An eUtils toolset and its use for creating a pipeline to link genomics and proteomics analyses to domain-specific biomedical literature

Nadkarni, Prakash M.; Parikh, Chirag R.

doi:10.1186/2043-9113-2-9

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…An in-house pipeline of scripts (using Linux commands) was designed around the eUtils tools ( Nadkarni and Parikh, 2012 ) from NCBI in order to download and process the SARS-CoV-2 records from NCBI’s GenBank ( https://www.ncbi.nlm.nih.gov/genbank/ ). Briefly, we used esearch and efetch commands to obtain these GenBank records.…”

Section: Methodsmentioning

confidence: 99%

Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance

Najar

Linde

Murphy

et al. 2023

eLife

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COVID19 has aptly revealed that airborne viruses such as SARS-CoV-2 with the ability to rapidly mutate, combined with high rates of transmission and fatality can cause a deadly world-wide pandemic in a matter of weeks.1 Apart from vaccines and post-infection treatment options, strategies for preparedness will be vital in responding to the current and future pandemics. Therefore, there is wide interest in approaches that allow predictions of increase in infections ('surges') before they occur. We describe here real time genomic surveillance particularly based on mutation analysis, of viral proteins as a methodology for a priori determination of surge in number of infection cases. The full results are available for SARS-CoV-2 at http://pandemics.okstate.edu/covid19/, and are updated daily as new virus sequences become available. This approach is generic and will also be applicable to other pathogens.

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Section: Methodsmentioning

confidence: 99%

Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance

Najar

Linde

Murphy

et al. 2023

eLife

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“…Proteins were aligned against the NR database using blastp followed by MEGAN classification [ 34 , 58 ]. A list of GI protein identifiers belonging to the ESCG identified bacterial orders was retrieved via an E-utilities query [ 59 ]. The second step was to classify the remaining proteins by aligning them against a GI restricted database followed by MEGAN classification.…”

Section: Methodsmentioning

confidence: 99%

Functional Profiling of Unfamiliar Microbial Communities Using a Validated De Novo Assembly Metatranscriptome Pipeline

et al. 2016

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BackgroundMetatranscriptomic landscapes can provide insights in functional relationships within natural microbial communities. Analysis of complex metatranscriptome datasets of these communities poses a considerable bioinformatic challenge since they are non-restricted with a varying number of participating strains and species. For RNA-Seq data a standard approach is to align the generated reads to a set of closely related reference genomes. This only works well for microbial communities for which a near complete catalogue of reference genomes is available at a small evolutionary distance. In this study, we focus on the design of a validated de novo metatranscriptome assembly pipeline for single-end Illumina RNA-Seq data to obtain functional and taxonomic profiles of murine microbial communities.ResultsThe here developed de novo assembly metatranscriptome pipeline combined rRNA removal, IDBA-UD assembler, functional annotation and taxonomic classification. Different assemblers were tested and validated using RNA-Seq data from an in silico generated mock community and in vivo RNA-Seq data from a restricted microbial community taken from a mouse model colonized with Altered Schaedler Flora (ASF). Precision and recall of resulting gene expression, functional and taxonomic profiles were compared to those obtained with a standard alignment method. The validated pipeline was subsequently used to generate expression profiles from non-restricted cecal communities of four C57BL/6J mice fed on a high-fat high-protein diet spiked with an RNA-Seq data set from a well-characterized human sample. The spike in control was used to estimate precision and recall at assembly, functional and taxonomic level of non-restricted communities.ConclusionsA generic de novo assembly pipeline for metatranscriptome data analysis was designed for microbial ecosystems, which can be applied for microbial metatranscriptome analysis in any chosen niche.

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“…Because of this a great number of text mining tools have been developed (see e.g. Nadkarni and Parikh, 2012).…”

Section: Information Practices In Biomedicinementioning

confidence: 99%

Using the domain analytical approach in the study of information practices in biomedicine

Roos

Hedlund

2016

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Purpose The purpose of this paper is to analyze the information practices of the researchers in biomedicine using the domain analytical approach. Design/methodology/approach The domain analytical research approach used in the study of the scientific domain of biomedicine leads to studies into the organization of sciences. By using Whitley’s dimensions of “mutual dependence” and “task uncertainty” in scientific work as a starting point the authors were able to reanalyze previously collected data. By opening up these concepts in the biomedical research work context, the authors analyzed the distinguishing features of the biomedical domain and the way these features affected researchers’ information practices. Findings Several indicators representing “task uncertainty” and “mutual dependence” in the scientific domain of biomedicine were identified. This study supports the view that in biomedicine the task uncertainty is low and researchers are mutually highly dependent on each other. Hard competition seems to be one feature, which is behind the explosion of the data and publications in this domain. This fact, on its part is directly related to the ways information is searched, followed, used and produced. The need for new easy to use services or tools for searching and following information in so called “hot” topics came apparent. Originality/value The study highlights new information about information practices in the biomedical domain. Whitley’s theory enabled a thorough analysis of the cultural and social nature of the biomedical domain and it proved to be useful in the examination of researchers’ information practices.

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An eUtils toolset and its use for creating a pipeline to link genomics and proteomics analyses to domain-specific biomedical literature

Cited by 6 publications

References 12 publications

Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance

Future COVID19 surges prediction based on SARS-CoV-2 mutations surveillance

Functional Profiling of Unfamiliar Microbial Communities Using a Validated De Novo Assembly Metatranscriptome Pipeline

Using the domain analytical approach in the study of information practices in biomedicine

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