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KnetMiner

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KnetMiner
Content
DescriptionKnowledge Network Miner
Data types
captured
Knowledge Discovery and Visualisation
Contact
Research centerRothamsted Research
LaboratoryBioinformatics
Primary citationdoi:10.1111/pbi.13583
Release dateOctober 2013
Access
Websiteknetminer.org
Tools
WebKnetMiner Gene View

KnetMiner Evidence View KnetMiner Network View

Ondex-knet-builder data integration platform
Miscellaneous
LicenseMIT
VersioningYes
Data release
frequency
Quarterly
Version4.0 (June 2020)
Curation policyManual Curation

Knowledge Network Miner[1](KnetMiner)[2][3] is a system of tools used to integrate, search, and visualize biological knowledge graphs (KGs). It is used to search for information across large biological databases and literature to find links between genes, traits, diseases, and other relevant information.

Current KnetMiners (non-exhaustive)

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KnetMiner KGs are built using the data integration platform, KnetBuilder, with output available in OXL, Neo4j, and RDF graph formats. It follows FAIR data[4] principles and supports a variety of biological data formats. The KnetMiner API provides web endpoints that enable users to search for specific genes and keywords, returning results in the form of a knowledge graph.

Originally developed through a collaboration of researchers at Rothamsted Research, KnetMiner has undergone further development and has initiated a spin-out process.

KnetMiner hosts a range of different species, including a knowledge graph dedicated to SARS-CoV-2[5][6] in response to the 2020 global pandemic, on Rothamsted Research HPC machines.

Species included in KnetMiner's knowledge graphs:

KnetMiner has been involved in several studies, including studies for wheat,[7][8][9] willow,[9] and SARS-CoV-2.[5] It is also being used for exploring pathogen-host interactions in collaboration with PHI-base, soybean loopers, and other species.

API access

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KnetMiner uses REST API access to obtain either JSON outputs of each view type or network views for certain searches.

Funding

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KnetMiner is funded by the Biotechnology and Biological Sciences Research Council, a UK research council.[2]

References

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  1. ^ "knetMiner".
  2. ^ a b Hassani‐Pak, Keywan; Singh, Ajit; Brandizi, Marco; Hearnshaw, Joseph; Parsons, Jeremy D.; Amberkar, Sandeep; Phillips, Andrew L.; Doonan, John H.; Rawlings, Chris (2021-03-22). "KnetMiner: a comprehensive approach for supporting evidence‐based gene discovery and complex trait analysis across species". Plant Biotechnology Journal. 19 (8): 1670–1678. doi:10.1111/pbi.13583. ISSN 1467-7644. PMC 8384599. PMID 33750020.
  3. ^ Hassani-Pak, Keywan (2017). "KnetMiner - An integrated data platform for gene mining and biological knowledge discovery". Bielefeld University, Bielefeld.
  4. ^ Brandizi, Marco; Singh, Ajit; Rawlings, Christopher; Hassani-Pak, Keywan (2018). "Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach". Journal of Integrative Bioinformatics. 15 (3). doi:10.1515/jib-2018-0023. ISSN 1613-4516. PMC 6340125. PMID 30085931.
  5. ^ a b Hearnshaw, Joseph; Brandizi, Marco; Singh, Ajit; Hassani-Pak, Keywan. "Rothamsted Answers White House Call For Coronavirus Data Help". Rothamsted Research.
  6. ^ "Artificial-intelligence tools aim to tame the coronavirus literature". Nature.
  7. ^ Adamski, Nikolai M; Borrill, Philippa; Brinton, Jemima; Harrington, Sophie; Marchal, Clemence; Bentley, Alison R; Bovill, Wiliam D; Cattivelli, Luigi; Cockram, James; Contreras-Moreira, Bruno; Ford, Brett; Ghosh, Sreya; Harwood, Wendy; Hassani-Pak, Keywan; Hayta, Sadiye; Hickey, Lee T; Kanyuka, Kostya; King, Julie; Maccaferri, Marco; Naamati, Guy; Pozniak, Curtis J; Ramirez-Gonzalez, Ricardo H; Sansaloni, Carolina; Trevaskis, Ben; Wingen, Luzie U; Wulff, Brande BH; Uauy, Cristobal. "A roadmap for gene functional characterisation in wheat" (PDF). doi:10.7287/peerj.preprints.26877v2. S2CID 43925415. {{cite journal}}: Cite journal requires |journal= (help)
  8. ^ Harrington, Sophie A.; Backhaus, Anna E.; Singh, Ajit; Hassani-Pak, Keywan; Uauy, Cristobal (2019). "Validation and characterisation of a wheat GENIE3 network using an independent RNA-Seq dataset". doi:10.1101/684183. S2CID 198383382. {{cite journal}}: Cite journal requires |journal= (help)
  9. ^ a b Alabdullah, Abdul Kader; Borrill, Philippa; Martin, Azahara C.; Ramirez-Gonzalez, Ricardo H.; Hassani-Pak, Keywan; Uauy, Cristobal; Shaw, Peter; Moore, Graham (2019). "A Co-Expression Network in Hexaploid Wheat Reveals Mostly Balanced Expression and Lack of Significant Gene Loss of Homeologous Meiotic Genes Upon Polyploidization". Frontiers in Plant Science. 10: 1325. doi:10.3389/fpls.2019.01325. ISSN 1664-462X. PMC 6813927. PMID 31681395.