross, Curtis, Zweifel, Adrienne E, Liles, Nathan, Farrar, Shabnam, Gill, Jason J, Erill, Ivan, Ades, Sarah, Berardini, Tanya Z, Bennett, Jennifer A, Brady, Siobhan, Britton, Robert, Carbon, Seth, Caruso, Steven M, Clements, Dave, Dalia, Ritu, Defelice, Meredith, Doyle, Erin L, Friedberg, Iddo, Gurney, Susan MR, Hughes, Lee, Johnson, Allison, Kowalski, Jason M, Li, Donghui, Lovering, Ruth C, Mans, Tamara L, McCarthy, Fiona, Moore, Sean D, Murphy, Rebecca, Paustian, Timothy D, Perdue, Sarah, Peterson, Celeste N, Prüß, Birgit M, Saha, Margaret S, Sheehy, Robert R, Tansey, John T, Temple, Louise, Thorman, Alexander William, Trevino, Saul, Vollmer, Amy Cheng, Walbot, Virginia, Willey, Joanne, Siegele, Deborah A, and Hu, James C

Subjects
Networking and Information Technology R&D, Genetics, 1.5 Resources and infrastructure (underpinning), Bioinformatics, Mathematical Sciences, Biological Sciences, Information and Computing Sciences
Abstract

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.

Published
2021

3. The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST)

Author

Touré, Vasundra, Vercruysse, Steven, Acencio, Marcio Luis, Lovering, Ruth C, Orchard, Sandra, Bradley, Glyn, Casals-Casas, Cristina, Chaouiya, Claudine, del-Toro, Noemi, Flobak, Åsmund, Gaudet, Pascale, Hermjakob, Henning, Hoyt, Charles Tapley, Licata, Luana, Lægreid, Astrid, Mungall, Christopher J, Niknejad, Anne, Panni, Simona, Perfetto, Livia, Porras, Pablo, Pratt, Dexter, Saez-Rodriguez, Julio, Thieffry, Denis, Thomas, Paul D, Türei, Dénes, and Kuiper, Martin

Subjects
Generic health relevance, Causality, Humans, Software, Mathematical Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

MotivationA large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g. gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources.ResultsHere, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources.Availability and implementationThe checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST.Supplementary informationSupplementary data are available at Bioinformatics online.

Published
2021

4. The Gene Ontology resource: enriching a GOld mine

Author

Carbon, Seth, Douglass, Eric, Good, Benjamin M, Unni, Deepak R, Harris, Nomi L, Mungall, Christopher J, Basu, Siddartha, Chisholm, Rex L, Dodson, Robert J, Hartline, Eric, Fey, Petra, Thomas, Paul D, Albou, Laurent-Philippe, Ebert, Dustin, Kesling, Michael J, Mi, Huaiyu, Muruganujan, Anushya, Huang, Xiaosong, Mushayahama, Tremayne, LaBonte, Sandra A, Siegele, Deborah A, Antonazzo, Giulia, Attrill, Helen, Brown, Nick H, Garapati, Phani, Marygold, Steven J, Trovisco, Vitor, dos Santos, Gil, Falls, Kathleen, Tabone, Christopher, Zhou, Pinglei, Goodman, Joshua L, Strelets, Victor B, Thurmond, Jim, Garmiri, Penelope, Ishtiaq, Rizwan, Rodríguez-López, Milagros, Acencio, Marcio L, Kuiper, Martin, Lægreid, Astrid, Logie, Colin, Lovering, Ruth C, Kramarz, Barbara, Saverimuttu, Shirin CC, Pinheiro, Sandra M, Gunn, Heather, Su, Renzhi, Thurlow, Katherine E, Chibucos, Marcus, Giglio, Michelle, Nadendla, Suvarna, Munro, James, Jackson, Rebecca, Duesbury, Margaret J, Del-Toro, Noemi, Meldal, Birgit HM, Paneerselvam, Kalpana, Perfetto, Livia, Porras, Pablo, Orchard, Sandra, Shrivastava, Anjali, Chang, Hsin-Yu, Finn, Robert Daniel, Mitchell, Alexander Lawson, Rawlings, Neil David, Richardson, Lorna, Sangrador-Vegas, Amaia, Blake, Judith A, Christie, Karen R, Dolan, Mary E, Drabkin, Harold J, Hill, David P, Ni, Li, Sitnikov, Dmitry M, Harris, Midori A, Oliver, Stephen G, Rutherford, Kim, Wood, Valerie, Hayles, Jaqueline, Bähler, Jürg, Bolton, Elizabeth R, De Pons, Jeffery L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Plasterer, Cody, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D’Eustachio, Peter, Matthews, Lisa, Balhoff, James P, Aleksander, Suzi A, Alexander, Michael J, Cherry, J Michael, Engel, Stacia R, Gondwe, Felix, and Karra, Kalpana

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Networking and Information Technology R&D (NITRD), Genetics, 1.5 Resources and infrastructure (underpinning), 2.6 Resources and infrastructure (aetiology), Animals, Arabidopsis, Caenorhabditis elegans, Dictyostelium, Drosophila melanogaster, Escherichia coli, Gene Ontology, Humans, Internet, Mice, Molecular Sequence Annotation, Rats, Saccharomyces cerevisiae, Schizosaccharomyces, User-Computer Interface, Zebrafish, Gene Ontology Consortium, Environmental Sciences, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences
Abstract

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

Published
2021

5. RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

Author

Sweeney, Blake A, Petrov, Anton I, Ribas, Carlos E, Finn, Robert D, Bateman, Alex, Szymanski, Maciej, Karlowski, Wojciech M, Seemann, Stefan E, Gorodkin, Jan, Cannone, Jamie J, Gutell, Robin R, Kay, Simon, Marygold, Steven, dos Santos, Gil, Frankish, Adam, Mudge, Jonathan M, Barshir, Ruth, Fishilevich, Simon, Chan, Patricia P, Lowe, Todd M, Seal, Ruth, Bruford, Elspeth, Panni, Simona, Porras, Pablo, Karagkouni, Dimitra, Hatzigeorgiou, Artemis G, Ma, Lina, Zhang, Zhang, Volders, Pieter-Jan, Mestdagh, Pieter, Griffiths-Jones, Sam, Fromm, Bastian, Peterson, Kevin J, Kalvari, Ioanna, Nawrocki, Eric P, Petrov, Anton S, Weng, Shuai, Bouchard-Bourelle, Philia, Scott, Michelle, Lui, Lauren M, Hoksza, David, Lovering, Ruth C, Kramarz, Barbara, Mani, Prita, Ramachandran, Sridhar, and Weinberg, Zasha

Subjects
Biological Sciences, Bioinformatics and Computational Biology, 2.6 Resources and infrastructure (aetiology), Animals, Apicomplexa, Base Sequence, Betacoronavirus, Databases, Nucleic Acid, Fungi, Gene Ontology, Humans, Internet, Molecular Sequence Annotation, Nucleic Acid Conformation, RNA, Untranslated, Sequence Analysis, RNA, Software, RNAcentral Consortium, Environmental Sciences, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences
Abstract

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world's largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

Published
2021

6. Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns.

Author

Wood, Valerie, Carbon, Seth, Harris, Midori A, Lock, Antonia, Engel, Stacia R, Hill, David P, Van Auken, Kimberly, Attrill, Helen, Feuermann, Marc, Gaudet, Pascale, Lovering, Ruth C, Poux, Sylvain, Rutherford, Kim M, and Mungall, Christopher J

Subjects
annotation, biocuration, gene ontology, quality control, Biochemistry and Cell Biology, Microbiology, Immunology
Abstract

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

Published
2020

7. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure.

Author

Shah, Sonia, Henry, Albert, Roselli, Carolina, Lin, Honghuang, Sveinbjörnsson, Garðar, Fatemifar, Ghazaleh, Hedman, Åsa K, Wilk, Jemma B, Morley, Michael P, Chaffin, Mark D, Helgadottir, Anna, Verweij, Niek, Dehghan, Abbas, Almgren, Peter, Andersson, Charlotte, Aragam, Krishna G, Ärnlöv, Johan, Backman, Joshua D, Biggs, Mary L, Bloom, Heather L, Brandimarto, Jeffrey, Brown, Michael R, Buckbinder, Leonard, Carey, David J, Chasman, Daniel I, Chen, Xing, Chen, Xu, Chung, Jonathan, Chutkow, William, Cook, James P, Delgado, Graciela E, Denaxas, Spiros, Doney, Alexander S, Dörr, Marcus, Dudley, Samuel C, Dunn, Michael E, Engström, Gunnar, Esko, Tõnu, Felix, Stephan B, Finan, Chris, Ford, Ian, Ghanbari, Mohsen, Ghasemi, Sahar, Giedraitis, Vilmantas, Giulianini, Franco, Gottdiener, John S, Gross, Stefan, Guðbjartsson, Daníel F, Gutmann, Rebecca, Haggerty, Christopher M, van der Harst, Pim, Hyde, Craig L, Ingelsson, Erik, Jukema, J Wouter, Kavousi, Maryam, Khaw, Kay-Tee, Kleber, Marcus E, Køber, Lars, Koekemoer, Andrea, Langenberg, Claudia, Lind, Lars, Lindgren, Cecilia M, London, Barry, Lotta, Luca A, Lovering, Ruth C, Luan, Jian'an, Magnusson, Patrik, Mahajan, Anubha, Margulies, Kenneth B, März, Winfried, Melander, Olle, Mordi, Ify R, Morgan, Thomas, Morris, Andrew D, Morris, Andrew P, Morrison, Alanna C, Nagle, Michael W, Nelson, Christopher P, Niessner, Alexander, Niiranen, Teemu, O'Donoghue, Michelle L, Owens, Anjali T, Palmer, Colin NA, Parry, Helen M, Perola, Markus, Portilla-Fernandez, Eliana, Psaty, Bruce M, Regeneron Genetics Center, Rice, Kenneth M, Ridker, Paul M, Romaine, Simon PR, Rotter, Jerome I, Salo, Perttu, Salomaa, Veikko, van Setten, Jessica, Shalaby, Alaa A, Smelser, Diane T, Smith, Nicholas L, Stender, Steen, and Stott, David J

Subjects
Regeneron Genetics Center, Humans, Atrial Fibrillation, Cardiomyopathies, Microfilament Proteins, Adaptor Proteins, Signal Transducing, Carrier Proteins, Muscle Proteins, Risk Factors, Case-Control Studies, Ventricular Function, Left, Cyclin-Dependent Kinase Inhibitor p21, Apoptosis Regulatory Proteins, Coronary Artery Disease, Heart Failure, Genome-Wide Association Study, Mendelian Randomization Analysis, Adaptor Proteins, Signal Transducing, Ventricular Function, Left
Abstract

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies.

Published
2020

8. The endocytic membrane trafficking pathway plays a major role in the risk of Parkinson's disease

Author

Bandres‐Ciga, Sara, Saez‐Atienzar, Sara, Bonet‐Ponce, Luis, Billingsley, Kimberley, Vitale, Dan, Blauwendraat, Cornelis, Gibbs, Jesse Raphael, Pihlstrøm, Lasse, Gan‐Or, Ziv, Noyce, Alastair J, Kaiyrzhanov, Rauan, Middlehurst, Ben, Kia, Demis A, Tan, Manuela, Houlden, Henry, Morris, Huw R, Plun‐Favreau, Helene, Holmans, Peter, Hardy, John, Trabzuni, Daniah, Bras, Jose, Quinn, John, Mok, Kin Y, Kinghorn, Kerri J, Wood, Nicholas W, Lewis, Patrick, Schreglmann, Sebastian, Guerreiro, Rita, Lovering, Ruth, RņBibo, Lea, Manzoni, Claudia, Rizig, Mie, Ryten, Mina, Guelfi, Sebastian, Escott‐Price, Valentina, Chelban, Viorica, Foltynie, Thomas, Williams, Nigel, Morrison, Karen E, Brice, Alexis, Danjou, Fabrice, Lesage, Suzanne, Corvol, Jean‐Christophe, Martinez, Maria, Schulte, Claudia, Brockmann, Kathrin, SimɃn‐Sȥnchez, Javier, Heutink, Peter, Rizzu, Patrizia, Sharma, Manu, Gasser, Thomas, Nicolas, Aude, Cookson, Mark R, Craig, David W, Faghri, Faraz, Gibbs, J Raphael, Hernandez, Dena G, Van Keuren‐Jensen, Kendall, Shulman, Joshua M, Iwaki, Hirotaka, Leonard, Hampton L, Nalls, Mike A, Robak, Laurie, Lubbe, Steven, Finkbeiner, Steven, Mencacci, Niccolo E, Lungu, Codrin, Singleton, Andrew B, Scholz, Sonja W, Reed, Xylena, Alcalay, Roy N, Rouleau, Guy A, Hilten, Jacobus J, Marinus, Johan, Adarmes‐GɃmez, Astrid D, Aguilar, Miquel, Alvarez, Ignacio, Alvarez, Victoria, Barrero, Francisco Javier, Yarza, Jesɐs Alberto Bergareche, Bernal‐Bernal, Inmaculada, Blazquez, Marta, Bonilla‐Toribio, Marta, Botȷa, Juan A, Boungiorno, Marȷa Teresa, Buiza‐Rueda, Dolores, Cȥmara, Ana, Carrillo, Fȥtima, CarriɃn‐Claro, Mario, Cerdan, Debora, ClarimɃn, Jordi, Compta, Yaroslau, Casa, Beatrȷz, Diez‐Fairen, Monica, Dols‐Icardo, Oriol, and Duarte, Jacinto

Subjects
Parkinson's Disease, Human Genome, Genetics, Neurosciences, Brain Disorders, Prevention, Neurodegenerative, Genetic Testing, 2.3 Psychological, social and economic factors, 2.1 Biological and endogenous factors, Aetiology, Decent Work and Economic Growth, Endocytosis, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Parkinson Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, International Parkinson's Disease Genomics Consortium, Parkinson's disease, endocytosis, genetic risk, heritability, polygenic risk score, Clinical Sciences, Human Movement and Sports Sciences, Neurology & Neurosurgery
Abstract

BackgroundPD is a complex polygenic disorder. In recent years, several genes from the endocytic membrane-trafficking pathway have been suggested to contribute to disease etiology. However, a systematic analysis of pathway-specific genetic risk factors is yet to be performed.ObjectivesTo comprehensively study the role of the endocytic membrane-trafficking pathway in the risk of PD.MethodsLinkage disequilibrium score regression was used to estimate PD heritability explained by 252 genes involved in the endocytic membrane-trafficking pathway including genome-wide association studies data from 18,869 cases and 22,452 controls. We used pathway-specific single-nucleotide polymorphisms to construct a polygenic risk score reflecting the cumulative risk of common variants. To prioritize genes for follow-up functional studies, summary-data based Mendelian randomization analyses were applied to explore possible functional genomic associations with expression or methylation quantitative trait loci.ResultsThe heritability estimate attributed to endocytic membrane-trafficking pathway was 3.58% (standard error = 1.17). Excluding previously nominated PD endocytic membrane-trafficking pathway genes, the missing heritability was 2.21% (standard error = 0.42). Random heritability simulations were estimated to be 1.44% (standard deviation = 0.54), indicating that the unbiased total heritability explained by the endocytic membrane-trafficking pathway was 2.14%. Polygenic risk score based on endocytic membrane-trafficking pathway showed a 1.25 times increase of PD risk per standard deviation of genetic risk. Finally, Mendelian randomization identified 11 endocytic membrane-trafficking pathway genes showing functional consequence associated to PD risk.ConclusionsWe provide compelling genetic evidence that the endocytic membrane-trafficking pathway plays a relevant role in disease etiology. Further research on this pathway is warranted given that critical effort should be made to identify potential avenues within this biological process suitable for therapeutic interventions. © 2019 International Parkinson and Movement Disorder Society.

Published
2019

9. RNAcentral: a hub of information for non-coding RNA sequences

Author

Sweeney, Blake A, Petrov, Anton I, Burkov, Boris, Finn, Robert D, Bateman, Alex, Szymanski, Maciej, Karlowski, Wojciech M, Gorodkin, Jan, Seemann, Stefan E, Cannone, Jamie J, Gutell, Robin R, Fey, Petra, Basu, Siddhartha, Kay, Simon, Cochrane, Guy, Billis, Kostantinos, Emmert, David, Marygold, Steven J, Huntley, Rachael P, Lovering, Ruth C, Frankish, Adam, Chan, Patricia P, Lowe, Todd M, Bruford, Elspeth, Seal, Ruth, Vandesompele, Jo, Volders, Pieter-Jan, Paraskevopoulou, Maria, Ma, Lina, Zhang, Zhang, Griffiths-Jones, Sam, Bujnicki, Janusz M, Boccaletto, Pietro, Blake, Judith A, Bult, Carol J, Chen, Runsheng, Zhao, Yi, Wood, Valerie, Rutherford, Kim, Rivas, Elena, Cole, James, Laulederkind, Stanley JF, Shimoyama, Mary, Gillespie, Marc E, Orlic-Milacic, Marija, Kalvari, Ioanna, Nawrocki, Eric, Engel, Stacia R, Cherry, J Michael, Team, SILVA, Berardini, Tanya Z, Hatzigeorgiou, Artemis, Karagkouni, Dimitra, Howe, Kevin, Davis, Paul, Dinger, Marcel, He, Shunmin, Yoshihama, Maki, Kenmochi, Naoya, Stadler, Peter F, and Williams, Kelly P

Subjects
Biological Sciences, Environmental Sciences, Chemical Sciences, The RNAcentral Consortium, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences
Published
2019

10. Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources

Author

Köhler, Sebastian, Carmody, Leigh, Vasilevsky, Nicole, Jacobsen, Julius OB, Danis, Daniel, Gourdine, Jean-Philippe, Gargano, Michael, Harris, Nomi L, Matentzoglu, Nicolas, McMurry, Julie A, Osumi-Sutherland, David, Cipriani, Valentina, Balhoff, James P, Conlin, Tom, Blau, Hannah, Baynam, Gareth, Palmer, Richard, Gratian, Dylan, Dawkins, Hugh, Segal, Michael, Jansen, Anna C, Muaz, Ahmed, Chang, Willie H, Bergerson, Jenna, Laulederkind, Stanley JF, Yüksel, Zafer, Beltran, Sergi, Freeman, Alexandra F, Sergouniotis, Panagiotis I, Durkin, Daniel, Storm, Andrea L, Hanauer, Marc, Brudno, Michael, Bello, Susan M, Sincan, Murat, Rageth, Kayli, Wheeler, Matthew T, Oegema, Renske, Lourghi, Halima, Della Rocca, Maria G, Thompson, Rachel, Castellanos, Francisco, Priest, James, Cunningham-Rundles, Charlotte, Hegde, Ayushi, Lovering, Ruth C, Hajek, Catherine, Olry, Annie, Notarangelo, Luigi, Similuk, Morgan, Zhang, Xingmin A, Gómez-Andrés, David, Lochmüller, Hanns, Dollfus, Hélène, Rosenzweig, Sergio, Marwaha, Shruti, Rath, Ana, Sullivan, Kathleen, Smith, Cynthia, Milner, Joshua D, Leroux, Dorothée, Boerkoel, Cornelius F, Klion, Amy, Carter, Melody C, Groza, Tudor, Smedley, Damian, Haendel, Melissa A, Mungall, Chris, and Robinson, Peter N

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Rare Diseases, Human Genome, Networking and Information Technology R&D (NITRD), Generic health relevance, Good Health and Well Being, Biological Ontologies, Computational Biology, Congenital Abnormalities, Databases, Genetic, Genetic Predisposition to Disease, Genetic Variation, Humans, Internet, Knowledge Bases, Phenotype, Whole Genome Sequencing, Environmental Sciences, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences
Abstract

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO's interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes.

Published
2019

11. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes.

Author

Franceschini, Nora, Giambartolomei, Claudia, de Vries, Paul S, Finan, Chris, Bis, Joshua C, Huntley, Rachael P, Lovering, Ruth C, Tajuddin, Salman M, Winkler, Thomas W, Graff, Misa, Kavousi, Maryam, Dale, Caroline, Smith, Albert V, Hofer, Edith, van Leeuwen, Elisabeth M, Nolte, Ilja M, Lu, Lingyi, Scholz, Markus, Sargurupremraj, Muralidharan, Pitkänen, Niina, Franzén, Oscar, Joshi, Peter K, Noordam, Raymond, Marioni, Riccardo E, Hwang, Shih-Jen, Musani, Solomon K, Schminke, Ulf, Palmas, Walter, Isaacs, Aaron, Correa, Adolfo, Zonderman, Alan B, Hofman, Albert, Teumer, Alexander, Cox, Amanda J, Uitterlinden, André G, Wong, Andrew, Smit, Andries J, Newman, Anne B, Britton, Annie, Ruusalepp, Arno, Sennblad, Bengt, Hedblad, Bo, Pasaniuc, Bogdan, Penninx, Brenda W, Langefeld, Carl D, Wassel, Christina L, Tzourio, Christophe, Fava, Cristiano, Baldassarre, Damiano, O'Leary, Daniel H, Teupser, Daniel, Kuh, Diana, Tremoli, Elena, Mannarino, Elmo, Grossi, Enzo, Boerwinkle, Eric, Schadt, Eric E, Ingelsson, Erik, Veglia, Fabrizio, Rivadeneira, Fernando, Beutner, Frank, Chauhan, Ganesh, Heiss, Gerardo, Snieder, Harold, Campbell, Harry, Völzke, Henry, Markus, Hugh S, Deary, Ian J, Jukema, J Wouter, de Graaf, Jacqueline, Price, Jacqueline, Pott, Janne, Hopewell, Jemma C, Liang, Jingjing, Thiery, Joachim, Engmann, Jorgen, Gertow, Karl, Rice, Kenneth, Taylor, Kent D, Dhana, Klodian, Kiemeney, Lambertus ALM, Lind, Lars, Raffield, Laura M, Launer, Lenore J, Holdt, Lesca M, Dörr, Marcus, Dichgans, Martin, Traylor, Matthew, Sitzer, Matthias, Kumari, Meena, Kivimaki, Mika, Nalls, Mike A, Melander, Olle, Raitakari, Olli, Franco, Oscar H, Rueda-Ochoa, Oscar L, Roussos, Panos, Whincup, Peter H, Amouyel, Philippe, and Giral, Philippe

Subjects
MEGASTROKE Consortium, Humans, Coronary Disease, Genetic Predisposition to Disease, Amino Acid Oxidoreductases, Protein-Lysine 6-Oxidase, Risk Factors, Lod Score, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Plaque, Atherosclerotic, Carotid Intima-Media Thickness, ADAMTS9 Protein, Plaque, Atherosclerotic, Polymorphism, Single Nucleotide
Abstract

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Published
2018

12. The gene regulation knowledge commons: the action area of GREEKC

Author

Kuiper, Martin, Bonello, Joseph, Fernández-Breis, Jesualdo T., Bucher, Philipp, Futschik, Matthias E., Gaudet, Pascale, Kulakovskiy, Ivan V., Licata, Luana, Logie, Colin, Lovering, Ruth C., Makeev, Vsevolod J., Orchard, Sandra, Panni, Simona, Perfetto, Livia, Sant, David, Schulz, Stefan, Vercruysse, Steven, Zerbino, Daniel R., and Lægreid, Astrid

Published
2022
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17. An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Author

Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T, Bankapur, Asma R, D'Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S, Kahanda, Indika, Verspoor, Karin M, Ben-Hur, Asa, Koo, Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed ME, Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching-Tai, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T, Chapman, Samuel, C., Dukka B K., Khan, Ishita K, Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E, Hieta, Reija, Legge, Duncan, Lovering, Ruth C, Magrane, Michele, Melidoni, Anna N, Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, ElShal, Sarah, Tranchevent, Léon-Charles, Das, Sayoni, Dawson, Natalie L, Lee, David, Lees, Jonathan G, Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamás, Romero, Alfonso E, Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E, Pavlidis, Paul, Feng, Shou, Cejuela, Juan M, Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio, del Pozo, Angela, Fernández, José M, Maietta, Paolo, Valencia, Alfonso, Tress, Michael L, Benso, Alfredo, Di Carlo, Stefano, Politano, Gianfranco, Savino, Alessandro, Rehman, Hafeez Ur, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W, van Dijk, Aalt DJ, Gemovic, Branislava, Glisic, Sanja, Perovic, Vladmir, Veljkovic, Veljko, Veljkovic, Nevena, Almeida-e-Silva, Danillo C, Vencio, Ricardo ZN, Sharan, Malvika, Vogel, Jörg, Kansakar, Lakesh, Zhang, Shanshan, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael JE, Wass, Mark N, Huntley, Rachael P, Martin, Maria J, O'Donovan, Claire, Robinson, Peter N, Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C, Brenner, Steven E, Linial, Michal, Orengo, Christine A, Rost, Burkhard, Greene, Casey S, Mooney, Sean D, Friedberg, Iddo, and Radivojac, Predrag

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Background: The increasing volume and variety of genotypic and phenotypic data is a major defining characteristic of modern biomedical sciences. At the same time, the limitations in technology for generating data and the inherently stochastic nature of biomolecular events have led to the discrepancy between the volume of data and the amount of knowledge gleaned from it. A major bottleneck in our ability to understand the molecular underpinnings of life is the assignment of function to biological macromolecules, especially proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, accurately assessing methods for protein function prediction and tracking progress in the field remain challenging. Methodology: We have conducted the second Critical Assessment of Functional Annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. One hundred twenty-six methods from 56 research groups were evaluated for their ability to predict biological functions using the Gene Ontology and gene-disease associations using the Human Phenotype Ontology on a set of 3,681 proteins from 18 species. CAFA2 featured significantly expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis also compared the best methods participating in CAFA1 to those of CAFA2. Conclusions: The top performing methods in CAFA2 outperformed the best methods from CAFA1, demonstrating that computational function prediction is improving. This increased accuracy can be attributed to the combined effect of the growing number of experimental annotations and improved methods for function prediction., Comment: Submitted to Genome Biology

Published
2016
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19. RNA sequencing-based transcriptome profiling of cardiac tissue implicates novel putative disease mechanisms in FLNC-associated arrhythmogenic cardiomyopathy

Author

Hall, Charlotte L., Gurha, Priyatansh, Sabater-Molina, Maria, Asimaki, Angeliki, Futema, Marta, Lovering, Ruth C., Suárez, Mari Paz, Aguilera, Beatriz, Molina, Pilar, Zorio, Esther, Coarfa, Cristian, Robertson, Matthew J., Cheedipudi, Sirisha M., Ng, Keat-eng, Delaney, Paul, Hernández, Juan Pedro, Pastor, Francisco, Gimeno, Juan R., McKenna, William J., Marian, Ali J., and Syrris, Petros

Published
2020
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20. Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Author

Adarmes-Gómez, Astrid D, Aguilar, Miquel, Aitkulova, Akbota, Akhmetzhanov, Vadim, Alcalay, Roy N, Alvarez, Ignacio, Alvarez, Victoria, Bandres-Ciga, Sara, Barrero, Francisco Javier, Bergareche Yarza, Jesús Alberto, Bernal-Bernal, Inmaculada, Billingsley, Kimberley, Blauwendraat, Cornelis, Blazquez, Marta, Bonilla-Toribio, Marta, Botía, Juan A, Boungiorno, María Teresa, Bras, Jose, Brice, Alexis, Brockmann, Kathrin, Bubb, Vivien, Buiza-Rueda, Dolores, Cámara, Ana, Carrillo, Fátima, Carrión-Claro, Mario, Cerdan, Debora, Chelban, Viorica, Clarimón, Jordi, Clarke, Carl, Compta, Yaroslau, Cookson, Mark R, Corvol, Jean-Christophe, Craig, David W, Danjou, Fabrice, Diez-Fairen, Monica, Dols-Icardo, Oriol, Duarte, Jacinto, Duran, Raquel, Escamilla-Sevilla, Francisco, Escott-Price, Valentina, Ezquerra, Mario, Faghri, Faraz, Feliz, Cici, Fernández, Manel, Fernández-Santiago, Rubén, Finkbeiner, Steven, Foltynie, Thomas, Gan-Or, Ziv, Garcia, Ciara, García-Ruiz, Pedro, Gasser, Thomas, Gibbs, J Raphael, Gomez Heredia, Maria Jose, Gómez-Garre, Pilar, González, Manuel Menéndez, Gonzalez-Aramburu, Isabel, Guelfi, Sebastian, Guerreiro, Rita, Hardy, John, Hassin-Baer, Sharon, Hernandez, Dena G, Heutink, Peter, Hoenicka, Janet, Holmans, Peter, Houlden, Henry, Infante, Jon, Iwaki, Hirotaka, Jesús, Silvia, Jimenez-Escrig, Adriano, Kaishybayeva, Gulnaz, Kaiyrzhanov, Rauan, Karimova, Altynay, Kia, Demis A, Kinghorn, Kerri J, Koks, Sulev, Krohn, Lynne, Kulisevsky, Jaime, Labrador-Espinosa, Miguel A, Leonard, Hampton L, Lesage, Suzanne, Lewis, Patrick, Lopez-Sendon, Jose Luis, Lovering, Ruth, Lubbe, Steven, Lungu, Codrin, Macias, Daniel, Majamaa, Kari, Manzoni, Claudia, Marín, Juan, Marinus, Johan, Marti, Maria Jose, Martinez, Maria, Martínez Torres, Irene, Martínez-Castrillo, Juan Carlos, Mata, Marina, Mencacci, Niccolo E, Méndez-del-Barrio, Carlota, Middlehurst, Ben, Mínguez, Adolfo, Mir, Pablo, Mok, Kin Y, Morris, Huw R, Muñoz, Esteban, Nalls, Mike A, Narendra, Derek, Noyce, Alastair J, Ojo, Oluwadamilola O, Okubadejo, Njideka U, Pagola, Ana Gorostidi, Pastor, Pau, Perez Errazquin, Francisco, Periñán-Tocino, Teresa, Pihlstrom, Lasse, Plun-Favreau, Helene, Quinn, John, R'Bibo, Lea, Reed, Xylena, Rezola, Elisabet Mondragon, Rizig, Mie, Rizzu, Patrizia, Robak, Laurie, Rodriguez, Antonio Sanchez, Rouleau, Guy A, Ruiz-Martínez, Javier, Ruz, Clara, Ryten, Mina, Sadykova, Dinara, Scholz, Sonja W, Schreglmann, Sebastian, Schulte, Claudia, Sharma, Manu, Shashkin, Chingiz, Shulman, Joshua M, Sierra, María, Siitonen, Ari, Simón-Sánchez, Javier, Singleton, Andrew B, Suarez-Sanmartin, Esther, Taba, Pille, Tabernero, Cesar, Tan, Manuela X, Tartari, Juan Pablo, Tejera-Parrado, Cristina, Toft, Mathias, Tolosa, Eduard, Trabzuni, Daniah, Valldeoriola, Francesc, van Hilten, Jacobus J, Van Keuren-Jensen, Kendall, Vargas-González, Laura, Vela, Lydia, Vives, Francisco, Williams, Nigel, Wood, Nicholas W, Zharkinbekova, Nazira, Zharmukhanov, Zharkyn, Zholdybayeva, Elena, Zimprich, Alexander, Ylikotila, Pauli, Shulman, Lisa M., von Coelln, Rainer, Reich, Stephen, Savitt, Joseph, Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Huber, Karen E., Hicks, Barry, Jewett, Ethan M., Jiang, Yunxuan, Kleinman, Aaron, Lin, Keng-Han, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., McManus, Kimberly F., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Poznik, G. David, Sathirapongsasuti, J. Fah, Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce, Vacic, Vladimir, Wang, Xin, Wilson, Catherine H., Anderson, Tim, Bentley, Steven, Dalrymple-Alford, John, Fowdar, Javed, Gratten, Jacob, Halliday, Glenda, Henders, Anjali K., Hickie, Ian, Kassam, Irfahan, Kennedy, Martin, Kwok, John, Lewis, Simon, Mellick, George, Montgomery, Grant, Pearson, John, Pitcher, Toni, Sidorenko, Julia, Silburn, Peter A., Vallerga, Costanza L., Visscher, Peter M., Wallace, Leanne, Wray, Naomi R., Xue, Angli, Yang, Jian, Zhang, Futao, Vallerga, Costanza L, Heilbron, Karl, Chang, Diana, Tan, Manuela, Young, Emily, Pihlstrøm, Lasse, Leonard, Hampton, Botia, Juan A, Jankovic, Joseph, Shulman, Lisa M, Sutherland, Margaret, Tienari, Pentti, Andreassen, Ole A, Bangale, Tushar, Hinds, David A, Hardy, John A, Visscher, Peter M, and Graham, Robert R

Published
2019
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21. SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse

Author

Koopmans, Frank, van Nierop, Pim, Andres-Alonso, Maria, Byrnes, Andrea, Cijsouw, Tony, Coba, Marcelo P., Cornelisse, L. Niels, Farrell, Ryan J., Goldschmidt, Hana L., Howrigan, Daniel P., Hussain, Natasha K., Imig, Cordelia, de Jong, Arthur P.H., Jung, Hwajin, Kohansalnodehi, Mahdokht, Kramarz, Barbara, Lipstein, Noa, Lovering, Ruth C., MacGillavry, Harold, Mariano, Vittoria, Mi, Huaiyu, Ninov, Momchil, Osumi-Sutherland, David, Pielot, Rainer, Smalla, Karl-Heinz, Tang, Haiming, Tashman, Katherine, Toonen, Ruud F.G., Verpelli, Chiara, Reig-Viader, Rita, Watanabe, Kyoko, van Weering, Jan, Achsel, Tilmann, Ashrafi, Ghazaleh, Asi, Nimra, Brown, Tyler C., De Camilli, Pietro, Feuermann, Marc, Foulger, Rebecca E., Gaudet, Pascale, Joglekar, Anoushka, Kanellopoulos, Alexandros, Malenka, Robert, Nicoll, Roger A., Pulido, Camila, de Juan-Sanz, Jaime, Sheng, Morgan, Südhof, Thomas C., Tilgner, Hagen U., Bagni, Claudia, Bayés, Àlex, Biederer, Thomas, Brose, Nils, Chua, John Jia En, Dieterich, Daniela C., Gundelfinger, Eckart D., Hoogenraad, Casper, Huganir, Richard L., Jahn, Reinhard, Kaeser, Pascal S., Kim, Eunjoon, Kreutz, Michael R., McPherson, Peter S., Neale, Ben M., O’Connor, Vincent, Posthuma, Danielle, Ryan, Timothy A., Sala, Carlo, Feng, Guoping, Hyman, Steven E., Thomas, Paul D., Smit, August B., and Verhage, Matthijs

Published
2019
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22. Representation of non-coding RNA-mediated regulation of gene expression using the Gene Ontology

Author

Antonazzo, Giulia, Gaudet, Pascale, Lovering, Ruth C., and Attrill, Helen

Abstract

ABSTRACTRegulatory non-coding RNAs (ncRNAs) are increasingly recognized as integral to the control of biological processes. This is often through the targeted regulation of mRNA expression, but this is by no means the only mechanism through which regulatory ncRNAs act. The Gene Ontology (GO) has long been used for the systematic annotation of protein-coding and ncRNA gene function, but rapid progress in the understanding of ncRNAs meant that the ontology needed to be revised to accurately reflect current knowledge. Here, a targeted effort to revise GO terms used for the annotation of regulatory ncRNAs is described, focusing on microRNAs (miRNAs), long non-coding RNAs (lncRNAs), small interfering RNAs (siRNAs) and PIWI-interacting RNAs (piRNAs). This paper provides guidance to biocurators annotating ncRNA-mediated processes using the GO and serves as background for researchers wishing to make use of the GO in their studies of ncRNAs and the biological processes they regulate.

Published
2024
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25. Towards a unified open access dataset of molecular interactions

Author

Porras, Pablo, Barrera, Elisabet, Bridge, Alan, del-Toro, Noemi, Cesareni, Gianni, Duesbury, Margaret, Hermjakob, Henning, Iannuccelli, Marta, Jurisica, Igor, Kotlyar, Max, Licata, Luana, Lovering, Ruth C., Lynn, David J., Meldal, Birgit, Nanduri, Bindu, Paneerselvam, Kalpana, Panni, Simona, Pastrello, Chiara, Pellegrini, Matteo, Perfetto, Livia, Rahimzadeh, Negin, Ratan, Prashansa, Ricard-Blum, Sylvie, Salwinski, Lukasz, Shirodkar, Gautam, Shrivastava, Anjalia, and Orchard, Sandra

Published
2020
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29. Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis

Author

White, Jon, Sofat, Reecha, Hemani, Gibran, Shah, Tina, Engmann, Jorgen, Dale, Caroline, Shah, Sonia, Kruger, Felix A, Giambartolomei, Claudia, Swerdlow, Daniel I, Palmer, Tom, McLachlan, Stela, Langenberg, Claudia, Zabaneh, Delilah, Lovering, Ruth, Cavadino, Alana, Jefferis, Barbara, Finan, Chris, Wong, Andrew, Amuzu, Antoinette, Ong, Ken, Gaunt, Tom R, Warren, Helen, Davies, Teri-Louise, Drenos, Fotios, Cooper, Jackie, Ebrahim, Shah, Lawlor, Debbie A, Talmud, Philippa J, Humphries, Steve E, Power, Christine, Hypponen, Elina, Richards, Marcus, Hardy, Rebecca, Kuh, Diana, Wareham, Nicholas, Ben-Shlomo, Yoav, Day, Ian N, Whincup, Peter, Morris, Richard, Strachan, Mark W J, Price, Jacqueline, Kumari, Meena, Kivimaki, Mika, Plagnol, Vincent, Whittaker, John C, Smith, George Davey, Dudbridge, Frank, Casas, Juan P, Holmes, Michael V, and Hingorani, Aroon D

Published
2016
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30. The Gene Ontology knowledgebase in 2023.

Author

Gene Ontology Consortium, Baryshnikova, A1, Gene Ontology Consortium, Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, Dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Luna Buitrago, Diana, Erdol, Meltem N, Gage, Matthew C, Ali Kadhum, Mohamed, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D'Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, Gene Ontology Consortium, Baryshnikova, A1, Gene Ontology Consortium, Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, Dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Luna Buitrago, Diana, Erdol, Meltem N, Gage, Matthew C, Ali Kadhum, Mohamed, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D'Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, and Bakker, Erika

Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023

31. The Gene Ontology knowledgebase in 2023

Author

Consortium, Gene Ontology, Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, Dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Buitrago, Diana Luna, Erdol, Meltem N, Gage, Matthew C, Kadhum, Mohamed Ali, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D'Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, Berardini, Tanya Z, Reiser, Leonore, Auchincloss, Andrea, Argoud-Puy, Ghislaine, Blatter, Marie-Claude, Boutet, Emmanuel, Breuza, Lionel, Casals-Casas, Cristina, Coudert, Elisabeth, Estreicher, Anne, Famiglietti, Maria Livia, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hulo, Chantal, Jungo, Florence, Le Mercier, Philippe, Lieberherr, Damien, Masson, Patrick, Pedruzzi, Ivo, Pourcel, Lucille, Poux, Sylvain, Rivoire, Catherine, Sundaram, Shyamala, Bateman, Alex, Bowler-Barnett, Emily, Bye-A-Jee, Hema, Denny, Paul, Ignatchenko, Alexandr, Ishtiaq, Rizwan, Lock, Antonia, Lussi, Yvonne, Magrane, Michele, Martin, Maria J, Orchard, Sandra, Raposo, Pedro, Speretta, Elena, Tyagi, Nidhi, Warner, Kate, Zaru, Rossana, Diehl, Alexander D, Chan, Juancarlos, Diamantakis, Stavros, Raciti, Daniela, Zarowiecki, Magdalena, Fisher, Malcolm, James-Zorn, Christina, Ponferrada, Virgilio, Zorn, Aaron, Ramachandran, Sridhar, Ruzicka, Leyla, and Westerfield, Monte

Subjects
Ecology,Evolution & Ethology, Cell Cycle & Chromosomes, Cell Biology
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023
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35. Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology

Author

Lovering, Ruth C., Roncaglia, Paola, Howe, Douglas G., Laulederkind, Stanley J.F., Khodiyar, Varsha K., Berardini, Tanya Z., Tweedie, Susan, Foulger, Rebecca E., Osumi-Sutherland, David, Campbell, Nancy H., Huntley, Rachael P., Talmud, Philippa J., Blake, Judith A., Breckenridge, Ross, Riley, Paul R., Lambiase, Pier D., Elliott, Perry M., Clapp, Lucie, Tinker, Andrew, and Hill, David P.

Published
2018
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36. Gene Ontology curation of the blood-brain barrier to improve the analysis of Alzheimer's and other neurological diseases

Author

Saverimuttu, Shirin CC, Kramarz, Barbara, Rodríguez-López, Milagros, Garmiri, Penelope, Attrill, Helen, Thurlow, Katherine E, Makris, Marios, De Miranda Pinheiro, Sandra, Orchard, Sandra, Lovering, Ruth C, Saverimuttu, Shirin CC [0000-0003-1191-2681], Rodríguez-López, Milagros [0000-0002-5691-3971], Garmiri, Penelope [0000-0002-2283-2575], Attrill, Helen [0000-0003-3212-6364], Thurlow, Katherine E [0000-0001-9985-3684], Makris, Marios [0000-0002-6176-1677], Orchard, Sandra [0000-0002-8878-3972], Lovering, Ruth C [0000-0002-9791-0064], and Apollo - University of Cambridge Repository

Subjects
Gene Ontology, Alzheimer Disease, Blood-Brain Barrier, Databases, Genetic, Computational Biology, Humans, Molecular Sequence Annotation
Abstract

Funder: National Institute for Health Research University College London Hospitals Biomedical Research Centre, The role of the blood-brain barrier (BBB) in Alzheimer's and other neurodegenerative diseases is still the subject of many studies. However, those studies using high-throughput methods have been compromised by the lack of Gene Ontology (GO) annotations describing the role of proteins in the normal function of the BBB. The GO Consortium provides a gold-standard bioinformatics resource used for analysis and interpretation of large biomedical data sets. However, the GO is also used by other research communities and, therefore, must meet a variety of demands on the breadth and depth of information that is provided. To meet the needs of the Alzheimer's research community we have focused on the GO annotation of the BBB, with over 100 transport or junctional proteins prioritized for annotation. This project has led to a substantial increase in the number of human proteins associated with BBB-relevant GO terms as well as more comprehensive annotation of these proteins in many other processes. Furthermore, data describing the microRNAs that regulate the expression of these priority proteins have also been curated. Thus, this project has increased both the breadth and depth of annotation for these prioritized BBB proteins. Database URLhttps://www.ebi.ac.uk/QuickGO/.

Published
2021

45. Contributors

Author

Ahmed, Farah, Armstrong, Catherine, Bakalakos, Athanasios, Balasubramanian, Meena, Baritussio, Anna, Bhatia, Raghav T., Bogaard, Harm J., Bogaard, Harm Jan, Boomars, Karin A., Bueser, Teofila, Caforio, Alida LP., Carmo-Fonseca, M., Carvalho, Teresa, Celant, Lucas R., Chatrath, Nikhil, Cornel, Martina C., Dooijes, Dennis, du Toit, Clea, Elliott, Perry Mark, Furtado, Marta, Giordani, Andrea Silvio, Houweling, Arjan C., Iliceto, Sabino, Jansen, Samara M.A., Kassi, Maria, Koudstaal, Thomas, Kukavica, Deni, Kumar, Dhavendra, Lambiase, Pier D., Loeys, Bart L., Louca, Panayiotis, Lovering, Ruth C., Malfait, Fransiska, Marcolongo, Renzo, Markus, Hugh Stephen, Martins, Sandra, Menni, Cristina, Mercer, Catherine L., Monserrat, Lorenzo, Munroe, Patricia B., Nogal, Ana, Olczak, Kaya, Padmanabhan, Sandosh, Papadakis, Michael, Perkins, Jonathan A., Pilichou, Kalliopi, Priori, Silvia G., Ribeiro, Marta, Sharma, Sanjay, Tan, Rhea Yan Ying, Valdes, Ana M., van de Beek, Irma, van der Crabben, Saskia N., Van Gucht, Ilse, Verstraeten, Aline, Wilson, Dirk G., and Young, William J.

Published
2024
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46. Gene-centric Association Signals for Lipids and Apolipoproteins Identified via the HumanCVD BeadChip

Author

Talmud, Philippa J., Drenos, Fotios, Shah, Sonia, Shah, Tina, Palmen, Jutta, Verzilli, Claudio, Gaunt, Tom R., Pallas, Jacky, Lovering, Ruth, Li, Kawah, Casas, Juan Pablo, Sofat, Reecha, Kumari, Meena, Rodriguez, Santiago, Johnson, Toby, Newhouse, Stephen J., Dominiczak, Anna, Samani, Nilesh J., Caulfield, Mark, Sever, Peter, Stanton, Alice, Shields, Denis C., Padmanabhan, Sandosh, Melander, Olle, Hastie, Claire, Delles, Christian, Ebrahim, Shah, Marmot, Michael G., Smith, George Davey, Lawlor, Debbie A., Munroe, Patricia B., Day, Ian N., Kivimaki, Mika, Whittaker, John, Humphries, Steve E., and Hingorani, Aroon D.

Published
2009
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50. Gene Ontology curation of the blood–brain barrier to improve the analysis of Alzheimer’s and other neurological diseases

Author

Saverimuttu, Shirin C C, primary, Kramarz, Barbara, additional, Rodríguez-López, Milagros, additional, Garmiri, Penelope, additional, Attrill, Helen, additional, Thurlow, Katherine E, additional, Makris, Marios, additional, de Miranda Pinheiro, Sandra, additional, Orchard, Sandra, additional, and Lovering, Ruth C, additional

Published
2021
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