computer science

KnetMiner

KnetMiner is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand KnetMiner rather than just read about it. In short: Knowledge Network Miner(KnetMiner) 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.

Key takeaways

KnetMiner belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect KnetMiner to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of KnetMiner from memory before moving on to harder problems.

Reference excerpt

Knowledge Network Miner(KnetMiner) 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) KnetMiner KGs are built using the data integration platform, KnetBuilder, with output available in OXL, Neo4j, and RDF graph formats. It follows FAIR data 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 in response to the 2020 global pandemic, on Rothamsted Research HPC machines. Species included in KnetMiner's knowledge graphs:

Triticum aestivum Arabidopsis thaliana Oryza sativa japonica SARS-CoV-2 Fusarium graminearum Fusarium culmorum Zymoseptoria tritici KnetMiner has been involved in several studies, including studies for wheat, willow, and SARS-CoV-2. It is also being used for exploring pathogen-host interactions in collaboration with PHI-base, soybean loopers, and other species.

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

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

References

Worked examples

Example 1 — a first encounter with KnetMiner

Start with the simplest possible case. Write down what KnetMiner claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to KnetMiner before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about KnetMiner ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of KnetMiner

In research: KnetMiner appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses KnetMiner in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: KnetMiner is common in secondary-school and first-year university syllabi. It links to neighbouring topics 2013 software, Data analysis software, so understanding it makes those chapters shorter.
In everyday life: Look for KnetMiner outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study KnetMiner in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what KnetMiner means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain KnetMiner out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is KnetMiner in simple terms?

Why does KnetMiner matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study KnetMiner?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on KnetMiner.