Involving community in genes and pathway curation

Naithani, Sushma; Gupta, Parul; Preece, Justin; Garg, Priyanka; Fraser, Valerie N.; Padgitt-Cobb, Lillian K.; Martin, Matthew T.; Vining, Kelly J.; Jaiswal, Pankaj

doi:10.1093/database/bay146

Cited by 14 publications

(14 citation statements)

References 30 publications

(27 reference statements)

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“…In this work, we combined and harmonised expertise in biocuration across multiple teams, formulated clear guidelines and cross-reviewed the outcomes of our work with domain experts. Although the approach of community curation was applied in the past (Slayden et al, 2013;Naithani et al, 2019), we are not aware of any curation effort on a similar scale for a single human disease to date.…”

Section: Discussionmentioning

confidence: 99%

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

Ostaszewski

Niarakis

Mazein

et al. 2021

Molecular Systems Biology

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We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

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Section: Discussionmentioning

confidence: 99%

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

Ostaszewski

Niarakis

Mazein

et al. 2021

Molecular Systems Biology

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“…In addition to retrieving new knowledge and enriching public databases, manual biocuration projects teach students/researchers genomic data evaluation, help to build the community of biocurators ( Naithani et al, 2019 ), and provide peer-review of the public genomic datasets. The re-use of genomic and transcriptomic data for mining new insights (“data parasitism”) is already making significant impact in the field of genomics and the value of secondary data analyses and meta-analyses is being recognized.…”

Section: Discussionmentioning

confidence: 99%

Beyond gene ontology (GO): using biocuration approach to improve the gene nomenclature and functional annotation of rice S-domain kinase subfamily

Naithani¹,

Dikeman²,

Garg³

et al. 2021

PeerJ

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The S-domain subfamily of receptor-like kinases (SDRLKs) in plants is poorly characterized. Most members of this subfamily are currently assigned gene function based on the S-locus Receptor Kinase from Brassica that acts as the female determinant of self-incompatibility (SI). However, Brassica like SI mechanisms does not exist in most plants. Thus, automated Gene Ontology (GO) pipelines are not sufficient for functional annotation of SDRLK subfamily members and lead to erroneous association with the GO biological process of SI. Here, we show that manual bio-curation can help to correct and improve the gene annotations and association with relevant biological processes. Using publicly available genomic and transcriptome datasets, we conducted a detailed analysis of the expansion of the rice (Oryza sativa) SDRLK subfamily, the structure of individual genes and proteins, and their expression.The 144-member SDRLK family in rice consists of 82 receptor-like kinases (RLKs) (67 full-length, 15 truncated),12 receptor-like proteins, 14 SD kinases, 26 kinase-like and 10 GnK2 domain-containing kinases and RLKs. Except for nine genes, all other SDRLK family members are transcribed in rice, but they vary in their tissue-specific and stress-response expression profiles. Furthermore, 98 genes show differential expression under biotic stress and 98 genes show differential expression under abiotic stress conditions, but share 81 genes in common.Our analysis led to the identification of candidate genes likely to play important roles in plant development, pathogen resistance, and abiotic stress tolerance. We propose a nomenclature for 144 SDRLK gene family members based on gene/protein conserved structural features, gene expression profiles, and literature review. Our biocuration approach, rooted in the principles of findability, accessibility, interoperability and reusability, sets forth an example of how manual annotation of large-gene families can fill in the knowledge gap that exists due to the implementation of automated GO projections, thereby helping to improve the quality and contents of public databases.

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“…Therefore, increasing education in bioinformatics will provide researchers the knowledge and skills to appropriately interpret their data. Provision of sufficient bioinformatics training has long been a challenge, [27][28][29] which is being partially addressed globally with 62 events on the TeSS Bioinformatics training platform 30 (access date: 02/06/21) and over 100 open-source training materials and resources for bioinformatics available from the GOBLET training portal 31 (access date: 02/06/21), many of which are available directly from the resource providers. However, while the TeSS platform includes events covering data mining and machine learning, only a handful of these events are specifically for biologists and clinicians using bioinformatics.…”

Section: Importance Of Gomentioning

confidence: 99%

Student biocuration projects as a learning environment

2022

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Background: Bioinformatics is becoming an essential tool for the majority of biological and biomedical researchers. Although bioinformatics data is exploited by academic and industrial researchers, limited focus is on teaching this area to undergraduates, postgraduates and senior scientists. Many scientists are developing their own expertise without formal training and often without appreciating the source of the data they are reliant upon. Some universities do provide courses on a variety of bioinformatics resources and tools, a few also provide biocuration projects, during which students submit data to annotation resources. Methods: To assess the usefulness and enjoyability of annotation projects a survey was sent to University College London (UCL) students who have undertaken Gene Ontology biocuration projects. Results: Analysis of survey responses suggest that these projects provide students with an opportunity not only to learn about bioinformatics resources but also to improve their literature analysis, presentation and writing skills. Conclusion: Biocuration student projects provide valuable annotations as well as enabling students to develop a variety of skills relevant to their future careers. It is also hoped that, as future scientists, these students will critically assess their own manuscripts and ensure that these are written with the biocurators of the future in mind.

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Involving community in genes and pathway curation

Cited by 14 publications

References 30 publications

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

Beyond gene ontology (GO): using biocuration approach to improve the gene nomenclature and functional annotation of rice S-domain kinase subfamily

Student biocuration projects as a learning environment

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