KnetMiner 5.6: Leaping into Multispecies

KnetMiner 5.6 brings multispecies functionality, performance improvements, bug fixes, UI enhancements, website improvements, a new tutorial, several new species and updated datasets.

Key new features

Multispecies functionality

KnetMiner 5.6 has taken a significant step forward with the introduction of multispecies functionality, which enables the configuration of a knowledge graph with multiple species. This feature provides users with a species selector in the header, allowing them to choose from the available species listed in the configuration file. By selecting a specific species, users can conduct targeted searches and queries that are specific to that species.

The results pages have received new updates. The Gene View tab now only displays genes belonging to the selected species, further refining search results to match the user’s needs. However, the Evidence View columns, such as p-value and total genes, are still based on all species data, providing a broader context for the selected genes. With the Map View tab, the chromosome map is automatically selected for the chosen species, allowing users to visualize the location of genes on the chromosome more efficiently. The Network View feature still shows nodes and relations across all species present in the knowledge graph, providing a comprehensive overview of the network.

These changes represent a significant improvement in the tool’s functionality, making it more user-friendly and species-specific.

Multispecies Selector example

YAML based configuration

The introduction of a YAML-based configuration system is a significant enhancement to KnetMiner. This update provides users with an easy-to-use and flexible way to configure and customise their KnetMiner instances. The ability to efficiently customise and extend default settings through inclusions, overrides, and merges is a powerful feature that can save a lot of time and effort. Moreover, the support for advanced features like special markers, rules, and property interpolation makes the configuration system even more powerful and versatile. We recommend users to refer to the documentation available on GitHub to learn more about creating and configuring a KnetMiner instance.

Gene names and synonyms

Previously we had introduced several enhancements to improve the efficiency and accuracy of gene searches. In release 5.6 this has been rounded up. In Gene View, all names and synonyms for a gene can now be viewed directly, making it easier to access relevant information. Furthermore, we have improved our approach to selecting a default gene name from multiple possibilities, resulting in a consistent experience across all results views. In Network View, KnetMiner now adds species initials to the front of gene labels, which will save users time and effort by facilitating the identification of genes from different species without having to click on each node.

Gene synonym viewer (left). Prefixed species initials (right).

Network data exporter

We understand that being able to export network data is essential for your work, and so we’ve introduced a new network data exporter feature in KnetMiner. You can now export your network data in both Tabular and Cytoscape desktop (JSON) formats, making it easier to conduct further analytics in Cytoscape or generate tables for reports. The exported data includes essential information about visible nodes and edges, such as their types and labels. However, it does not export all the node and edge properties shown in the KnetMiner Info Box. For guidance on how to import the exported JSON data into Cytoscape Desktop, our handy guide will pop up after clicking the download button.

Data exporter dropdown in Network view.

Gene Ranking via KnetScore

We’ve added a new feature to Gene View that allows you to view KnetScore – the ranking system used to measure the evidence and significance of candidate genes. This feature was published in the KnetMiner paper Hassani-Pak et al., (2021).

With KnetScore now visible in Gene View, you can easily sort and rank your candidate genes based on their evidence and significance. This feature will be particularly useful when prioritizing genes based on a single score. We’re excited to bring this enhancement to our users and look forward to hearing how it helps you in your research.

Evidence View Enhancements

We have made some exciting enhancements to the Evidence View in KnetMiner. To further streamline the gene discovery process, we have introduced a new feature that enables users to quickly view all genes connected to particular evidence nodes via semantic motifs (curated graph paths). By clicking the green icon beside the Gene count in Evidence View, a popup appears, allowing users to easily download the entire table or copy all gene accessions for KnetMiner Gene List Search. With this new feature, it’s easier than ever to search and analyze in a recursive manner. For example, users can identify all DEAD-box genes, copy their gene accessions, run a new search to identify enriched GO or TO terms in Evidence View, and continue to iterate on the process. These enhancements will allow KnetMiner power users to discover new insights and relationships faster and more efficiently than ever before.

Gene List functionality in Evidence View.

KnetGraph programmatic endpoints

We are excited to announce that we have modernized KnetMiner’s programmatic endpoints homepage to make it more user-friendly and accessible. The updated homepage includes updated links and improved key features such as the logo and key texts, providing a more engaging and informative experience for our users.

Please note that the KnetGraphs license allows for academic use only. If you would like to use the graph endpoints for any other purposes, please contact us for a quote. We are happy to work with you to provide the necessary resources to support your research needs.

Our programmatic endpoints provide access to KnetMiner’s rich knowledge graph and enable users to perform complex analyses and build custom applications. With the updated homepage, it is now easier than ever to access and utilize these powerful tools in your research projects.

We welcome you to explore KnetMiner’s programmatic endpoints and discover how they can enhance your gene discovery and complex trait analysis efforts.

Take a look here.

Modernised KnetGraph endpoint page.

New Tutorial

New KnetMiner users can now take advantage of our improved Tutorial pages, featuring an updated design and enhanced functionality. The tutorial provides an intuitive platform for users to quickly troubleshoot issues or learn about particular features.

To ensure that the tutorial is easily accessible, we have included a link to the tutorial page in the KnetMiner header. We have also ensured that the tutorial page is Google indexed, making it easier for users to find the information they need quickly and efficiently.

Whether you are an experienced KnetMiner user or just starting out, our tutorial is an invaluable resource for getting the most out of our platform. Visit the tutorial here to learn more.

New tutorial homepage.

Improved Evidence Filtering

We’ve also improved the evidence type filter in Gene and Evidence View. The evidence type names are now shown next to the symbols, and it’s possible to filter based on multiple types.

To infinity and beyond

We’re thrilled to have shared some of the exciting updates that have come with KnetMiner 5.6! While we’ve only touched on a few of the major user experience improvements, we’ve closed over 79 tickets during this update, and we’re constantly working on making KnetMiner even better.

If you’re a KnetMiner user, we encourage you to read more about ongoing updates on our website, and for developers, we recommend checking out our Revision History to learn more about current and past updates.

Our team is dedicated to making KnetMiner the best gene discovery platform out there, and we have big plans for the future. So stay tuned for more updates as we continue to enhance and improve the tool to support efficient gene discovery and complex trait analysis across species.

Upgrade to KnetMiner Pro and expand your research capabilities on Poaceae and Ascomycota. With the Pro plan, users can search using more genes, construct larger networks, and have more storage space for their networks. Users can easily upgrade to Pro by visiting our pricing page or contacting us directly.

Our new Paid KnetMiner bundles offer even more species and relationships to explore. We have carefully curated rich knowledge graphs for Poaceae, Solanaceae, and Brassicaceae, which span homology, literature, and phenotype data across related species. If you’re interested in a bespoke multi-species knowledge graph tailored to your species of interest, please don’t hesitate to contact us. We’d be happy to provide you with a quote and discuss how we can help enhance your research.

Happy KnetMining!